Whale Optimization Algorithm Fused with Dynamic Pinhole Imaging
Aiming at the shortcomings of whale optimization algorithm(WOA),which is easy to fall into local optimum and low convergence accuracy,an improved whale optimization algorithm(DPIWOA)combined with dynamic pinhole imaging strategy is proposed.Compared with the ordinary opposition learning strategy,the dynamic pinhole imaging strategy can generate more diverse opposition points.Using this strategy can speed up the convergence speed and improve the convergence accuracy of the algorithm and can also avoid the algorithm from falling into local problems during the iterative process.The experimental results on 23 benchmark functions show that DPIWOA has improved in terms of convergence speed and optimization accuracy,which verifies the effectiveness and practicability of the improved strategy in this paper.
whale optimization algorithmdynamic pinhole imagingreverse learningbenchmark function test
万方数据
维普
