Electrical Engineering Department College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China 在期刊界中查找 在百度中查找 在本站中查找
Electrical Engineering Department College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China 在期刊界中查找 在百度中查找 在本站中查找
Electrical Engineering Department College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China 在期刊界中查找 在百度中查找 在本站中查找
Electrical Engineering Department College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China 在期刊界中查找 在百度中查找 在本站中查找
The traditional genetic algorithm easily converges to slow speed, leads to a poor climbing ability and shows weak static stability and robustness when seeking a solution. On the basis of analyzing multi-constrained and multi-objective optimization model o
