Project Overview & Abstract
A standardized scientific research workstation for empirically benchmarking 10 metaheuristic optimization algorithms (Grey Wolf Optimizer, Whale Optimization Algorithm, Ant Lion Optimizer, Moth-Flame Optimization, Grasshopper Optimization Algorithm, Multi-Verse Optimizer, Sine Cosine Algorithm, Arithmetic Optimization Algorithm, Mountain Gazelle Optimizer, Geometric Mean Optimizer) on Deep Convolutional Neural Network (CNN) compression across Top-1 Accuracy, Synchronized Hardware Latency (ms), Model Footprint (MB), and Energy Consumption (Joules).
System Architecture & 7-Stage Pipeline
Deterministic 7-stage evaluation pipeline: Baseline FP32 Calibration, Post-Training Quantization (INT8/FP16), Structured L1 Channel Pruning, Continuous Metaheuristic Search [0.0, 1.0]^D, CUDA Synchronized Hardware Telemetry, Statistical Multi-Run Aggregation, and Pareto Frontier Dominance with Weighted Sum Model (WSM) scoring.
Export Formats Supported
Export complete research reports and benchmark data in Plain Text (TXT), Printable PDF, Microsoft Word (DOCS .doc), GitHub Markdown (.md), CSV, and JSON.