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13,402 | On the Easiest and Hardest Fitness Functions | cs.NE | The hardness of fitness functions is an important research topic in the field
of evolutionary computation. In theory, the study can help understanding the
ability of evolutionary algorithms. In practice, the study may provide a
guideline to the design of benchmarks. The aim of this paper is to answer the
following rese... | computer science |
13,403 | Neural Network Model for Path-Planning of Robotic Rover Systems | cs.NE | Today, robotics is an auspicious and fast-growing branch of technology that
involves the manufacturing, design, and maintenance of robot machines that can
operate in an autonomous fashion and can be used in a wide variety of
applications including space exploration, weaponry, household, and
transportation. More particu... | computer science |
13,404 | Managing contextual artificial neural networks with a service-based
mediator | cs.NE | Today, a wide variety of probabilistic and expert AI systems used to analyze
real world inputs such as unstructured text, sounds, images, and statistical
data. However, all these systems exist on different platforms, with different
implementations, and with very different, often very specific goals in mind.
This paper ... | computer science |
13,405 | Efficient Design of Triplet Based Spike-Timing Dependent Plasticity | cs.NE | Spike-Timing Dependent Plasticity (STDP) is believed to play an important
role in learning and the formation of computational function in the brain. The
classical model of STDP which considers the timing between pairs of
pre-synaptic and post-synaptic spikes (p-STDP) is incapable of reproducing
synaptic weight changes ... | computer science |
13,406 | Affine Image Registration Transformation Estimation Using a Real Coded
Genetic Algorithm with SBX | cs.NE | This paper describes the application of a real coded genetic algorithm (GA)
to align two or more 2-D images by means of image registration. The proposed
search strategy is a transformation parameters-based approach involving the
affine transform. The real coded GA uses Simulated Binary Crossover (SBX), a
parent-centric... | computer science |
13,407 | Self-Adaptive Surrogate-Assisted Covariance Matrix Adaptation Evolution
Strategy | cs.NE | This paper presents a novel mechanism to adapt surrogate-assisted
population-based algorithms. This mechanism is applied to ACM-ES, a recently
proposed surrogate-assisted variant of CMA-ES. The resulting algorithm,
saACM-ES, adjusts online the lifelength of the current surrogate model (the
number of CMA-ES generations ... | computer science |
13,408 | A Fast and Effective Local Search Algorithm for Optimizing the Placement
of Wind Turbines | cs.NE | The placement of wind turbines on a given area of land such that the wind
farm produces a maximum amount of energy is a challenging optimization problem.
In this article, we tackle this problem, taking into account wake effects that
are produced by the different turbines on the wind farm. We significantly
improve upon ... | computer science |
13,409 | Curved Space Optimization: A Random Search based on General Relativity
Theory | cs.NE | Designing a fast and efficient optimization method with local optima
avoidance capability on a variety of optimization problems is still an open
problem for many researchers. In this work, the concept of a new global
optimization method with an open implementation area is introduced as a Curved
Space Optimization (CSO)... | computer science |
13,410 | A Large Population Size Can Be Unhelpful in Evolutionary Algorithms | cs.NE | The utilization of populations is one of the most important features of
evolutionary algorithms (EAs). There have been many studies analyzing the
impact of different population sizes on the performance of EAs. However, most
of such studies are based computational experiments, except for a few cases.
The common wisdom s... | computer science |
13,411 | An Efficient Genetic Programming System with Geometric Semantic
Operators and its Application to Human Oral Bioavailability Prediction | cs.NE | Very recently new genetic operators, called geometric semantic operators,
have been defined for genetic programming. Contrarily to standard genetic
operators, which are uniquely based on the syntax of the individuals, these new
operators are based on their semantics, meaning with it the set of input-output
pairs on tra... | computer science |
13,412 | Learning sparse messages in networks of neural cliques | cs.NE | An extension to a recently introduced binary neural network is proposed in
order to allow the learning of sparse messages, in large numbers and with high
memory efficiency. This new network is justified both in biological and
informational terms. The learning and retrieval rules are detailed and
illustrated by various ... | computer science |
13,413 | A novel Hopfield neural network approach for minimizing total weighted
tardiness of jobs scheduled on identical machines | cs.NE | This paper explores fast, polynomial time heuristic approximate solutions to
the NP-hard problem of scheduling jobs on N identical machines. The jobs are
independent and are allowed to be stopped and restarted on another machine at a
later time. They have well-defined deadlines, and relative priorities
quantified by no... | computer science |
13,414 | Feasibility of Genetic Algorithm for Textile Defect Classification Using
Neural Network | cs.NE | The global market for textile industry is highly competitive nowadays.
