Hyperparameter Optimization Using a Genetic Algorithm Considering Verification Time in a Convolutional Neural Network

• Published in: Journal of electrical engineering & technology Vol. 15; no. 2; pp. 721 - 726
• Main Authors: Han, Ji-Hoon, Choi, Dong-Jin, Park, Sang-Uk, Hong, Sun-Ki
• Format: Journal Article
• Language: English
• Published: Singapore Springer Singapore 01.03.2020
• Subjects: Electrical Engineering; Electrical Machines and Networks; Electronics and Microelectronics; Engineering; Instrumentation; Original Article; Power Electronics; MNIST; Hyper-parameter optimization; Genetic algorithm; Motor fault diagnosis; Convolutional neural network; Deep learning algorithm

Hyperparameter optimization is a very difficult problem in developing deep learning algorithms. In this paper, a genetic algorithm was applied to solve this problem. The accuracy and the verification time were considered by conducting a fitness evaluation. The algorithm was evaluated by using a simp...