混合神經網路 的英文怎麼說

中文拼音 [húngěshénjīngwǎnglù]
混合神經網路 英文
hnn hybrid neural network
  • 混 : 混形容詞1. （渾濁） muddy; turbid2. （糊塗; 不明事理） foolish; stupid
  • 合 : 合量詞（容量單位） ge, a unit of dry measure for grain （=1 decilitre）
  • 神 : Ⅰ名詞1 （神靈） god; deity; divinity 2 （精神; 精力） spirit; mind 3 （神氣; 神情） expression; l...
  • 經 : 經動詞[紡織] （把紡好的紗或線梳整成經紗或經線） warp
  • 網 : Ⅰ名詞1 （捕魚捉鳥的器具） net 2 （像網的東西） thing which looks like a net 3 （像網一樣的組織或...
  • 路 : 1 （道路） road; way; path 2 （路程） journey; distance 3 （途徑; 門路） way; means 4 （條理） se...
  • 混合 : （攙雜在一起） mix; blend; mingle; admix; mixture; mix up; interfusion; commixture; blending; cre...
  • 神經 : nerve; nervus
  • 網路 : 1. [電學] network; electric network2. （網） meshwork; system; graph （指一維復形）; mesh
  1. The two - dimensional henon chaotic nonlinear map is effectively controlled by the proposed approach. secondly, because of the distinguished advantages, such as rapid convergency and strong approachability, the rbf networks is trained as chaotic controller by ogy scheme, then successful of controlling the henon chaotic map

    其次，利用一種學習過程收斂速度快、擬合能力強的rbf神經網路，以ogy法為依據，訓練網路成為混沌控制器，仍以henon映射作為混沌控制對象，對其混沌行為實施了成功控制。
  2. In algorithms, classification algorithms are divided into two cases : one for known statistical distribution model and the other for unknown statistical distribution model. four classification algorithms, the bata - prime statistic model fusing quadratic gamma classifier, based on sar image rcs reconstruction and space position mode, on the mixed double hint layers rbfn ( mdhrbfn ) model and on the self - adapt fuzzy rbfn ( afrbfn ) model, are derived. the problems, including how to further improving the class ratio of the bayes decision, decreasing the dependence on the statistical model and directly providing the adapted algorithm with samples, are solved

    提出了基於徑向基函數神經網路（ rbfn ）的雙隱層混合網路（ mdhrbfn ）模型，解決了標準神經網路在具體sar圖像地物分類中分類類別數目不夠和分類精度差的問題；提出了基於模糊推理系統的自適應模糊rbfn分類（ afrbfn ）模型，兼顧通用性與精確性，增強人機交互能力，進一步提高了演算法分類率。
  3. The experimental results show that the system constructed by this method has the virtues of robustness, flexibility, explicable ability and self - study capability, since the new method has got both the merits of expert system and of neural network

    實驗結果表明，混合型專家系統既具有專家系統靈活性、解釋性的特點，又具有神經網路魯棒性、自學習能力的特點，因此非常適合用於企業信用評價，具有廣泛的應用前景。
  4. Secondly, the artificial neural networks and mixed evolutionary computation are employed into the mathematical simulation of complex geological structure, and with gis and visualization technique, the method of geological digital 3 - d modeling and visualization is presented. so, not only the functions of making geological section and querying spatial information could be achieved, but also the spatial distribution of geological structures and their complex relationship could be described visually. thereby an interactive and convenient way for engineering geological design could be actualized

    （ 2 ）提出了復雜地質構造數學模擬的神經網路方法與混合進化方法，並利用gis技術和可視化技術，深入研究了數字地質三維建模及其可視化方法，實現了地質三維任意剖切、信息空間查詢與管理等功能，從而為直觀描述地質構造的空間展布及其相互間的復雜空間關系，以及快捷、交互地進行工程地質設計提供了新的途徑與手段。
  5. The knowledge base includes diversified rules, such as basic and complex rule composed of vary tests item, diagnosis rule that distributed impliedly over combined chaos neural network and the transformer fault case

    專家系統知識庫包括：由針對各類試驗項目組成的基本規則與復合規則；隱含分佈於組合混沌神經網路中的診斷規則；各類變壓器故障實例組成的源範例。
  6. It supply a gap of single way to adopt the reasoning mechanism cooperated with case - based reasoning and the combination of positive reasoning and chaos neural network model

    採取正向推理與混沌神經網路模型相結合併與範例推理相互驗證的推理機制彌補了單一方式的不足。
  7. In view of the feature of neural network and its advantages in pattern recognition, we have a great deal work in off - line handwritten character recognition based on neural network. we present two recognition methods based on neural network. one of which is the hybrid neural network recognition system, a multi - level neural network classifier constructed by using the multi neural networks integration technology