Quality control in production process in textile industry has been a key factor
for retaining existence in such competitive market. Automated textile
inspection systems are very useful in this respect, because manual inspection
is time consuming and... | computer science |
13,415 | Design of Low Noise Amplifiers Using Particle Swarm Optimization | cs.NE | This short paper presents a work on the design of low noise microwave
amplifiers using particle swarm optimization (PSO) technique. Particle Swarm
Optimization is used as a method that is applied to a single stage amplifier
circuit to meet two criteria: desired gain and desired low noise. The aim is to
get the best opt... | computer science |
13,416 | Automatic ECG Beat Arrhythmia Detection | cs.NE | Background: In recent years automated data analysis techniques have drawn
great attention and are used in almost every field of research including
biomedical. Artificial Neural Networks (ANNs) are one of the Computer- Aided-
Diagnosis tools which are used extensively by advances in computer hardware
technology. The app... | computer science |
13,417 | Comparison Study for Clonal Selection Algorithm and Genetic Algorithm | cs.NE | Two metaheuristic algorithms namely Artificial Immune Systems (AIS) and
Genetic Algorithms are classified as computational systems inspired by
theoretical immunology and genetics mechanisms. In this work we examine the
comparative performances of two algorithms. A special selection algorithm,
Clonal Selection Algorithm... | computer science |
13,418 | The Future of Neural Networks | cs.NE | The paper describes some recent developments in neural networks and discusses
the applicability of neural networks in the development of a machine that
mimics the human brain. The paper mentions a new architecture, the pulsed
neural network that is being considered as the next generation of neural
networks. The paper a... | computer science |
13,419 | A Neuro-Fuzzy Technique for Implementing the Half-Adder Circuit Using
the CANFIS Model | cs.NE | A Neural Network, in general, is not considered to be a good solver of
mathematical and binary arithmetic problems. However, networks have been
developed for such problems as the XOR circuit. This paper presents a technique
for the implementation of the Half-adder circuit using the CoActive Neuro-Fuzzy
Inference System... | computer science |
13,420 | A New Continuous-Time Equality-Constrained Optimization Method to Avoid
Singularity | cs.NE | In equality-constrained optimization, a standard regularity assumption is
often associated with feasible point methods, namely the gradients of
constraints are linearly independent. In practice, the regularity assumption
may be violated. To avoid such a singularity, we propose a new projection
matrix, based on which a ... | computer science |
13,421 | Developing Improved Greedy Crossover to Solve Symmetric Traveling
Salesman Problem | cs.NE | The Traveling Salesman Problem (TSP) is one of the most famous optimization
problems. Greedy crossover designed by Greffenstette et al, can be used while
Symmetric TSP (STSP) is resolved by Genetic Algorithm (GA). Researchers have
proposed several versions of greedy crossover. Here we propose improved version
of it. We... | computer science |
13,422 | Generating High-Order Threshold Functions with Multiple Thresholds | cs.NE | In this paper, we consider situations in which a given logical function is
realized by a multithreshold threshold function. In such situations, constant
functions can be easily obtained from multithreshold threshold functions, and
therefore, we can show that it becomes possible to optimize a class of
high-order neural ... | computer science |
13,423 | Adaptive Intelligent Cooperative Spectrum Sensing In Cognitive Radio | cs.NE | Radio Spectrum is most precious and scarce resource and must be utilized
efficiently and effectively. Cognitive radio is the promising solutions for the
optimum utilization of the scared natural resource. The spectrum owned by the
primary user should be shared among the secondary user, but primary user should
not be in... | computer science |
13,424 | Hybridization of Evolutionary Algorithms | cs.NE | Evolutionary algorithms are good general problem solver but suffer from a
lack of domain specific knowledge. However, the problem specific knowledge can
be added to evolutionary algorithms by hybridizing. Interestingly, all the
elements of the evolutionary algorithms can be hybridized. In this chapter, the
hybridizatio... | computer science |
13,425 | Graph 3-coloring with a hybrid self-adaptive evolutionary algorithm | cs.NE | This paper proposes a hybrid self-adaptive evolutionary algorithm for graph
coloring that is hybridized with the following novel elements: heuristic
genotype-phenotype mapping, a swap local search heuristic, and a neutral
survivor selection operator. This algorithm was compared with the evolutionary
algorithm with the ... | computer science |
13,426 | Recurrent Neural Network Method in Arabic Words Recognition System | cs.NE | The recognition of unconstrained handwriting continues to be a difficult task
for computers despite active research for several decades. This is because
handwritten text offers great challenges such as character and word
segmentation, character recognition, variation between handwriting styles,
different character size... | computer science |
13,427 | A Neuromorphic VLSI Design for Spike Timing and Rate Based Synaptic
Plasticity | cs.NE | Triplet-based Spike Timing Dependent Plasticity (TSTDP) is a powerful
synaptic plasticity rule that acts beyond conventional pair-based STDP (PSTDP).
