back propagation network造句
例句與造句
- Error back propagation network is one kind of ann and it ' s widely used in economics prediction
誤差反向傳播網(wǎng)絡(luò)( ebp網(wǎng)絡(luò))是人工神經(jīng)網(wǎng)絡(luò)的一種，它被大量運(yùn)用在經(jīng)濟(jì)學(xué)的預(yù)測(cè)問(wèn)題上。 - Genetic algorithm is used to optimize the initial weight of back propagation network and the operation efficiency is enhanced
用遺傳算法優(yōu)化bp網(wǎng)絡(luò)的初始權(quán)值,提高神經(jīng)網(wǎng)絡(luò)的運(yùn)算速度。 - The essence of back propagation networks is that make the change of weights become little by gradient descent method and finally attain the minimal error
其實(shí)質(zhì)是采用梯度下降法使權(quán)值的改變總是朝著誤差變小的方向改進(jìn)，最終達(dá)到最小誤差。 - To get the much more quality and rate of image compression , we bring forward another new three layers back propagation networks and it ' s arithmetic
基于此我們提出了新型二層誤差逆?zhèn)鞑ゾW(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)和算法，為進(jìn)一步提高圖像壓縮的壓縮比和壓縮質(zhì)量，我們提出了新型三層誤差逆?zhèn)鞑ゾW(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)和算法。 - Taking the evaluation criterion of lake nutrient states as sample pattern , the network was trained in the light of learning rule of error back propagation network
將湖泊營(yíng)養(yǎng)狀態(tài)評(píng)價(jià)標(biāo)準(zhǔn)作為樣本模式提供給網(wǎng)絡(luò)，按照誤差逆?zhèn)鞑ゾW(wǎng)絡(luò)的學(xué)習(xí)規(guī)則對(duì)網(wǎng)絡(luò)進(jìn)行訓(xùn)練，經(jīng)過(guò)39925次學(xué)習(xí)后，網(wǎng)絡(luò)達(dá)到預(yù)先給定的收斂標(biāo)準(zhǔn)。 - It's difficult to find back propagation network in a sentence. 用back propagation network造句挺難的
- Firstly , second harmonic component ratio and dead angles of two phase inrush ' s dispersion in three - phase transformes are acted as input variable . secondly , the method applies improved algorithm based on the original algorithm of multi - layer forward back propagation network , that is to say , adding last variational effect of weight value and bias value to this time and making use of variable learning rate . at the same time , this method also adopts dynamic form in the number of hidden floor node
首先，文中將三相變壓器兩相涌流差流的二次諧波含量比和間斷角作為網(wǎng)絡(luò)的輸入變量；其次，利用對(duì)原有bp網(wǎng)絡(luò)訓(xùn)練算法基礎(chǔ)上的改進(jìn)型算法(即在計(jì)算本次權(quán)值和閾值的變化時(shí)增加上一次權(quán)值和閾值變化的影響以及采用變學(xué)習(xí)率，與此同時(shí)隱含層神經(jīng)元個(gè)數(shù)采用動(dòng)態(tài)形式) ，通過(guò)樣本訓(xùn)練使網(wǎng)絡(luò)結(jié)構(gòu)模型達(dá)到最優(yōu)。 - In the process of image compression , considering that the three or more layers bp networks have some redundancies in the weights between input layer and meddle layer so as to effect the network ' s study speed and compression quality , we bring forward a new two layers back propagation networks and it ' s arithmetic
考慮到利用三層及三層以上bp網(wǎng)絡(luò)對(duì)圖像壓縮，其有效信息是中間層單元上的輸出值和中間層與輸出層之間的連接權(quán)，而輸入層與中間層的連接權(quán)是冗余的，以至于對(duì)學(xué)習(xí)速度和壓縮質(zhì)量有負(fù)面影響。