非聯想性學習 的英文怎麼說

中文拼音 [fēiliánxiǎngxìngxuéxí]
非聯想性學習 英文
non associative learning
  • 非 : Ⅰ名詞1 （錯誤） mistake; wrong; errors 2 （指非洲） short for africa 3 （姓氏） a surname Ⅱ動詞1 ...
  • 聯 : Ⅰ動詞（聯結; 聯合） unite; join Ⅱ名詞（對聯） antithetical couplet
  • 想 : 動詞1 （思索） think; ponder 2 （推測; 認為） suppose; reckon; consider; think 3 （希望; 打算） w...
  • 性 : Ⅰ名詞1 （性格） nature; character; disposition 2 （性能; 性質） property; quality 3 （性別） sex ...
  • 學 : Ⅰ動詞1 （學習） study; learn 2 （模仿） imitate; mimic Ⅱ名詞1 （學問） learning; knowledge 2 （學...
  • 聯想 : associate; connect in the mind
  1. Moreover, this thesis proposes two novel strategies : the weighted fuzzy control strategy for multi objects and the behavior control strategy based on emotion evaluation and associative learning, and these two strategies are applied on an invert - pendulum system and a simulative agent system, respectively

    最後，本文分別提出了基於對多性能指標分別加權的專家模糊控制策略，以及基於人工情感評估機制與聯想學習的行為控制策略，並分別將兩種策略應用於非精確倒立擺系統和模擬agent系統。
  2. In order to overcome problems arisen from the application of x fluorescence analysis into complex spectrum produced by archaeological ceramic fragments with multi - element, low content and thick ground, we have employed the artificial neural network into the research of x fluorescence archaeology and conducted three kinds of research works. as the first one, we have applied the linear olam network ( optimal linear association memory network ) and the non - linear bp network ( back - propagation network ) respectively to analyze the complex x fluorescence spectrum of archaeological samples, and taken both results of spectrum analysis to compare with each other. the second, the method of pattern recognition of bp network was tentatively used to perform intelligent identification of production places of these archaeological samples

    針對科技考古中對大量考古陶片進行產地研究時x熒光分析對多元素、低含量、厚基底考古陶片產生的復雜譜分析的問題，將人工神經網路引入x熒光考古中，進行了三方面的研究工作：一是用線性olam網路（最優線性聯想網路）和非線性bp網路（誤差反傳導網路）分別對考古樣品的x熒光復雜譜進行解譜，並比較二者的解譜效果；二是用bp網路模式識別方法對考古樣品的產地進行智能識別；三是為了提高網路運算的可靠性和減小基體效應及電噪聲的干擾和影響，研究並提出了三種網路學習前的譜數據預處理方法。
  3. In this paper an artificial neural network ( ann ) approach, which is based on flexible nonlinear models for a very broad class of transfer functions, is applied for multi - spectral data analysis and modeling of airborne laser fiuorosensor in order to differentiate between classes of oil on water surface

    由於ann方法適合於處理非線性系統，具有自組織、自學習、自適應和聯想能力，故通過對樣本反復訓練，能辨別各類樣本特徵差異，本論文的核心工作就是將人工神經網路（ ann ）的方法應用於激光遙感光譜數據的智能分析。
  4. As in nature, the network function is determined largely by connections ( weights ) between elements, so that a particular input leads to a specific target output. the cores of backpropagation neural network are the capacity of parallel computing, distribute saving, self - studying, fault - tolerant and nonlinear function approximating. input vectors and the corresponding target vectors are used to train a network until it can approximate a function, associate input vectors with specific output vectors, or classify input vectors in an appropriate way as defined by you

    人工神經網路是一類模擬人類神經系統的結構，他揭示數據樣本中蘊含的非線性關系，大量處理單元組成非線性自適應動態系統，具有良好的自適應性、自組織及很強的學習、聯想、容錯和抗干擾能力，在不同程度和層次上可模仿大腦的信息處理機理，可靈活方便的對多成因的復雜未知系數進行建模。
  5. Nn, one of soft measurement modeling tools having the association & recollection self - learning better fault tolerance prompt response simulation of the high nonlinear system, has its advantage in modeling the nonlinear and time - varying flux of sluice gate. this thesis focuses on the soft measurement modeling based on nn, which solves the problem quite good

    神經網路方法是一種效果較好的軟測量建模方法，具有聯想記憶，自學習，高度容錯，快速處理，能逼近高度復雜的非線性系統的特點，適用於非線性、時變的涵閘水力流量過程建模。
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