recurrent fault 中文意思是什麼
recurrent fault
解釋
生長斷層-
It is used to provide reference to operator of power plant. in recurrent composed bp networks, the relation of interior node is enhanced because the link weight of input layer and output layer are added, and the saturation of fault prediction is avoided by using the linear prompting function
本文所建的用於鍋爐故障預測的遞推合成bp網路由於bp網路各層之間及輸入層與輸出層之間的連接權的增加和線性激勵函數的採用，極大地加強了內部節點的關聯能力，避免了bp網路預測的飽和性的出現。 -
The software of diagnosis and prediction for boiler fault is developed by using fuzzy modular networks and recurrent composed networks, and the method of mixed knowledge representation and expert system technology etc are used in this paper
本文應用模糊模塊化神經網路和遞推合成bp網路，並結合混合型知識表示和知識獲取方法、基於知識的專家系統等技術對鍋爐故障診斷與預測問題進行了研究，開發了鍋爐故障診斷與預測軟體。 -
The comparison of three models ( single variable time series model 、 multivariable time series model and gray prediction model ) shows that the multivariable time series model ' s prediction precision is the highest. it indicates that using recurrent composed bp networks can exactly predict the boiler fault in order to prevent the fault, and help operator of power plant to adjust the parameters in a permitting range
通過基於遞推合成bp網路的單、多變量時間序列模型與灰色預測模型的預測精度分析計算表明，應用基於遞推合成bp網路的多變量時間序列模型能較準確的預測鍋爐故障，指導運行人員對機組進行即時調整，使預期的參數在允許范圍內，以避免故障的發生。 -
Trend prediction and fault diagnosis tech., etc. the information intelligent processing technology facing the application is presented as an emphasis. after introducing the development situation and the whole pattern on related fields, this paper describes several algorithm applied in the simulation experiment, including direct multi - steps nonlinear autoregressive - moving average ( narma ) prediction model based on diagonal recurrent neural networks and fuzzy neural networks model based on generalized probability sum ( gps ) and generalized probability product ( gpp ), and lists the algorithm steps facing the application
作為重點，本文辟用了較大的篇幅討論面向應用（主要是趨勢預測與故障診斷）的集成智能信息處理技術，在介紹相關領域的發展情況和總體格局之後，重點闡述了幾種基於神經網路的智能演算法，包括基於對角遞歸神經網路（ drnn ）的直接多步非線性自回歸滑動平均（ narma ）預測模型，以及基於廣義概率和（ gps ）與廣義概率積（ gpp ）兩種運算元的模糊神經網路模型，給出了它們的詳細演算法及面向應用的運算步驟。
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