电子测试
電子測試
전자측시
Electronic Test
2015年
20期
39-40,25
,共3页
BP神经网络优化%粒子群算法改进%方法
BP神經網絡優化%粒子群算法改進%方法
BP신경망락우화%입자군산법개진%방법
BP neural network optimization%Particle swarm optimization algorithm to improve%method
粒子群优化算法作为一种新型的算法由于具有原理简单、收敛速度快且易于实现的优势等成为学术界的专家学者关注的热点问题.文介绍了BP神经网络和粒子群算法两种预测方法,提出了基于改进改进粒子群算法的BP神经网络的基本算法及操作流程.
粒子群優化算法作為一種新型的算法由于具有原理簡單、收斂速度快且易于實現的優勢等成為學術界的專傢學者關註的熱點問題.文介紹瞭BP神經網絡和粒子群算法兩種預測方法,提齣瞭基于改進改進粒子群算法的BP神經網絡的基本算法及操作流程.
입자군우화산법작위일충신형적산법유우구유원리간단、수렴속도쾌차역우실현적우세등성위학술계적전가학자관주적열점문제.문개소료BP신경망락화입자군산법량충예측방법,제출료기우개진개진입자군산법적BP신경망락적기본산법급조작류정.
As a new kind of particle swarm optimization algorithm is presented with the principle of simple, fast convergence speed and the advantages of easy to implement and so on become the hot topic in the academic experts and scholars. This paper introduces the BP neural network and two kinds of prediction method of particle swarm optimization, is proposed based on improved particle swarm algorithm of the basic algorithm of BP neural network and the operation process.