Here, the TSTDP is capable of reproducing the outcomes from a variety of
biological experiments, while the PSTDP rule fails to reproduce them.
Additionally, it has been s... | computer science |
13,428 | A Cumulative Multi-Niching Genetic Algorithm for Multimodal Function
Optimization | cs.NE | This paper presents a cumulative multi-niching genetic algorithm (CMN GA),
designed to expedite optimization problems that have computationally-expensive
multimodal objective functions. By never discarding individuals from the
population, the CMN GA makes use of the information from every objective
function evaluation ... | computer science |
13,429 | Evolutionary Design of Digital Circuits Using Genetic Programming | cs.NE | For simple digital circuits, conventional method of designing circuits can
easily be applied. But for complex digital circuits, the conventional method of
designing circuits is not fruitfully applicable because it is time-consuming.
On the contrary, Genetic Programming is used mostly for automatic program
generation. T... | computer science |
13,430 | A New Distributed Evolutionary Computation Technique for Multi-Objective
Optimization | cs.NE | Now-a-days, it is important to find out solutions of Multi-Objective
Optimization Problems (MOPs). Evolutionary Strategy helps to solve such real
world problems efficiently and quickly. But sequential Evolutionary Algorithms
(EAs) require an enormous computation power to solve such problems and it takes
much time to so... | computer science |
13,431 | Sustainable Cooperative Coevolution with a Multi-Armed Bandit | cs.NE | This paper proposes a self-adaptation mechanism to manage the resources
allocated to the different species comprising a cooperative coevolutionary
algorithm. The proposed approach relies on a dynamic extension to the
well-known multi-armed bandit framework. At each iteration, the dynamic
multi-armed bandit makes a deci... | computer science |
13,432 | Evolution of Swarm Robotics Systems with Novelty Search | cs.NE | Novelty search is a recent artificial evolution technique that challenges
traditional evolutionary approaches. In novelty search, solutions are rewarded
based on their novelty, rather than their quality with respect to a predefined
objective. The lack of a predefined objective precludes premature convergence
caused by ... | computer science |
13,433 | Generic Behaviour Similarity Measures for Evolutionary Swarm Robotics | cs.NE | Novelty search has shown to be a promising approach for the evolution of
controllers for swarm robotics. In existing studies, however, the experimenter
had to craft a domain dependent behaviour similarity measure to use novelty
search in swarm robotics applications. The reliance on hand-crafted similarity
measures plac... | computer science |
13,434 | Modified Soft Brood Crossover in Genetic Programming | cs.NE | Premature convergence is one of the important issues while using Genetic
Programming for data modeling. It can be avoided by improving population
diversity. Intelligent genetic operators can help to improve the population
diversity. Crossover is an important operator in Genetic Programming. So, we
have analyzed number ... | computer science |
13,435 | A Novel Metaheuristics To Solve Mixed Shop Scheduling Problems | cs.NE | This paper represents the metaheuristics proposed for solving a class of Shop
Scheduling problem. The Bacterial Foraging Optimization algorithm is featured
with Ant Colony Optimization algorithm and proposed as a natural inspired
computing approach to solve the Mixed Shop Scheduling problem. The Mixed Shop
is the combi... | computer science |
13,436 | Improving Generalization Ability of Genetic Programming: Comparative
Study | cs.NE | In the field of empirical modeling using Genetic Programming (GP), it is
important to evolve solution with good generalization ability. Generalization
ability of GP solutions get affected by two important issues: bloat and
over-fitting. Bloat is uncontrolled growth of code without any gain in fitness
and important issu... | computer science |
13,437 | Solving Linear Equations Using a Jacobi Based Time-Variant Adaptive
Hybrid Evolutionary Algorithm | cs.NE | Large set of linear equations, especially for sparse and structured
coefficient (matrix) equations, solutions using classical methods become
arduous. And evolutionary algorithms have mostly been used to solve various
optimization and learning problems. Recently, hybridization of classical
methods (Jacobi method and Gau... | computer science |
13,438 | An accelerated CLPSO algorithm | cs.NE | The particle swarm approach provides a low complexity solution to the
optimization problem among various existing heuristic algorithms. Recent
advances in the algorithm resulted in improved performance at the cost of
increased computational complexity, which is undesirable. Literature shows that
the particle swarm opti... | computer science |
13,439 | Multiobjective optimization in Gene Expression Programming for Dew Point | cs.NE | The processes occurring in climatic change evolution and their variations
