神經遺傳學 的英文怎麼說

中文拼音 [shénjīngyízhuànxué]
神經遺傳學 英文
neurogenetics
  • 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
  • 遺 : 遺動詞[書面語] （贈與） offer as a gift; make a present of sth : 遺之千金 present sb with a gener...
  • 傳 : 傳名詞1 （解釋經文的著作） commentaries on classics 2 （傳記） biography 3 （敘述歷史故事的作品）...
  • 學 : Ⅰ動詞1 （學習） study; learn 2 （模仿） imitate; mimic Ⅱ名詞1 （學問） learning; knowledge 2 （學...
  • 神經 : nerve; nervus
  • 遺傳學 : genetics; hereditism遺傳學家 geneticist
  • 遺傳 : [生物學] heredity; hereditary; inheritance; inherit
  1. Hidden markov models have been widely used for modeling sequences of weakly dependent random variables, with applications in as such as speech processing, neurophysiology and biology

    隱馬爾可夫模型可應用於弱相依隨機變量的建模上，也可用作研究發音過程、神經生理學與生物遺傳等方面的工具。
  2. This article puts forward a solution named divide - assemble by deducing the size of bp neural network to overcome entering the local best point, the dividing process is that a big bp neural network is divided into several small bp neural networks, every small bp neural network can study alone, after all small bp neural networks finish their study, we can assemble all these small bp neural networks into the quondam big bp neural networks ; on the basis of divide - assemble solution, this article discusses the preprocessing of input species and how to deduce the size of bp neural network further to make it easy to overcome entering the local best point ; for the study of every small bp neural network, this article adopts a solution named gdr - ga algorithm, which includes two algorithms. gdr ? a algorithm makes the merits of the two algorithms makeup each other to increase searching speed. finally, this article discusses the processing of atm band - width distribution dynamically

    本文從bp網的結構出發，以減小bp神經網路的規模為手段來克服陷入局部極小點，提出了bp神經網路的拆分組裝方法，即將一個大的bp網有機地拆分為幾個小的子bp網，每個子網的權值單獨訓練，訓練好以後，再將每個子網的單元和權值有機地組裝成原先的bp網，從理論和實驗上證明了該方法在解決局部極小值這一問題時是有效的；在拆分組裝方法基礎上，本文詳細闡述了輸入樣本的預處理過程，更進一步地減小了bp網路的規模，使子網的學習更加容易了；對于子網的學習，本文採用了最速梯度? ?遺傳混合演算法（即gdr ? ? ga演算法） ，使gdr演算法和ga演算法的優點互為補充，提高了收斂速度；最後本文闡述了用以上方法進行atm帶寬動態分配的過程。
  3. The horrible paradox in this almost four - century - old play of man s constitutional inability to foresee consequences while in hot pursuit of what he calls " truth " is that as each discovery of this truth has brought man close and close to his own extinction either through the prospects of physical destruction or psychological maltransformation or biogenetic tampering, science itself remains supremely and arrogantly confident of its limitless purposes and indeed has the full support and encouragement of governments, industrial entrepreneurs and peoples generally, all of whom continue to believe in its doubtful benefits

    將近四世紀以來，人類熱中追求於他所謂"真理"這個人類天生無法預見後果的游戲里，可怕的矛盾存在於，每次真理的發現，或經由預期身體的滅亡或精神惡化或擅改生物遺傳，都帶領著人類，一步一步地接近人類自身的滅絕;然科學本身，對其無限的目的，仍高傲無上地維持其自信，而且，全然保有來自，政府，企業，及普遍人們的支持與鼓勵，他們都仍然相信那其實很可疑的益處
  4. Epigenetic alterations in cell - type - specific gene expression control the transition of neural stem cells ( nscs ) from predominantly neurogenic to predominantly gliogenic phases of differentiation, but how this switch occurs is unclear

    細胞類型特異的基因表達之表觀遺傳學改變控制著神經幹細胞由神經元發生為主向膠質細胞發生為主的轉變，但是這一時相的切換機制還不清楚。
  5. It is very important to estimate the basic parameters in helicopter preliminary design. neural network ( nn ) has the advantages in estimating accuracy and generalization over traditional methods. however, there are some difficulties in using nn, e. g., how to select a proper network structure and the number of hidden layers. in this paper, structure and connection weight of a three - layer nn are optimized by genetic algorithm, and the optimized network is applied to helicopter sizing. the proposed method can not only give an optimal nn structure and connection weight, but also reduce the prediction error and has the capability of self - learning when the latest data are available. furthermore, this method can be easily applied to helicopter design systems