    由於神經網路的特點及其在手寫體字元識別領域體現出的潛力，本文對基於神經網路的手寫體字元識別技術進行了大量的研究工作，提出了兩種新穎的基於神經網路的手寫體字元識別模型，其中，基於混合神經網路的手寫體字元識別模型利用了在抗干擾和描述字元拓撲結構方面具有互補性的中心投影特徵和llf特徵，使用多神經網路集成技術構建了多級的神經網路分類器。
  8. Research on mixture neural network model based on radial basis function

    基於徑向基函數的混合神經網路模型研究
  9. Besides stability, bifurcation and chaos in neural networks have receiving much attention recently. in this dissertation, we propose two neuron models with chaotic dynamics, which constitute chaotic neural networks that encompassed various associative and back - propagation networks

    除了穩定性之外，極限環以及混沌也是神經網路動態行為研究的重點，本文構造了具有混沌解的兩種神經元模型，通過混沌神經元的耦合可以構成混沌神經網路。
  10. By combining chaotic dynamics and converging dynamics together, the neural network transit gradually to hopfield neural network is made. by introducing converging factor, the aim of controlling chaos is attained, which provides initial value of hopfield neural network that is near to the global optimal solutions, and solve the problem of local minimum. the principle of genetic algorithm is analyzed, and the design and of genetic algorithm are studied

    通過把混沌動力學與收斂動力學相結合，使網路逐漸由混沌神經網路向hopfield網路過渡，達到控制混沌的目的，並且提供了一個在全局最優解附近的初值，避開了神經網路權值初始化沒有理論依據的難題，無須確定連接權值和閾值，使神經網路具有物理意義明確、便於與工程應用相結合的特點。
  11. The paper is divided into three parts. firstly, from chapter one to chapter two the author mainly states the importance of combining the chaos with the neural network in the field of the intelligent message treatment, especially of associative memory

    論文分為三部份，從第一章到第二章詳細論述了混沌與神經網路相結合的方法在智能信息處理特別是聯想記憶中的重要意義，簡述了聯想記憶混沌神經網路的理論基礎。
  12. An image compressing algorithm based on pca sofm hybrid neural network

    混合神經網路的圖象壓縮演算法
  13. All these methods are new edge subjects, so researchers apt to investigate the relations between them. each of these three subjects can reflect one aspect of information processes in brain, and the existing anns, such as fuzzy neural networks ( fnn ) and chaotic neural networks ( cnn ), can only behave one or two aspects of those. a new method which is based on fl, ann and chaos is proposed in this paper

    本論文從模糊邏輯、人工神經網路和混沌動力學三方面出發，探索它們之間的相互交叉和融合，在對現有的各類混沌神經網路進行深入研究和改進的基礎上，對三者結合方面即模糊混沌神經網路進行研究，試圖從另一側面更加全面的了解人腦處理信息的過程，從而推動人工智慧科學向前發展。
  14. Development of a car - following model based on combined neural network model

    混合神經網路跟馳模型的建立
  15. A simple and effective fuzzy identification approach is presented

    摘要提出一種簡明而有效的基於混合神經網路的模糊辨識方法。
  16. Application of generalized hybrid neural network modeling methods in penicilllin fermentation process

    混合神經網路建模方法在青霉素發酵過程中的應用
  17. In this research background, this paper come up with a ftc method based on the hybrid neural network and apply hi the ship automatic manoeuvre system

    本文就是在這樣的研究背景下，運用集成智能技術，提出一種基於混合神經網路的容錯控制方法，並應用於船舶控制系統。
  18. Simulation results show that this fuzzy neural networks ( fnn ) has better generalization and approximation abilities. 3. it is compared the three kinds of multi - resolution neural networks ( mrnn )

    針對目前發酵過程應用的混合神經網路模型做了比較，串連型和串並聯型混合神經網路訓練復雜，許多成熟的訓練方法不能採用。
  19. The training of the multi - resolution neural networks in parallel is simple. but the generalization ability is bad compared to the other multi - resolution neural networks. so we use the multi - resolution fuzzy neural networks model

    並聯混合神經網路訓練方法簡單，但泛化能力不強，因此，本文採用anfis的混合模糊神經網路模型，與並聯的混合神經網路相比，其泛化能力和建模精度都有了提高。
  20. The principle research contents include : ( 1 ) this paper comes up with a new ftc scheme based on the hybrid neural network, which is focused on the sensor failure and actuator failure, thus make use of multi - neural network to realize the fault detection and fault tolerant control of the system

    主要研究內容包括： （ 1 ）提出了一種新的基於混合神經網路的容錯控制系統框架結構，針對傳感器和執行器兩類故障，應用多種類型神經網路實現系統的故障檢測與容錯控制。
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