play a major role in environmental engineering. Different techniques are used
to model the relationship between temperatures, dew point and relative
humidity. Gene expression programming is capable of modelling complex realities
with great accura... | computer science |
13,440 | Dew Point modelling using GEP based multi objective optimization | cs.NE | Different techniques are used to model the relationship between temperatures,
dew point and relative humidity. Gene expression programming is capable of
modelling complex realities with great accuracy, allowing at the same time, the
extraction of knowledge from the evolved models compared to other learning
algorithms. ... | computer science |
13,441 | Harmony search algorithm for the container storage problem | cs.NE | Recently a new metaheuristic called harmony search was developed. It mimics
the behaviors of musicians improvising to find the better state harmony. In
this paper, this algorithm is described and applied to solve the container
storage problem in the harbor. The objective of this problem is to determine a
valid containe... | computer science |
13,442 | Evolutionary Approach for the Containers Bin-Packing Problem | cs.NE | This paper deals with the resolution of combinatorial optimization problems,
particularly those concerning the maritime transport scheduling. We are
interested in the management platforms in a river port and more specifically in
container organisation operations with a view to minimizing the number of
container rehandl... | computer science |
13,443 | Urban ozone concentration forecasting with artificial neural network in
Corsica | cs.NE | Atmospheric pollutants concentration forecasting is an important issue in air
quality monitoring. Qualitair Corse, the organization responsible for
monitoring air quality in Corsica (France) region, needs to develop a
short-term prediction model to lead its mission of information towards the
public. Various determinist... | computer science |
13,444 | Using the quaternion's representation of individuals in swarm
intelligence and evolutionary computation | cs.NE | This paper introduces a novel idea for representation of individuals using
quaternions in swarm intelligence and evolutionary algorithms. Quaternions are
a number system, which extends complex numbers. They are successfully applied
to problems of theoretical physics and to those areas needing fast rotation
calculations... | computer science |
13,445 | Second Order Swarm Intelligence | cs.NE | An artificial Ant Colony System (ACS) algorithm to solve general-purpose
combinatorial Optimization Problems (COP) that extends previous AC models [21]
by the inclusion of a negative pheromone, is here described. Several Travelling
Salesman Problem (TSP) were used as benchmark. We show that by using two
different sets ... | computer science |
13,446 | English Character Recognition using Artificial Neural Network | cs.NE | This work focuses on development of a Offline Hand Written English Character
Recognition algorithm based on Artificial Neural Network (ANN). The ANN
implemented in this work has single output neuron which shows whether the
tested character belongs to a particular cluster or not. The implementation is
carried out comple... | computer science |
13,447 | Solution to Quadratic Equation Using Genetic Algorithm | cs.NE | Solving Quadratic equation is one of the intrinsic interests as it is the
simplest nonlinear equations. A novel approach for solving Quadratic Equation
based on Genetic Algorithms (GAs) is presented. Genetic Algorithms (GAs) are a
technique to solve problems which need optimization. Generation of trial
solutions have b... | computer science |
13,448 | Modeling The Stable Operating Envelope For Partially Stable Combustion
Engines Using Class Imbalance Learning | cs.NE | Advanced combustion technologies such as homogeneous charge compression
ignition (HCCI) engines have a narrow stable operating region defined by
complex control strategies such as exhaust gas recirculation (EGR) and variable
valve timing among others. For such systems, it is important to identify the
operating envelope... | computer science |
13,449 | Optimization of supply diversity for the self-assembly of simple objects
in two and three dimensions | cs.NE | The field of algorithmic self-assembly is concerned with the design and
analysis of self-assembly systems from a computational perspective, that is,
from the perspective of mathematical problems whose study may give insight into
the natural processes through which elementary objects self-assemble into more
complex ones... | computer science |
13,450 | Beyond Feedforward Models Trained by Backpropagation: a Practical
Training Tool for a More Efficient Universal Approximator | cs.NE | Cellular Simultaneous Recurrent Neural Network (SRN) has been shown to be a
function approximator more powerful than the MLP. This means that the
complexity of MLP would be prohibitively large for some problems while SRN
could realize the desired mapping with acceptable computational constraints.
