building diagnosis

基本解釋

Using BP neural network, SOC self-organizing competitive neural network and SVM support vector machine building the fault diagnosis model and to compare with their performance.
應(yīng)用BP神經(jīng)網(wǎng)絡(luò)，SOC自組織競爭神經(jīng)網(wǎng)絡(luò)以及SVM支持向量機(jī)建立故障診斷模型，比對其性能進(jìn)行比較。
Be aimed at the characteristic of the fault influencing to exhaust, building the fault diagnosis expert system through idea and method of the analyzing exhaust gas emission component is researched.
并針對影響汽車排放的故障的特點(diǎn)，通過廢氣排放成分分析的診斷思路及方法，對構(gòu)建尾氣分析專家系統(tǒng)進(jìn)行了研究。
This thesis has carried on related analysis with PEST, 5-power model, brought up the necessity of building intellect auxiliary diagnosis system in commercial enterprises;
論文中運(yùn)用PEST分析法、五力模型等方法對商業(yè)企業(yè)進(jìn)行了相關(guān)的分析，提出了構(gòu)建商業(yè)企業(yè)智能化輔助診斷系統(tǒng)的必要性；

建筑診斷
This paper is commissioned and supported by . Technology Research Center of Industrial Building Diagnosis and Reconstruct of China.
本課題研究受國家工業(yè)建筑診斷與改造工程技術(shù)研究中心的委托且得到該中心的協(xié)助。
環(huán)境科學(xué)技術(shù)
建筑診斷