weighted matrix造句
例句與造句
- grouped weight matrix for splice site recognition
模型的參數(shù)估計(jì) - pwm, position weight matrix
結(jié)合位置權(quán)重矩陣 - numerical algorithms for the weighting matrix q of discrete-time lq optimal control systems
最優(yōu)控制逆問(wèn)題解的數(shù)值算法 - construction of weighting matrixes in mixed sensitivities h controller design for aeroengine
渦扇發(fā)動(dòng)機(jī)轉(zhuǎn)速魯棒控制器設(shè)計(jì)及試驗(yàn) - in this paper, grouped weight matrix ( gwm ) method is proposed for splice site recognition
摘要提出識(shí)別剪切位點(diǎn)的分組權(quán)重矩陣方法。 - It's difficult to find weighted matrix in a sentence. 用weighted matrix造句挺難的
- the gwm model for splice signals is a mixture of weight matrix models ( wmm ) with unknown number of components
分組權(quán)重矩陣是一個(gè)子總體數(shù)未知的混合權(quán)重矩陣模型。 - it should be mentioned that all the results obtained in this chapter is relevant to the hypnosis that the weight matrix is symmetric . chapter 5 is made up of two sections
而這些結(jié)果都不是以連接權(quán)矩陣具有對(duì)稱性作為前提，所以部分結(jié)果涵蓋了原有的在對(duì)稱連接權(quán)矩陣條件下的前人的一些結(jié)果 - the two-stage method, including the weighting matrix important for the stage-two regression, is discussed detailedly in the paper . 4 . analysis of the attenuation law of ground motion energy
本文對(duì)兩步回歸法做了詳細(xì)的論述，尤其對(duì)第二步回歸分析時(shí)的加權(quán)矩陣做了細(xì)致的分析，并編制了計(jì)算程序。 - by contriving appropriate algorithms in the computations, the regularized parameter can automatically correct to the appropriate value due to its adaptive character, meanwhile, the adaptive effect is developed with a weight matrix included in the regularized item
運(yùn)算中合理地設(shè)計(jì)算法,自適應(yīng)的正則化參數(shù)可以自動(dòng)修正到最優(yōu)值,同時(shí)自適應(yīng)加權(quán)的正則項(xiàng)使算法的性能更加完善。 - after analyzing the functions of the weighting matrices q and r, an efficient method, which is very easy to calculate with clear meaning, to select q and r is proposed . without iteration process, this method can save computational time considerably
同時(shí)分析了加權(quán)矩陣在最優(yōu)控制器設(shè)計(jì)中的作用，提出了一種簡(jiǎn)單有效、意義明確、計(jì)算量小、不需要疊代計(jì)算的加權(quán)矩陣選取和計(jì)算方法。 - an updated-latin hypercube sampling and calculated data based on wave motion theories are adapted for efficient generation of the patterns of training the neural network . the levenberg-marquardt algorithms was applied to modify the weight matrices of neural network
采用修正的latin超立方采樣技術(shù)和波動(dòng)理論的計(jì)算數(shù)據(jù)來(lái)形成網(wǎng)絡(luò)的輸入和輸出數(shù)據(jù)，用lm算法訓(xùn)練網(wǎng)絡(luò)，改善了網(wǎng)絡(luò)訓(xùn)練的收斂性能。 - we compose a neural network in which the input signals are the frame substructure natural frequencies and mode shapes, and output signals are the submatrix scaling factor . the levenberg-marquardt algorithms is applied to modify the weight matrices of neural network
框架子結(jié)構(gòu)在動(dòng)載作用下的自振頻率和模態(tài)作為網(wǎng)絡(luò)的輸入，子矩陣參與系數(shù)作為網(wǎng)絡(luò)的輸出，用levenberg一marquardi算法訓(xùn)練網(wǎng)絡(luò)。 - with a new fitness, the evolutionary strategy is used to optimize the weight matrix and the clustering accuracy based on the partition similarity is used to evaluate the clustering result . the experiment gives a better result with the soybean disease data set as the input samples
應(yīng)用進(jìn)化策略對(duì)屬性進(jìn)行加權(quán)，改進(jìn)了fuzzyk-modes算法，以基于劃分相似度的聚類精確度為聚類結(jié)果的評(píng)價(jià)準(zhǔn)則，進(jìn)行實(shí)驗(yàn)分析，獲得了較好的聚類效果。
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