The speed of training ... | computer science |
13,451 | Fault-Trajectory Approach for Fault Diagnosis on Analog Circuits | cs.NE | This issue discusses the fault-trajectory approach suitability for fault
diagnosis on analog networks. Recent works have shown promising results
concerning a method based on this concept for ATPG for diagnosing faults on
analog networks. Such method relies on evolutionary techniques, where a generic
algorithm (GA) is c... | computer science |
13,452 | The Fundamental Problem with the Building Block Hypothesis | cs.NE | Skepticism of the building block hypothesis (BBH) has previously been
expressed on account of the weak theoretical foundations of this hypothesis and
the anomalies in the empirical record of the simple genetic algorithm. In this
paper we hone in on a more fundamental cause for skepticism--the extraordinary
strength of ... | computer science |
13,453 | Two Remarkable Computational Competencies of the Simple Genetic
Algorithm | cs.NE | Since the inception of genetic algorithmics the identification of
computational efficiencies of the simple genetic algorithm (SGA) has been an
important goal. In this paper we distinguish between a computational competency
of the SGA--an efficient, but narrow computational ability--and a computational
proficiency of th... | computer science |
13,454 | A Study of NK Landscapes' Basins and Local Optima Networks | cs.NE | We propose a network characterization of combinatorial fitness landscapes by
adapting the notion of inherent networks proposed for energy surfaces (Doye,
2002). We use the well-known family of $NK$ landscapes as an example. In our
case the inherent network is the graph where the vertices are all the local
maxima and ed... | computer science |
13,455 | The Connectivity of NK Landscapes' Basins: A Network Analysis | cs.NE | We propose a network characterization of combinatorial fitness landscapes by
adapting the notion of inherent networks proposed for energy surfaces. We use
the well-known family of NK landscapes as an example. In our case the inherent
network is the graph where the vertices represent the local maxima in the
landscape, a... | computer science |
13,456 | Comparing Single and Multiobjective Evolutionary Approaches to the
Inventory and Transportation Problem | cs.NE | EVITA, standing for Evolutionary Inventory and Transportation Algorithm, is a
two-level methodology designed to address the Inventory and Transportation
Problem (ITP) in retail chains. The top level uses an evolutionary algorithm to
obtain delivery patterns for each shop on a weekly basis so as to minimise the
inventor... | computer science |
13,457 | Frequency based Classification of Activities using Accelerometer Data | cs.NE | This work presents, the classification of user activities such as Rest, Walk
and Run, on the basis of frequency component present in the acceleration data
in a wireless sensor network environment. As the frequencies of the above
mentioned activities differ slightly for different person, so it gives a more
accurate resu... | computer science |
13,458 | High Accuracy Human Activity Monitoring using Neural network | cs.NE | This paper presents the designing of a neural network for the classification
of Human activity. A Triaxial accelerometer sensor, housed in a chest worn
sensor unit, has been used for capturing the acceleration of the movements
associated. All the three axis acceleration data were collected at a base
station PC via a CC... | computer science |
13,459 | Symmetry Breaking in Neuroevolution: A Technical Report | cs.NE | Artificial Neural Networks (ANN) comprise important symmetry properties,
which can influence the performance of Monte Carlo methods in Neuroevolution.
The problem of the symmetries is also known as the competing conventions
problem or simply as the permutation problem. In the literature, symmetries are
mainly addressed... | computer science |
13,460 | Time series modeling with pruned multi-layer perceptron and 2-stage
damped least-squares method | cs.NE | A Multi-Layer Perceptron (MLP) defines a family of artificial neural networks
often used in TS modeling and forecasting. Because of its "black box" aspect,
many researchers refuse to use it. Moreover, the optimization (often based on
the exhaustive approach where "all" configurations are tested) and learning
phases of ... | computer science |
13,461 | A radial basis function neural network based approach for the electrical
characteristics estimation of a photovoltaic module | cs.NE | The design process of photovoltaic (PV) modules can be greatly enhanced by
using advanced and accurate models in order to predict accurately their
electrical output behavior. The main aim of this paper is to investigate the
application of an advanced neural network based model of a module to improve
the accuracy of the... | computer science |
13,462 | Average Drift Analysis and Population Scalability | cs.NE | This paper aims to study how the population size affects the computation time
of evolutionary algorithms in a rigorous way. The computation time of an
evolutionary algorithm can be measured by either the expected number of
generations (hitting time) or the expected number of fitness evaluations
(running time) to find a... | computer science |
13,463 | Innovative Second-Generation Wavelets Construction With Recurrent Neural
Networks for Solar Radiation Forecasting | cs.NE | Solar radiation prediction is an important challenge for the electrical
engineer because it is used to estimate the power developed by commercial
