例句與造句

1. Design of on - line learning based error back propagation algorithm in simulation servo system
   基于在線學(xué)習(xí)誤差反傳算法的仿真伺服系統(tǒng)設(shè)計(jì)
2. Chapter four details the basis of the modeling of the thesis - - error back propagation algorithm , or bp , which is the stress of the thesis
   2005年4月末,金融機(jī)構(gòu)個(gè)人貸款余額達(dá)到27043億元,比上年同期增長(zhǎng)了57 % ,呈現(xiàn)了快速發(fā)展的態(tài)勢(shì)。
3. Chapter 4 presents an error back propagation algorithm with quadratic momentum of the multilayer forward neural networks that will speed up the error convergence velocity
   本文提出一種帶二次動(dòng)量項(xiàng)的多層前向網(wǎng)絡(luò)誤差反傳算法，提高了神經(jīng)網(wǎng)絡(luò)的誤差收斂速度。
4. In the stage of training , nntcs applies labeled documents to ann for training , and the error back propagation algorithm ( bp ) is employed to adjust weights of the networks . after training , the final fixed weights are saved as knowledge of classification
   在文本訓(xùn)練的時(shí)候，利用標(biāo)記好的訓(xùn)練文檔集進(jìn)行網(wǎng)絡(luò)訓(xùn)練，誤差反饋算法對(duì)網(wǎng)絡(luò)進(jìn)行權(quán)值調(diào)整，得到固定的權(quán)值作為分類知識(shí)存儲(chǔ)。
5. 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。
6. It's difficult to find error back propagation algorithm in a sentence. 用error back propagation algorithm造句挺難的
7. 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。
8. The simulation results indicate the capability of genetic algorithm in fast and steady learning of neural networks , guaranteeing a global convergence and overcoming some shortcomings of traditional error back propagation algorithms , meanwhile prove that this neural networks adaptive control structure is effective to many control problems and it is easy for us to programme and employ the method in the practical system
   仿真結(jié)果表明遺傳算法能夠快速穩(wěn)定地學(xué)習(xí)神經(jīng)網(wǎng)絡(luò)，保證全局收斂西安理工大學(xué)碩士學(xué)位論文并且能夠克服傳統(tǒng)誤差反傳算法的一些缺點(diǎn)，也證明了這種神經(jīng)網(wǎng)絡(luò)自適應(yīng)控制結(jié)構(gòu)可以有效解決系統(tǒng)中存在的控制難題，同時(shí)編程容易，便于在實(shí)際系統(tǒng)中應(yīng)用。
9. Neural network control is an important mode of intelligent control , and it is widely used in branches of control science , , first , the architecture and the learning rule ( error back propagation algorithm ) of multiplayered neural network which is widely used in control system are presentedo especially , the paper refers to the architecture of diagonal recurrent neural network and its learning algorithm - - - - - recurrent prediction error algorithm because of its faster convergence with low computing costo next , before introducing the neural network control to the double close loop dc driver system , the controllers of current and velocity loop are designed using engineering design approach after analysis of the system , , simulation models of the system are created
   神經(jīng)網(wǎng)絡(luò)控制是智能控制的重要方式之一，它廣泛應(yīng)用于自動(dòng)控制學(xué)科各個(gè)領(lǐng)域。本文首先敘述了控制系統(tǒng)中常用的多層前饋網(wǎng)絡(luò)結(jié)構(gòu)及算法( bp算法) ，特別提及了能夠較好描述系統(tǒng)動(dòng)態(tài)性能的對(duì)角遞歸神經(jīng)網(wǎng)絡(luò)和在用遞推預(yù)報(bào)誤差算法訓(xùn)練drnn時(shí)取得了較快的收斂速度。其次，應(yīng)用工程方法分析設(shè)計(jì)了tf - 1350糖分離機(jī)的電流、轉(zhuǎn)速雙閉環(huán)直流調(diào)速系統(tǒng)的控制器，作為引入神經(jīng)網(wǎng)絡(luò)控制的設(shè)計(jì)基礎(chǔ)，并建立了系統(tǒng)的仿真模型。
10. Firstly , on the basic of normal error back propagation algorithm ( bp a1gorithm ) , the model was added the inertia impulse item in the updating formula for weight , and then let learning rate and inertia parameter adjust ll self - adaptively , so the improved bp algorithm ( improved bp algorithm , ibp algorithm ) formed
    首先，該模型在誤差反向傳播算法( bp算法)的基礎(chǔ)上，在網(wǎng)絡(luò)權(quán)值更新公式中添加慣性沖量項(xiàng)，并對(duì)學(xué)習(xí)率和慣量因子進(jìn)行自適應(yīng)調(diào)整，從而形成bp改進(jìn)算法( improvedbp算法，簡(jiǎn)稱ibp算法) 。