Whale optimization algorithm based on hybrid adaptive strategy

Dou Jin; ShengBing Chen; AnQi Lu; Feng Qiu

doi:10.1117/12.2634390

4 May 2022 Whale optimization algorithm based on hybrid adaptive strategy

Dou Jin, ShengBing Chen, AnQi Lu, Feng Qiu

Proceedings Volume 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021); 121721H (2022) https://doi.org/10.1117/12.2634390
Event: International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 2021, Nanchang, China

Abstract

Whale optimization algorithm (WOA) is characterized by fewer parameters, simple structure, and stronger optimization seeking ability compared with traditional optimization algorithms, but in practical applications there are problems such as sluggish convergence speed and easily falling into local optimal solutions. This work proposes MAWOA, a whale optimization algorithm based on hybrid adaptive strategy, introducing a method to adaptively adjust the weights with the iterative situation of the population to accelerate the convergence of the algorithm; designing an adaptive adjustment threshold, and individuals select a random search method according to the value of the threshold to enhance the global search ability of the population and circumventing local values; introducing an adaptive nonlinear convergence factor to strengthen the algorithm in initial exploration breadth and later local development process. Twelve different morphological benchmark functions and a MAWOA-BP wine quality classification model were used to optimize the experiment. The results shows that MAWOA has stronger performance in terms of convergence speed and optimization-seeking accuracy, and the classification results are significantly improved compared with traditional classification models such as KNN, decision trees and BP neural networks.

Citation Download Citation

Dou Jin, ShengBing Chen, AnQi Lu, and Feng Qiu "Whale optimization algorithm based on hybrid adaptive strategy", Proc. SPIE 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 121721H (4 May 2022); https://doi.org/10.1117/12.2634390

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available