    在直升機初步設計階段估算其基本參數是很重要的.神經網路的通用性和精度比傳統的估算方法有更多的優勢，但是在應用神經網路時存在如何選擇合適的網路結構和隱層節點數目等一些困難.應用遺傳演算法優化三層神經網路結構和連接權重，並將優化得到的網路應用於直升機參數選擇中.該方法不但可以給出一個最優的神經網路結構和連接權重，而且降低了估算誤差，具有及時應用最新數據學習的能力.此外，該方法易於在直升機設計系統中得到應用
  6. This class grounds students in some of the more classical techniques, as well as the latest techniques in genetic manipulation and its impact on neurobiology

    這個課程讓學生學習一些更經典的技術，以及在遺傳操縱方面的最新技術與遺傳操縱對神經生物學的影響。
  7. In the algorithm level, currently various training algorithms of neural networks, including gradient algorithms, intelligent learning algorithms and hybrid algorithms, are comparatively studied ; the optimization principle of bp algorithm for neural networks training is analyzed in detail, and the reasons for serious disadvantages of bp algorithms are found out, moreover, the optimization principle of two kinds of improved bp algorithms is described in a uniform theoretic framework ; and the global optimization algorithms of neural networks, mainly genetic algorithm are expounded in detail, it follows that a improved genetic algorithm is proposed ; finally the training performances of various algorithms are compared based on a simulation experiment on a benchmark problem of neural network learning, furthermore, a viewpoint that genetic algorithm is subject to " curse of dimension " is proposed

    在演算法層，本文對目前用於神經網路訓練的各種演算法，包括梯度演算法、智能學習演算法和混合學習演算法進行了比較研究；對用於神經網路訓練的bp演算法的優化原理進行了詳細的理論分析，找到了bp演算法存在嚴重缺陷的原因，並對其兩類改進演算法-啟發式演算法和二次梯度演算法的優化原理，在統一的框架之下進行了詳盡的理論描述；對神經網路全局優化演算法主要是遺傳演算法進行了詳細的闡述，並在此基礎上，設計了一種性能改進的遺傳演算法；最後基於神經網路學習的benchmark問題對各種演算法在網路訓練中的應用性能進行了模擬研究，並提出了遺傳演算法受困於「維數災難」的觀點。
  8. Because ga possesses the traits of can global random search, the robustness is strong, been use briefly and broadly, it didn ’ t use path search, and use probability search, didn ’ t care inherence rule of problem itself, can search the global optimum points effectively and rapidly in great vector space of complicated, many peak values, cannot differentiable. so it can offset the shortages of nn study algorithm, can reduce the possibility that the minimum value get into local greatly, the speed of convergence can improve, interpolation time shorten greatly, the quantity of training reduce

    因為遺傳演算法具有全局隨機搜索能力，魯棒性強、使用簡單和廣泛的特點，它不採用路徑搜索，而採用概率搜索，不用關心問題本身的內在規律，能夠在復雜的、多峰值的、不可微的大矢量空間中迅速有效地尋找到全局最優解，所以可以彌補神經網路學習演算法的不足，使陷入局部最小值的可能性大大減少，使得收斂速度提高，訓練量減小。
  9. The paper includes the contents as follows : the second chapter introduces the basic theory of bp neural network, chapter 3 puts forward a solution named divide - assemble, chapter 4 introduces the preprocessing of input population, chapter 5 introduces the basic theory of genetic algorithms, chapter 6 discusses gdr - ga algorithms, 7 part introduces the processing of atm band - width distribution dynamically and gives several program modules among them. chapter 8 introduces the interface, running and results about the software system, the last chapter summarizes research work of this dissertation and further researches arc prospected

