back propagation algorithm

"back propagation algorithm"的翻譯和解釋

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In this paper , we improve the objective function of back propagation algorithm based on different financial actual situation . change the objective function into the expectation and the variance of error function to make its application more wide
本文首先基于bp算法應(yīng)用于金融實(shí)務(wù)領(lǐng)域的不同，對(duì)原bp算法的單一目標(biāo)函數(shù)進(jìn)行了改進(jìn)，分別取其期望目標(biāo)和方差目標(biāo)，進(jìn)行了bp算法的推廣，使其應(yīng)用范圍更廣。
In order to override the well - known limitation of back propagation algorithm , such as local grade problem , we suggest genetic algorithm , a global optimization algorithm , to optimize the weights set . the different parts of this model were modularized and combined as a prediction system
通過對(duì)固定網(wǎng)絡(luò)結(jié)構(gòu)的權(quán)系值進(jìn)行遺傳操作，優(yōu)化網(wǎng)絡(luò)的權(quán)系值組合，快速收斂到最優(yōu)權(quán)系值組合，進(jìn)而提高網(wǎng)絡(luò)的分析預(yù)測(cè)效率和能力。
The multiplayer forward neural network and its training algorithm are thorough analyzed , error back propagation algorithm is derived from the mathematic , the problem of bp algorithm is indicated . the improved bp algorithm with many target recognition is constructed
詳細(xì)分析了多層前饋型神經(jīng)網(wǎng)絡(luò)描述及訓(xùn)練算法機(jī)理，從數(shù)學(xué)的角度推導(dǎo)了誤差逆?zhèn)鞑ニ惴? bp算法) ，同時(shí)指出了bp算法存在的問題。構(gòu)建了一種用于多目標(biāo)識(shí)別的改進(jìn)的bp算法。
On the basis of analysing multilayer forward artificial neural networks which based on back propagation algorithms and basic principles of the adaptive noise cancellation system , this paper sets up an adaptive noise cancellation controller based on artificial neural network , which is proved to be more efficient in the noise cancellation and has robust performance based on simulink of matlab at the end , this paper proposes some advices of model and algorithms
在對(duì)基于誤差反向傳播學(xué)習(xí)算法的多層前向人工神經(jīng)網(wǎng)絡(luò)進(jìn)行分析基礎(chǔ)上，結(jié)合傳統(tǒng)自適應(yīng)噪聲抵消系統(tǒng)基本原理，建立了基于人工神經(jīng)網(wǎng)絡(luò)的自適應(yīng)噪聲抵消器，經(jīng)基于matlab的simulink仿真實(shí)例證明，具有很強(qiáng)的噪聲濾除能力和魯棒性。最后并提出了網(wǎng)絡(luò)及算法進(jìn)一步改進(jìn)的方法。
Based upon the deficiencies of the back propagation algorithm in the practical application , after some mechanisms effecting the network training and the other performances are analyzed when training samples with disturbance are employed in training , in this paper , through combining the chief thoughts of the classical bp algorithm and the robust statistic technique , improving the optimal algorithm of the bp algorithm , a new algorithm with high robustness - robust adaptive bp algorithm is proposed , and also make a good effect when integrated this new algorithm with the dynamical bp network to predict the stock price
本文從基本bp算法在應(yīng)用中存在的不足出發(fā)，著重分析了訓(xùn)練樣本中所含噪聲對(duì)基本bp算法在網(wǎng)絡(luò)訓(xùn)練過程中產(chǎn)生的不良影響，并以此為依據(jù)，采用魯棒統(tǒng)計(jì)技術(shù)，同時(shí)在優(yōu)化算法上做了一些有益的改進(jìn)，提出一種新的具有較強(qiáng)抗干擾能力的bp算法? ?魯棒自適應(yīng)bp算法，并將其應(yīng)用于動(dòng)態(tài)bp網(wǎng)絡(luò)，進(jìn)行股票價(jià)格的預(yù)測(cè)，取得了較好的預(yù)測(cè)效果。
