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README.md

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+# urban_traffic_flow_predictor
+
+## Overview
+This model is a time-series transformer designed to predict urban traffic density and flow rates. It leverages historical sensor data from major metropolitan intersections to provide hourly forecasts for the upcoming 24-hour period.
+
+## Model Architecture
+- **Architecture:** Informer (ProbSparse Attention mechanism)
+- **Input:** 7 days (168 hours) of historical traffic volume, weather data, and holiday markers.
+- **Output:** 24-hour continuous traffic flow forecast.
+- **Efficiency:** Designed for long-sequence time-series forecasting with O(L log L) complexity.
+
+## Intended Use
+- **Smart City Planning:** Optimizing traffic light synchronization based on predicted surges.
+- **Navigation Services:** Providing predictive routing to avoid anticipated congestion.
+- **Public Transport:** Adjusting bus and rail frequency in response to predicted road density.
+
+## Limitations
+- **Unforeseen Events:** Cannot predict traffic changes caused by sudden accidents or emergency road closures.
+- **Geographic Specificity:** Performance may degrade if applied to rural areas with significantly different traffic patterns than the training cities.
+- **Data Quality:** Requires consistent hourly inputs; missing sensor data can significantly impact forecast accuracy.