TY - GEN
T1 - An Improved Whale Optimization Algorithm and Its Application to Power Generation in Cascade Reservoir
AU - Lü, Ji Xiang
AU - Yan, Li-Jun
AU - Pan, Tien-Szu
AU - Chu, Shu-Chuan
AU - Pan, Jeng-Shyang
AU - He, Xian-Kang
AU - Chang, Kuo-Chi
PY - 2021
Y1 - 2021
N2 - Nowadays, there is a very popular artificial intelligence algorithm called whale optimization algorithm (WOA). WOA is obtained through the special bubble net foraging process of humpback whales. It has a special search mechanism, and is very helpful to solve some complex optimization problems and large scale. An improved WOA is implemented to optimize the cascade reservoir power generation. Firstly, by introducing nonlinear time-varying adaptive weights, the WOA performance in the local optimization and global exploration stages is improved; secondly, the differential mutation perturbation factor is introduced in the shrinking and surrounding stage of the whale algorithm to prevent premature convergence. In addition, the logarithmic spiral search method of whale individuals has been improved so that the ability to solve the algorithm traversal can be found. Experimental results show that it has a great improvement in accuracy and convergence compared with the original WOA in the optimal dispatch model of cascade reservoir power generation.
AB - Nowadays, there is a very popular artificial intelligence algorithm called whale optimization algorithm (WOA). WOA is obtained through the special bubble net foraging process of humpback whales. It has a special search mechanism, and is very helpful to solve some complex optimization problems and large scale. An improved WOA is implemented to optimize the cascade reservoir power generation. Firstly, by introducing nonlinear time-varying adaptive weights, the WOA performance in the local optimization and global exploration stages is improved; secondly, the differential mutation perturbation factor is introduced in the shrinking and surrounding stage of the whale algorithm to prevent premature convergence. In addition, the logarithmic spiral search method of whale individuals has been improved so that the ability to solve the algorithm traversal can be found. Experimental results show that it has a great improvement in accuracy and convergence compared with the original WOA in the optimal dispatch model of cascade reservoir power generation.
KW - Cascade reservoir power generation
KW - Differential mutation
KW - Logarithmic spiral
KW - Nonlinear time-varying adaptive weights
KW - Whale optimization algorithm
UR - http://www.scopus.com/inward/record.url?scp=85105884185&partnerID=8YFLogxK
U2 - 10.1007/978-981-33-6420-2_28
DO - 10.1007/978-981-33-6420-2_28
M3 - Conference contribution
AN - SCOPUS:85105884185
SN - 9789813364196
VL - 1
T3 - Smart Innovation, Systems and Technologies
SP - 228
EP - 237
BT - Advances in Intelligent Information Hiding and Multimedia Signal Processing
A2 - Pan, Jeng-Shyang
A2 - Li, Jianpo
A2 - Namsrai, Oyun-Erdene
A2 - Meng, Zhenyu
A2 - Savić, Miloš
PB - Springer Nature
CY - Singapore
T2 - 16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2020
Y2 - 5 November 2020 through 7 November 2020
ER -