基于自适应遗传算法优化BP神经网络

传统的BP算法具有简单可塑的优点,但是存在着容易陷入局部极值、收敛速度慢等无法克服的缺陷。遗传算法是一种全局搜索算法,具有很强的全局搜索能力。因此,文中设计了一种自适应遗传算法优化BP神经网络的方法,并通过对数字信号的实例仿真,证明了经过改进优化后的BP神经网络具有很好的应用前景。

Optimized BP Neural Network Based on Self-adapted Genetic Algorithm

Conventional BP algorithm has merit of plasticity, but presents insuperable bug that it easily gets into partial extremum, and has slow speed of convergence. Genetic algorithm is an wholly-searching algo-rithm, which has strong capability of wholly-search. Consequently, the paper design a BP neural network algo- rithm optimized by self-adapted genetic algorithm. It proves that optimized BP neural network has very excellent applied foreground through the simulation of digital information.