photovoltaic modules. This paper deals with the problem of solar radiation
prediction based on observed meteorological data. A 2-day forecast is obtained
by using novel wavel... | computer science |
13,464 | A study of retrieval algorithms of sparse messages in networks of neural
cliques | cs.NE | Associative memories are data structures addressed using part of the content
rather than an index. They offer good fault reliability and biological
plausibility. Among different families of associative memories, sparse ones are
known to offer the best efficiency (ratio of the amount of bits stored to that
of bits used ... | computer science |
13,465 | Genetic Algorithm for Solving Simple Mathematical Equality Problem | cs.NE | This paper explains genetic algorithm for novice in this field. Basic
philosophy of genetic algorithm and its flowchart are described. Step by step
numerical computation of genetic algorithm for solving simple mathematical
equality problem will be briefly explained | computer science |
13,466 | A hybrid evolutionary algorithm with importance sampling for
multi-dimensional optimization | cs.NE | A hybrid evolutionary algorithm with importance sampling method is proposed
for multi-dimensional optimization problems in this paper. In order to make use
of the information provided in the search process, a set of visited solutions
is selected to give scores for intervals in each dimension, and they are
updated as al... | computer science |
13,467 | A comparative analysis of methods for estimating axon diameter using DWI | cs.NE | The importance of studying the brain microstructure is described and the
existing and state of the art non-invasive methods for the investigation of the
brain microstructure using Diffusion Weighted Magnetic Resonance Imaging (DWI)
is studied. In the next step, Cramer-Rao Lower Bound (CRLB) analysis is
described and ut... | computer science |
13,468 | A Computational Model of Spatial Memory Anticipation during Visual
Search | cs.NE | Some visual search tasks require to memorize the location of stimuli that
have been previously scanned. Considerations about the eye movements raise the
question of how we are able to maintain a coherent memory, despite the frequent
drastically changes in the perception. In this article, we present a
computational mode... | computer science |
13,469 | A Multi-Agent Simulation of Retail Management Practices | cs.NE | We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of
problems in a retail context. Specifically, we are working to understand the
relationship between human resource management practices and retail
productivity. Despite the fact we are working within a relatively novel and
complex domain, it is c... | computer science |
13,470 | Understanding Retail Productivity by Simulating Management Practise | cs.NE | Intelligent agents offer a new and exciting way of understanding the world of
work. In this paper we apply agent-based modeling and simulation to investigate
a set of problems in a retail context. Specifically, we are working to
understand the relationship between human resource management practices and
retail producti... | computer science |
13,471 | Problem Solving and Complex Systems | cs.NE | The observation and modeling of natural Complex Systems (CSs) like the human
nervous system, the evolution or the weather, allows the definition of special
abilities and models reusable to solve other problems. For instance, Genetic
Algorithms or Ant Colony Optimizations are inspired from natural CSs to solve
optimizat... | computer science |
13,472 | Equivalence of Probabilistic Tournament and Polynomial Ranking Selection | cs.NE | Crucial to an Evolutionary Algorithm's performance is its selection scheme.
We mathematically investigate the relation between polynomial rank and
probabilistic tournament methods which are (respectively) generalisations of
the popular linear ranking and tournament selection schemes. We show that every
probabilistic to... | computer science |
13,473 | Neutral Fitness Landscape in the Cellular Automata Majority Problem | cs.NE | We study in detail the fitness landscape of a difficult cellular automata
computational task: the majority problem. Our results show why this problem
landscape is so hard to search, and we quantify the large degree of neutrality
found in various ways. We show that a particular subspace of the solution
space, called the... | computer science |
13,474 | Evolving Dynamic Change and Exchange of Genotype Encoding in Genetic
Algorithms for Difficult Optimization Problems | cs.NE | The application of genetic algorithms (GAs) to many optimization problems in
organizations often results in good performance and high quality solutions. For
successful and efficient use of GAs, it is not enough to simply apply simple
GAs (SGAs). In addition, it is necessary to find a proper representation for
the probl... | computer science |
13,475 | From Cells to Islands: An unified Model of Cellular Parallel Genetic
Algorithms | cs.NE | This paper presents the Anisotropic selection scheme for cellular Genetic
Algorithms (cGA). This new scheme allows to enhance diversity and to control
the selective pressure which are two important issues in Genetic Algorithms,
especially when trying to solve difficult optimization problems. Varying the
anisotropic deg... | computer science |
13,476 | Elagage d'un perceptron multicouches : utilisation de l'analyse de la
variance de la sensibilité des paramètres | cs.NE | The stucture determination of a neural network for the modelisation of a
system remain the core of the problem. Within this framework, we propose a
