推導(dǎo)了隱層節(jié)點(diǎn)和輸出節(jié)點(diǎn)的學(xué)習(xí)及修正公式，選擇了初始權(quán)值、學(xué)習(xí)速率和期望誤差等相關(guān)學(xué)習(xí)參數(shù)，結(jié)合結(jié)晶工段實(shí)際進(jìn)行了網(wǎng)絡(luò)訓(xùn)練。為加快網(wǎng)絡(luò)的收斂，在保證系統(tǒng)穩(wěn)定的基礎(chǔ)上，提出了S 函數(shù)輸出限幅和變步長(zhǎng)法兩種改進(jìn)方案。采用改進(jìn)的BP 算法對(duì)此BP 網(wǎng)絡(luò)進(jìn)行了訓(xùn)練，得到的ANN 網(wǎng)絡(luò)訓(xùn)練輸出值與實(shí)際輸出值非常逼近。
關(guān)鍵詞：BP 算法；網(wǎng)絡(luò)訓(xùn)練；收斂；修正

Algorithmic Choice and Betterment in the BP Network ofCane Sugar Crystallization YANG Jie1,2, YAN Qingdong1 (1. School of Communication Machinery and Civil Engineering, Southwest Forestry University, Kunming, Yunnan 650224, China; 2. School of Mechanical and Vehicle Engineering, Beijing Institute of Technology, Beijing 100081, China ) Abstract: The learning and amendatory formulae of the hidden layer nodes and deferent nodes were deduced. Initial weight value，learning rate and expectation error etc. correlative learning parameters were selected, then the BP network was trained integrating practical instance. In order to quicken convergence, S function output violent change and method of changing step length which two improved project were brought forward in the basis of system stabilization. And the BP network was trained by using improved algorithm, the result showed that ANN
model output extremely approximated to practical output.
Key words: BP algorithm; Network training; Convergence；Amendment