    本文主要包括以下內容：第2部分闡述bp神經網路基本理論，第3部分介紹了拆分組裝方法，第4部分主要介紹了bp神經網路輸入樣本的預處理，第5部分介紹了遺傳演算法的發展及其基本理論，第6章介紹的是最速梯度? ?遺傳演算法，第7部分介紹了atm帶寬動態分配過程、子網與總網的學習過程和其中的一些關鍵程序模塊，第8部分介紹的是該系統界面和運行情況，最後一部分總結了論文所做的工作和進一步工作設想。
  10. Based on the discussions of the conventional and recent methods of short term load forecasting such as time series, multiple regression approaches and artificial intelligence technologies, this paper presents a hybrid short term forecasting model which combines the artificial neural network ( ann ) and genetic algorithm ( ga ). in order to improve the convergence speed and precision of the back - propagation ( bp ), a new improved algorithm - the adapted learning algorithm based on quasi - newton method is given

    本文首先分析比較了電力系統短期負荷預測的傳統方法時間序列法和回歸方法以及最近的專家系統和神經網路技術的優點和不足，然後針對人工神經網路bp演算法的不足對其進行了改進，採用了基於擬牛頓的自適應演算法，它提高了網路學習效率，具有較快的收斂速度和較高的精度。接著提出了改進的遺傳演算法來改善神經網路的局部收斂性。
  11. The international behavioural and neural genetics society works to promote the field of neurobehavioral genetics

    國際行為學和神經遺傳學協會致力於促進神經行為學和遺傳學領域的發展。
  12. Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly

    本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。
  13. Discuss the cause of these two diseases in terms of their anatomical, genetic and neurotransmitter basis

    請就解剖學、遺傳學以及神經傳導物質方面討論這兩種疾病的成因。
  14. An improved genetic algorithm of wavelet neural network based on chaotic searching

    一種改進的基於混沌搜索策略的小波神經網路遺傳學習演算法
  15. ( 5 ) based on fuzzy control theory, fuzzy neural network ( fnn ) controller is introduced ; the changeable area and hierarchical genetic algorithm is used to training fuzzy neural network. simulation indicated that this designed fuzzy neural controller is effective

    （ 5 ）在模糊控制的基礎上，提出了模糊神經網路控制器，並用本文提出的變區域多層遺傳演算法與bp相結合進行網路學習，在理論上證明了遺傳學習演算法的收斂性。
  16. In designing a multi - structuring elements filter, combination rules and structuring elements of the morphological transform are determined automatically, and one kind of neural networks is taken for the filter, in optimzing structural parameters of the filter, three computation methods are designed respectively, by adopting some priori information in application fields to guide optimal structural parameter learning procedure, which are the bp adaptive learning algorithm, the heuristic genetic learning algorithm and the inductive simulated annealing learning algorithm

    在多結構基元濾波器設計中，通過學習人-機交互選定的目標樣本，自動確定形態變換的組合規則及其結構元素，最終以神經網路形式構成濾波器。在結構參數的優化學習中，利用應用領域的先驗知識，分別設計了自適應bp學習、啟發式遺傳學習和引導式模擬退火學習等三種最優化計算方法。
  17. Because of its ultra resolution and 3d sectioning feature, in no time, lcsm becomes a key tool of the research and application in many areas, such as biomedicine, morphologic, cytogenetics, neurology, pharmacology, etc

    由於它的高解析度與三維層析特性，迅速在生物醫學、形態學、分子細胞生物學、神經科學、藥理學、遺傳學等領域中佔有了重要的研究與應用地位。
  18. In the fast - changing world of genetics, genetic neurobiology is at the forefront

    在快速變化的遺傳世界里，遺傳神經生物學處于最前線的位置。
  19. Molecular and cellular mechanism of parkinson ' s disease ( pd ), drug therapy, surgical therapy, epidemiology of pd, genetics of pd, rehabilitation of pd, psychiatric aspects of pd and alternative medicine of pd

    帕金森病的神經生物學、內科藥物治療、外科治療、流行病學、遺傳學、康復治療、精神狀態的處理和老年人帕金森病的治療和康復。
  20. The lab is currently carrying out genetic analysis of behavior in drosophila and molecular studies of cell polarity in mammal neurons

    該實驗室目前主要興趣在於兩個神經生物學問題: 1 ）行為的遺傳學分析， 2 ）神經發育的分子機理。
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