pruning algorithm of the network based on the use of the analysis of the
sensitivity of the variance of all the parameters of the network. This
algorithm will be tested on ... | computer science |
13,477 | Sélection de la structure d'un perceptron multicouches pour la
réduction dun modèle de simulation d'une scierie | cs.NE | Simulation is often used to evaluate the relevance of a Directing Program of
Production (PDP) or to evaluate its impact on detailed sc\'enarii of
scheduling. Within this framework, we propose to reduce the complexity of a
model of simulation by exploiting a multilayer perceptron. A main phase of the
modeling of one sys... | computer science |
13,478 | Effect of Degree Distribution on Evolutionary Search | cs.NE | This paper introduces a method to generate hierarchically modular networks
with prescribed node degree list and proposes a metric to measure network
modularity based on the notion of edge distance. The generated networks are
used as test problems to explore the effect of modularity and degree
distribution on evolutiona... | computer science |
13,479 | Single Neuron Memories and the Network's Proximity Matrix | cs.NE | This paper extends the treatment of single-neuron memories obtained by the
B-matrix approach. The spreading of the activity within the network is
determined by the network's proximity matrix which represents the separations
amongst the neurons through the neural pathways. | computer science |
13,480 | How deals with discrete data for the reduction of simulation models
using neural network | cs.NE | Simulation is useful for the evaluation of a Master Production/distribution
Schedule (MPS). Also, the goal of this paper is the study of the design of a
simulation model by reducing its complexity. According to theory of
constraints, we want to build reduced models composed exclusively by
bottlenecks and a neural netwo... | computer science |
13,481 | A genetic algorithm for structure-activity relationships: software
implementation | cs.NE | The design and the implementation of a genetic algorithm are described. The
applicability domain is on structure-activity relationships expressed as
multiple linear regressions and predictor variables are from families of
structure-based molecular descriptors. An experiment to compare different
selection and survival s... | computer science |
13,482 | XDANNG: XML based Distributed Artificial Neural Network with Globus
Toolkit | cs.NE | Artificial Neural Network is one of the most common AI application fields.
This field has direct and indirect usages most sciences. The main goal of ANN
is to imitate biological neural networks for solving scientific problems. But
the level of parallelism is the main problem of ANN systems in comparison with
biological... | computer science |
13,483 | Adaptation and Self-Organization in Evolutionary Algorithms | cs.NE | Abbreviated Abstract: The objective of Evolutionary Computation is to solve
practical problems (e.g. optimization, data mining) by simulating the
mechanisms of natural evolution. This thesis addresses several topics related
to adaptation and self-organization in evolving systems with the overall aims
of improving the p... | computer science |
13,484 | A process planning system with feature based neural network search
strategy for aluminum extrusion die manufacturing | cs.NE | Aluminum extrusion die manufacturing is a critical task for productive
improvement and increasing potential of competition in aluminum extrusion
industry. It causes to meet the efficiency not only consistent quality but also
time and production cost reduction. Die manufacturing consists first of die
design and process ... | computer science |
13,485 | Evolution of Digital Logic Functionality via a Genetic Algorithm | cs.NE | Digital logic forms the functional basics of most modern electronic equipment
and as such the creation of novel digital logic circuits is an active area of
computer engineering research. This study demonstrates that genetic algorithms
can be used to evolve functionally useful sets of logic gate interconnections
to crea... | computer science |
13,486 | Digital Business Ecosystems: Natural Science Paradigms | cs.NE | A primary motivation for research in Digital Ecosystems is the desire to
exploit the self-organising properties of natural ecosystems. Ecosystems arc
thought to be robust, scalable architectures that can automatically solve
complex, dynamic problems. However, the biological processes that contribute to
these properties... | computer science |
13,487 | Predictability of PV power grid performance on insular sites without
weather stations: use of artificial neural networks | cs.NE | The official meteorological network is poor on the island of Corsica: only
three sites being about 50 km apart are equipped with pyranometers which enable
measurements by hourly and daily step. These sites are Ajaccio (41\degree 55'N
and 8\degree 48'E, seaside), Bastia (42\degree 33'N, 9\degree 29'E, seaside)
and Corte... | computer science |
13,488 | Particle Swarm Optimization Based Reactive Power Optimization | cs.NE | Reactive power plays an important role in supporting the real power transfer
by maintaining voltage stability and system reliability. It is a critical
element for a transmission operator to ensure the reliability of an electric
system while minimizing the cost associated with it. The traditional objectives
of reactive ... | computer science |
13,489 | Application of Artificial Neural Networks in Aircraft Maintenance,
