Add PlotNeuralNet implementation for 13 DL parking prediction archite…

[akramelsaied]

…ctures

Added comprehensive implementation to generate publication-quality 3D neural network architecture diagrams for all 13 deep learning models used in parking occupancy prediction research.

New files:

• pyexamples/parking_dl_architectures.py: Main implementation with all 13 architectures (DNN, LSTM, GRU, BiLSTM, CNN, CNN-LSTM, CNN-GRU, ConvLSTM, TCN, Transformer, Attention-LSTM, Encoder-Decoder, WaveNet)
• pyexamples/build_all_architectures.sh: Automated build script for all models
• PARKING_ARCHITECTURES_README.md: Comprehensive usage guide
• QUICKSTART_GUIDE.md: Quick start guide for fast setup
• MATPLOTLIB_vs_PLOTNEURALNET.md: Detailed comparison and migration guide

Features:

• Professional 3D isometric visualizations (vs flat matplotlib boxes)
• Vector PDF output (publication-quality, infinitely scalable)
• Proper representation of LSTM/GRU gates, attention mechanisms, skip connections
• Automated generation and compilation of all 13 architectures
• Extensive documentation with examples and customization guides

Usage: python parking_dl_architectures.py <model_name>
Build all: ./build_all_architectures.sh