Adaptive Wind Driven Optimization Trained Artificial Neural Networks
Machine Learning
2019-11-21 v1 Machine Learning
Abstract
This paper presents the application of a newly developed nature-inspired metaheuristic optimization method, namely the Adaptive Wind Driven Optimization (AWDO), to the training of feedforward artificial neural networks (NN) and presents a discussion into the future research of AWDO implementation in Deep Learning (DL). Application example of digit classification with MNIST dataset reveals interesting behavior of the derivative-free AWDO method compared to steepest descent method where results and future work on the implementation of AWDO in deep neural networks are discussed.
Cite
@article{arxiv.1911.08942,
title = {Adaptive Wind Driven Optimization Trained Artificial Neural Networks},
author = {Zikri Bayraktar},
journal= {arXiv preprint arXiv:1911.08942},
year = {2019}
}