Fourthly , the design of fuzzy inference engine for satellite environment control in accordance to the fuzzy inference theory 第四,根據(jù)模糊推理原理設(shè)計(jì)了衛(wèi)星環(huán)境控制模糊推理機(jī)。
Experiments proved its efficiency and robustness . this recognition system introduced d - s inference theory in statistical pattern recognition , and implemented it by neural network 該系統(tǒng)充分結(jié)合了d ? s證據(jù)理論在不確定性推理方面的優(yōu)勢(shì)以及神經(jīng)網(wǎng)絡(luò)強(qiáng)大的非線性處理能力,實(shí)驗(yàn)結(jié)果表明了這一形狀識(shí)別系統(tǒng)的有效性。
Abstract : the mathematical model of reliability design for shaft rigidity was established based on reliability inference theory . reliability calculation of cylinder shaft rigidity of press was proceeded and regularity of cylinder shaft rigidity reliability as the condition change was found 文摘:應(yīng)用可靠性設(shè)計(jì)相干理論建立了軸的剛度可靠性設(shè)計(jì)的數(shù)學(xué)模型,著重探討印刷機(jī)印刷滾筒軸的剛度可靠度的計(jì)算,并得出不同條件下印刷滾筒軸剛度可靠度的變化規(guī)律。
Furthermore , the bayesian inference theory about unrestricted and restricted var ( p ) model under the parameter ' s prior distributions is explored . the structure of minnesota conjugate prior distribution , its hyper - parameters and determination , and the bayesian theory about var ( p ) model under the special conjugate prior distribution are all analyzed in detail 其次,探討了非限制性和限制性var ( p )預(yù)測(cè)模型的貝葉斯推斷理論,系統(tǒng)地分析了著名的minnesota共軛先驗(yàn)分布的結(jié)構(gòu)及其超參數(shù)的設(shè)置,以及該先驗(yàn)分布下var ( p )模型的貝葉斯推斷。
This paper mainly deals with the multivariate bayesian inference theory used in the modern economical and management science . this includes the bayesian inference theory about three important kinds of linear models , including the single equation model , multiple equation model system and var ( p ) predictive model , and their application in economic forecasting and quality control , and also the design for the bayesian classification identification method among multiple populations 本文主要研究現(xiàn)代經(jīng)濟(jì)管理中的多元貝葉斯推斷理論,包括單方程模型、多方程模型系統(tǒng)和向量自回歸var ( p )模型的貝葉斯推斷理論及其在經(jīng)濟(jì)預(yù)測(cè)與質(zhì)量控制中的應(yīng)用,以及多總體的貝葉斯分類識(shí)別方法的構(gòu)造。