Repair and Overhaul Solutions | cs.NE | This paper reviews application of Artificial Neural Networks in Aircraft
Maintenance, Repair and Overhaul (MRO). MRO solutions are designed to
facilitate the authoring and delivery of maintenance and repair information to
the line maintenance technicians who need to improve aircraft repair turn
around time, optimize th... | computer science |
13,490 | Genetic Algorithm for Mulicriteria Optimization of a Multi-Pickup and
Delivery Problem with Time Windows | cs.NE | In This paper we present a genetic algorithm for mulicriteria optimization of
a multipickup and delivery problem with time windows (m-PDPTW). The m-PDPTW is
an optimization vehicles routing problem which must meet requests for transport
between suppliers and customers satisfying precedence, capacity and time
constraint... | computer science |
13,491 | Un Algorithme génétique pour le problème de ramassage et de
livraison avec fenêtres de temps à plusieurs véhicules | cs.NE | The PDPTW is an optimization vehicles routing problem which must meet
requests for transport between suppliers and customers satisfying precedence,
capacity and time constraints. We present, in this paper, a genetic algorithm
for optimization of a multi pickup and delivery problem with time windows
(m-PDPTW). We purpos... | computer science |
13,492 | Approche Multicritère pour le Problème de Ramassage et de Livraison
avec Fenêtres de Temps à Plusieurs Véhicules | cs.NE | Nowadays, the transport goods problem occupies an important place in the
economic life of modern societies. The pickup and delivery problem with time
windows (PDPTW) is one of the problems which a large part of the research was
interested. In this paper, we present a a brief literature review of the VRP
and the PDPTW, ... | computer science |
13,493 | Optimizing Monotone Functions Can Be Difficult | cs.NE | Extending previous analyses on function classes like linear functions, we
analyze how the simple (1+1) evolutionary algorithm optimizes pseudo-Boolean
functions that are strictly monotone. Contrary to what one would expect, not
all of these functions are easy to optimize. The choice of the constant $c$ in
the mutation ... | computer science |
13,494 | Sparse and silent coding in neural circuits | cs.NE | Sparse coding algorithms are about finding a linear basis in which signals
can be represented by a small number of active (non-zero) coefficients. Such
coding has many applications in science and engineering and is believed to play
an important role in neural information processing. However, due to the
computational co... | computer science |
13,495 | An Adaptive Quantum-inspired Differential Evolution Algorithm for 0-1
Knapsack Problem | cs.NE | Differential evolution (DE) is a population based evolutionary algorithm
widely used for solving multidimensional global optimization problems over
continuous spaces. However, the design of its operators makes it unsuitable for
many real-life constrained combinatorial optimization problems which operate on
binary space... | computer science |
13,496 | Multiplicative Drift Analysis | cs.NE | In this work, we introduce multiplicative drift analysis as a suitable way to
analyze the runtime of randomized search heuristics such as evolutionary
algorithms.
We give a multiplicative version of the classical drift theorem. This allows
easier analyses in those settings where the optimization progress is roughly
p... | computer science |
13,497 | Spectrum Management for Cognitive Radio based on Genetics Algorithm | cs.NE | Spectrum scarceness is one of the major challenges that the present world is
facing. The efficient use of existing licensed spectrum is becoming most
critical as growing demand of the radio spectrum. Different researches show
that the use of licensed are not utilized inefficiently. It has been also shown
that primary u... | computer science |
13,498 | New Model for Multi-Objective Evolutionary Algorithms | cs.NE | Multi-Objective Evolutionary Algorithms (MOEAs) have been proved efficient to
deal with Multi-objective Optimization Problems (MOPs). Until now tens of MOEAs
have been proposed. The unified mode would provide a more systematic approach
to build new MOEAs. Here a new model is proposed which includes two sub-models
based... | computer science |
13,499 | Evolving a New Feature for a Working Program | cs.NE | A genetic programming system is created. A first fitness function f1 is used
to evolve a program that implements a first feature. Then the fitness function
is switched to a second function f2, which is used to evolve a program that
implements a second feature while still maintaining the first feature. The
median number... | computer science |
13,500 | Evolving Pacing Strategies for Team Pursuit Track Cycling | cs.NE | Team pursuit track cycling is a bicycle racing sport held on velodromes and
is part of the Summer Olympics. It involves the use of strategies to minimize
the overall time that a team of cyclists needs to complete a race. We present
an optimisation framework for team pursuit track cycling and show how to evolve
strategi... | computer science |
13,501 | Idealized Dynamic Population Sizing for Uniformly Scaled Problems | cs.NE | This paper explores an idealized dynamic population sizing strategy for
solving additive decomposable problems of uniform scale. The method is designed
on top of the foundations of existing population sizing theory for this class
of problems, and is carefully compared with an optimal fixed population sized
genetic algo... | computer science |
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