Genetic Algorithm for Neural Network Architecture and Hyperparameter Optimization and Neural Network Weight Optimization with Genetic Algorithm
This project aims to use genetic algorithms to boost the learning of DNN. Building and training a family of NN with same structure and hyperparameters from scratch but starting from different random weights. After a few epochs of training, the networks that perform better are chosen and crossover their weights in order to mating and produce the …
Excel file and Python code used in the published SLR paper: RNN-LSTM: From Applications to Modeling Techniques and Beyond - Systematic Review
Weight optimization of a truss structure via evolution strategy.
Optimizing neural network weights using Evolutionary Algorithms
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