Based on polymerization reaction of the nylon - 6 rubberized cord fabric production of distributed control system in yangzhou organic chemical plant computer integrated manufacturing system ( yh - cims / dcs ) , the multiple stepwise regression method was used to build the statistic mathematical models of the molecule weight and the monomer quantum of casting slice belt . then the optimization model of polymerization reaction was presented , which was solved by using simulation annealing algorithm to obtain the best techniques parameters . the improved hybrid genetic algorithm and back propagation algorithm are combined to train neural network , brought out the neural network prediction model of casting slice belt ' s average molecule weight to guide the technologist on - line
提出了流程工業(yè)生產(chǎn)過程操作優(yōu)化策略和應(yīng)用實(shí)施方法，包括生產(chǎn)過程離線優(yōu)化策略、非線性問題求解策略、在線優(yōu)化模型及學(xué)習(xí)策略；結(jié)合揚(yáng)州有機(jī)化工廠計(jì)算機(jī)集成制造系統(tǒng)集散控制系統(tǒng)( yh - cims dcs )的實(shí)施，針對(duì)錦綸? 6浸膠南京理工大學(xué)博士學(xué)位論文摘要簾于布生產(chǎn)中己內(nèi)酚胺聚合反應(yīng)過程優(yōu)化控制這一工程實(shí)際問題，采用統(tǒng)計(jì)建模方法，建立了聚合反應(yīng)過程的優(yōu)化模型；為求解所得的優(yōu)化模型，提出了種改進(jìn)的有約束條件下的模擬退火算法，該算法能避免陷于局部最優(yōu)解，有效地提高了所求解的全局性和可靠性：提出了基于改進(jìn)的ga算法和sp算法相結(jié)合的混合學(xué)習(xí)算法，建立了基于神經(jīng)網(wǎng)絡(luò)的聚合反應(yīng)過程生產(chǎn)目標(biāo)在線預(yù)測(cè)模型，該算法和模型滿足了生產(chǎn)中的實(shí)時(shí)性和實(shí)用性要求。
5 based on studying artificial nerve network theory , establish the nerve network model of cutting parameter . use back propagation algorithm ( bp algorithm ) as system ' s nerve network learning method . system has realized cutting parameter nerve network intelligentized choosing function
5在深入研究人工神經(jīng)網(wǎng)絡(luò)理論的基礎(chǔ)上，建立了切削參數(shù)選擇的神經(jīng)網(wǎng)絡(luò)模型，采用誤差反傳算法(即算法)作為切削參數(shù)智能選擇的神經(jīng)網(wǎng)絡(luò)學(xué)習(xí)方法，實(shí)現(xiàn)了切削參數(shù)人工神經(jīng)網(wǎng)絡(luò)智能選擇功能。
Using error back propagation algorithm . the limitation of the bp net is also improved ; 2 > when prediction with little training sample set and large variable size is concemed , this paper abstracts the prime factors from the training sample set using rough set theory , then only inputs the prime factors into ann . this diminishes the size and the input nodes number of ann
對(duì)于即網(wǎng)絡(luò)本身易陷入局部極小點(diǎn)及收斂速度慢的問題，在文中也得到了改進(jìn)； 2 、對(duì)于財(cái)政轉(zhuǎn)移支付中標(biāo)準(zhǔn)收入的測(cè)算屬于多指標(biāo)小樣本的預(yù)測(cè)問題，文中首次利用粗集理論對(duì)初始的指標(biāo)體系進(jìn)行約簡(jiǎn)，提取出關(guān)鍵性的因素作為神經(jīng)網(wǎng)絡(luò)的輸入。
After researching the application of artificial neural network to fault diagnosis of transformer , the back propagation algorithm is improved observably . inducting chaos dynamics principium to create chaos neural network back propagation algorithm and using the pretreatment of training sample , the emulation program show that this method is effective
本文深入研究了人工神經(jīng)網(wǎng)絡(luò)在變壓器故障診斷中的應(yīng)用，對(duì)目前最常采用的bp算法做出了較大改進(jìn)，在原有算法中引入混沌動(dòng)力學(xué)原理構(gòu)造了混沌神經(jīng)網(wǎng)絡(luò)bp算法，并提出了訓(xùn)練樣本集的預(yù)處理方法，在仿真訓(xùn)練中取得了滿意的效果。
On basis of such theory , penman apply back propagation algorithm to estimate a stock - sanxiashuili ( 600116 ) . compare the estimated price with the real price and analyze the reasons , we point out the advantages and the disadvantages of the new method finally and get some satisfying results
在上述理論基礎(chǔ)上，筆者針對(duì)一支個(gè)股? ?三峽水利（ 600116 ）利用bp網(wǎng)絡(luò)建立了這支股票的估價(jià)模型，并將這支個(gè)股的估計(jì)價(jià)格和實(shí)際價(jià)格曲線進(jìn)行了擬合，在實(shí)踐上也取得了較滿意的結(jié)果。