Update content and detail model documentation

README.md

@@ -55,8 +55,9 @@ Each `Results_trained.mat` file contains three core structures:
 * **Goal**: Predicts the ultimate three-phase pyrolysis yields (Char, Liquid, Gas) under high-temperature conditions.
 * **Network Topology**: `259` (Input) → `45` → `45` → `45` → `45` → `45` → `3` (Outputs).
 * **Input Features (259 Dimensions)**:
-  * **Basic Feedstock Characteristics (19 Dimensions)**
-  * **Detailed Feedstock Blending/Mixing Features (240 Dimensions)**
+  * **Basic Feedstock Characteristics (19 Dimensions)**: Proximate, ultimate, and ash components.
+  * **Pyrolysis Process Conditions (4 Dimensions)**: Target temperature (°C), Reaction time (min), Heating rate (K/min), and Reactor type.
+  * **Detailed Feedstock Blending/Mixing Features (236 Dimensions)**: Feedstock combinations and ratios.
 * **Outputs (3 Dimensions)**:
   * Pyrolysis yields (expressed in weight percentages):
     1. **Char Yield (%)** (used directly as the ultimate residue w_inf for TG scaling).
@@ -112,7 +113,7 @@ For reference, the 19 basic feedstock input characteristics representing the bio
 | **18** | P₂O₅ | Phosphorus pentoxide percentage in biomass ash | wt.% of ash |
 | **19** | SO₃ | Sulfur trioxide percentage in biomass ash | wt.% of ash |
 
-*Note: For the Ea network, column 20 is the degree of conversion (α), and columns 21–256 contain mixed feedstock attributes. For the Yield network, columns 20–259 contain mixed feedstock attributes.*
+*Note: For the Ea network, column 20 is the degree of conversion (α), and columns 21–256 contain mixed feedstock attributes. For the Yield network, columns 20–23 contain pyrolysis process conditions, and columns 24–259 contain mixed feedstock attributes.*
 
 ---
 
@@ -168,13 +169,16 @@ basicBiomassFeatures = [ ...
     1.50 ...   % SO3 (% of ash)
 ];
 
+% Define Pyrolysis Process Conditions (4 features specific to Yield network)
+% 1. Target Temperature (°C), 2. Reaction Time (min), 3. Heating Rate (K/min), 4. Reactor Type
+processConditions = [600, 30, 20, 1];
+
 % Construct blending/mixing parameters (zero-padded for single pure biomass)
-feedstockMixingEa = zeros(1, 236);
-feedstockMixingYield = zeros(1, 240);
+feedstockMixingFeatures = zeros(1, 236);
 
 %% 3. Predict Pyrolysis Yields
 % Prepare input for Yield Network: (259 features x 1 sample)
-yieldInput = [basicBiomassFeatures, feedstockMixingYield]';
+yieldInput = [basicBiomassFeatures, processConditions, feedstockMixingFeatures]';
 
 % Switch global normalization handlers for nnpredict
 global PS TS
@@ -202,7 +206,7 @@ eaInputs = zeros(numAlpha, 256);
 
 for i = 1:numAlpha
     % Ea input structure: [basicFeatures(1-19), alpha(20), feedstockMixing(21-256)]
-    eaInputs(i, :) = [basicBiomassFeatures, alphaList(i), feedstockMixingEa];
+    eaInputs(i, :) = [basicBiomassFeatures, alphaList(i), feedstockMixingFeatures];
 end
 
 % Transpose to (256 features x numAlpha samples) for network evaluation