fnns 中文意思是什麼
fnns
解釋
模糊神經網路系統-
This paper is mainly devoted to the principle and the implemental algorithms of qualitative learning for feed - forward neural networks ( fnns )
本文主要研究前向神經網路定性學習的原理和學習演算法。 -
To overcome the limitations of general fnns and bp algorithm, this thesis introduced a hybrid feed - forward neural network, which is composed of a linear model and a general multi - layer fnn, and proposed a new learning algorithm for the hybrid fnn
其次，針對bp網路存在的缺陷，結合前向神經網路和線性最小二乘法的優點，構造了一種基於混合結構的神經網路，提出了相應的非迭代的快速學習演算法。 -
Also, the supervisory controller is appended into the fnns controller to force the system states to remain within constrains
利用監督控制器的特點，使控制過程系統所有狀態均處在約束集范圍內。 -
Taking in - situ toughened silicon nitride as a design object, principle component analysis ( pca ) is applied to study the microstructure and mechanical properties, to find out the main microstructure controlling factors, and to simplify the characterization variables and criterions ; fuzzy neural networks ( fnns ) is also applied to develop a design expert system for this material, which can realize the forward prediction from processing, microstructure to mechanical properties, and backward design from mechanical properties or microstructure to processing ; monte - carlo method is applied to simulate the grain growth of this material, and then crack propagation is simulated, which is another way based on physics and chemistry to developing prediction models from processing until to mechanical properties
本文以自增韌氮化硅陶瓷為設計對象，運用主成分分析法（ principlecomponentanalysis ： pca ）對自增韌si _ 3n _ 4陶瓷的顯微結構和力學性能進行數據空間降維，獲得自增韌si _ 3n _ 4陶瓷顯微結構控制的主要因素，進而簡化了表徵參量變量和準則；運用模糊神經網路（ fuzzyneuralnetworks ： fnn ）建立了自增韌si _ 3n _ 4陶瓷設計專家系統，能實現工藝?微結構?性能的正向預測及反向設計；運用monte - carlo方法（ mc ）進行自增韌si _ 3n _ 4陶瓷的晶體生長模擬，然後進行裂紋擴展模擬，探索建立工藝?微結構?力學性能預測模型的思路。 -
Finally, a perspective of learning methods for multi - output binary fnns and the qualitative learning for real - value networks are given
最後對多輸出二值網路的定性學習、以及定性學習在實數神經網路中的應用和前景作了討論。 -
Only small fuzzy rules ( “ if - then ” rule base ) are selected, the fnns may be applied to approximate the unknown chaotic system. using a lyapunov synthesis approach and the parameters projection algorithm, the free parameters of adaptive fnns controller can be tuned on - line
該方法採用少量模糊規則（ 「如果-則」語言規則） ，使模糊神經網路逼近系統中不確定函數;然後通過lyapunov函數法和參數投影演算法，即可在線調整模糊神經網路控制器參數。
分享友人