Calculation of slope erosion based on neural network toolbox of matlab 神經(jīng)網(wǎng)絡(luò)工具箱的邊坡沖刷量計(jì)算
The application of matlab neural network toolbox on system identification 神經(jīng)網(wǎng)絡(luò)工具箱在系統(tǒng)辨識(shí)中的應(yīng)用
An available neural network toolbox ( nnt ) in matlab , however , solves the problem 而matlab軟件提供了一個(gè)現(xiàn)成的神經(jīng)網(wǎng)絡(luò)工具箱( neuralnetworktoolbox ,簡(jiǎn)稱nnt ) ,為解決這個(gè)難題提供了便利條件。
Through the thesis , we can see that it ' s easy and effective to make bp network objects by using the neural network toolbox ( nnt ) based on matlab to evaluate the predictive model 同時(shí),為了彌補(bǔ)matlab在人機(jī)交互性能上的欠缺,建立matlab與delphi之間的應(yīng)用程序接口,將delphi靈活強(qiáng)大的編程能力、 matlab強(qiáng)大的科學(xué)計(jì)算能力相結(jié)合。
Secondly , based on the neural network toolbox , a convenient realization on matlab is discussed for bp neural network , and the programming methods are presented about how to create a network , train a network and simulate a network 然后在matlab神經(jīng)網(wǎng)絡(luò)工具箱的基礎(chǔ)上,探討了bp網(wǎng)絡(luò)在matlab環(huán)境中的實(shí)現(xiàn),并給出了bp網(wǎng)絡(luò)建立、訓(xùn)練和仿真過程的編程方法。
First of all , to normalize the load data to [ - 1 , + 1 ] , and then set up the model of load forecast . then training and simulating this model with the neural network toolbox of matlab software , then get all parameters of module after trained 首先將負(fù)荷數(shù)據(jù)歸一化,建立負(fù)荷預(yù)測(cè)模型,然后使用matlab軟件中的神經(jīng)網(wǎng)絡(luò)工具箱對(duì)該模型進(jìn)行仿真訓(xùn)練,計(jì)算出訓(xùn)練后的模型各個(gè)參數(shù)。
Secondly , matlab neural network toolbox is applied to construct training network and to offer fast learning algorithm , several typical qrs waves can be recognized , which proved that this approach conduce to resolve the problem and decrease the difficulty of programming 其次,在qrs波段的檢測(cè)和識(shí)別中,使用了前饋神經(jīng)網(wǎng)絡(luò)進(jìn)行快速的訓(xùn)練分析,對(duì)典型的幾例qrs波異常進(jìn)行了成功的自動(dòng)識(shí)別分類,即能夠進(jìn)行簡(jiǎn)單的基于qrs波段的診斷。
First , features of ncrna were summed up to serve as input for data mining procedures later on . second , statistics toolbox and artificial neural networks toolbox of matlab were used to carry out principal components analysis and artificial neural network training . finally , user prediction was designed in visual c + + while matcom served as interface between matlab and vc to complete the user prediction program 首先利用生物學(xué)實(shí)驗(yàn)數(shù)據(jù)總結(jié)出ncrna的特征,作為數(shù)據(jù)挖掘方法的輸入;然后在matlab環(huán)境下用統(tǒng)計(jì)工具箱和神經(jīng)網(wǎng)絡(luò)工具箱對(duì)輸入的特征進(jìn)行主成分分析和神經(jīng)網(wǎng)絡(luò)訓(xùn)練,用訓(xùn)練好的網(wǎng)絡(luò)去預(yù)測(cè)ncrna ;最后,為了實(shí)現(xiàn)通用性,運(yùn)用matcom接口與vc實(shí)現(xiàn)windows下供用戶實(shí)際使用的預(yù)測(cè)程序。
The fault diagnosis software of power supply system applying the expert system theory is programmed under vb 6 . 0 . while the fault diagnosis of electric load manage center and solid state power controller is based on the neural network theory , whose software is realized through adopting the neural network toolbox of matlab 6 . 1 in vb 6 . 0 對(duì)于飛機(jī)供電系統(tǒng),在vb6 . 0中編寫了基于專家系統(tǒng)理論的故障診斷軟件;對(duì)于電氣負(fù)載管理中心和固態(tài)功率控制器,其故障診斷軟件則基于神經(jīng)網(wǎng)絡(luò)理論,通過在vb6 . 0中調(diào)用matlab6 . 1的神經(jīng)網(wǎng)絡(luò)工具箱完成。