genetic influence 中文意思是什麼

genetic influence 解釋
遺傳影響
  • genetic : adj. 1. 遺傳（學）上的。2. 發生的，發展的；創始的。adv. -ically
  • influence : n 1 影響，感化 （on; upon）。2 勢力，權勢。3 有影響的人物[事物]，有權勢的人。4 感應。vt 1 影響。2...
  1. In addition, the computer method is proposed to get the stochastic pile capacity and the random optimum analysis is done in virtue of the genetic algorithm which can easily think over the influence of the randomness of pile capacity on the internal force of capping beam based on the thorough analysis about the primary factors influencing the randomness of pile capacity. an optimization program is worked out for the analysis which can consider the pile - soil - cap interaction and the non - linear character of the foundation soil

    此外，本文對影響基樁承載力差異性的主要因素進行了深入分析，提出了基樁承載力隨機生成的計算機方法，並採用遺傳演算法對承臺梁內力進行隨機優化分析，可方便地考慮基樁承載力隨機性對承臺梁內力的影響，並開發出能考慮樁?土?承臺共同工作及地基土非線性特性的樁基承臺梁內力優化分析程序。
  2. In this text, we first do some research on the genetic algorithm about clustering, discuss about the way of coding and the construction of fitness function, analyze the influence that different genetic manipulation do to the effect of cluster algorithm. then analyze and research on the way that select the initial value in the k - means algorithm, we propose a mix clustering algorithm to improve the k - means algorithm by using genetic algorithm. first we use k - learning genetic algorithm to identify the number of the clusters, then use the clustering result of the genetic clustering algorithm as the initial cluster center of k - means clustering. these two steps are finished based on small database which equably sampling from the whole database, now we have known the number of the clusters and initial cluster center, finally we use k - means algorithm to finish the clustering on the whole database. because genetic algorithm search for the best solution by simulating the process of evolution, the most distinct trait of the algorithm is connotative parallelism and the ability to take advantage of the global information, so the algorithm take on strong steadiness, avoid getting into the local

    本文首先對聚類分析的遺傳演算法進行了研究，討論了聚類問題的編碼方式和適應度函數的構造方案與計算方法，分析了不同遺傳操作對聚類演算法的性能和聚類效果的影響意義。然後對k - means演算法中初值的選取方法進行了分析和研究，提出了一種基於遺傳演算法的k - means聚類改進（混合聚類演算法） ，在基於均勻采樣的小樣本集上用k值學習遺傳演算法確定聚類數k ，用遺傳聚類演算法的聚類結果作為k - means聚類的初始聚類中心，最後在已知初始聚類數和初始聚類中心的情況下用k - means演算法對完整數據集進行聚類。由於遺傳演算法是一種通過模擬自然進化過程搜索最優解的方法，其顯著特點是隱含并行性和對全局信息的有效利用的能力，所以新的改進演算法具有較強的穩健性，可避免陷入局部最優，大大提高聚類效果。
  3. The obtained results do not support a major gene for body mass index in chinese, the discrepancies between our study and previous studies may result from ethnic difference between chinese and other populations ; the general model provides the best fit to the data, while the environmental model is the second parsimonious model, perhaps due to complex mode of body mass index inheritance ; a moderate heritability estimate is found for body mass index ( h2 = 0. 313 ), lower than that of other populations, this is presumably due to the fact that aside from the influence of genetic bases, body mass index is strongly influenced by environmental factors and that there is a low proportion of obese individuals in samples ( only 4. 1 % individuals have body mass index > 30 )

    分離分析的結果表明， （ 1 ）體重指數不存在主基因分離，不同於在其他非中國人群中檢測的結果，說明存在種群差異性； （ 2 ）一般模型提供了最合適模型，環境模型是次之的嚴格模型，可能由於體重指數遺傳模式的復雜性所致； （ 3 ）中國人群中體重指數具有適中的遺傳率（ h ~ 2 = 0 . 313 ） ，低於其他人群中的結果，這是由於體重指數除了受遺傳因素影響外還受環境因素影響及樣本中低比例的肥胖個體（ 4 . 1的個體bmi 30 ）的原因。
  4. Different influence on accuracy of hydraulic simulation of pipe networks by different genetic coding modes

    遺傳編碼方式對管網水力模擬準確度的影響分析
  5. The influence of cellular immunity and genetic factor on the effect of mother to infant transmission interrupted with hepatitis b vaccine

    6融合基因在恥垢分枝桿菌中的表達及其抗原性的初步研究
  6. Sleep need is partly genetic and may be determined by other factors that also influence life span, he says

    睡眠的需求一部分取決于基因，也可能取決于其他一些因素，這些因素還影響生命的長短。
  7. 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。
  8. Rather, such variables as genetic predisposition, parental predilection, sibling influence, peer pressure, educational experience and life impressions all shape the personality preferences that, in conjunction with numerous social and cultural influences, lead us to our beliefs

    其實各類變因例如遺傳傾向、父母的偏好、手足的影響、同儕壓力、教育過程與人生閱歷，都在在塑造我們的性格偏好，再配合上無數社會與文化的影響，才產生我們所懷抱的信念。
  9. Gene duplication is one of the most important factors that influence the evolution of genome size, the origination of novel gene, the genetic robustness against null mutations, the speciation, etc

    摘要基因重復是基因通過不等交換、逆轉錄轉座或全基因組重復等途徑產生一個與原基因相似的基因或堿基序列。
  10. This paper, firstly, expatiates the content and sense about optimal design of water supply networks, briefly introduces all optimal methods which have been advanced, analyzes these methods and points out their limitation, summarizes the factors which influence the results in optimal design of water supply networks ; secondly, it introduces the principle of genetic algorithms ( ga ). it takes yearly expenditure converting value as target function and sets up the ga model on optimal design of water supply networks based on sga by means of taking some effective measures on selection operator, crossover operator, mutation operator and some parameters setting ; finally, the ga model is verified by its application on engineering project

    本文首先闡述了給水管網優化設計的內容和意義，簡要介紹了已有的優化方法，分析比較了各種優化方法並指出其存在的不足，歸納總結了影響給水管網優化設計結果的各種因素；接著，介紹了遺傳演算法的基本原理，然後在標準遺傳演算法的基礎上，通過對選擇運算元、交叉運算元、變異運算元以及部分參數的設置採取改進措施，並以年費用折算值為目標函數，建立了給水管網優化設計的遺傳演算法模型；最後，通過工程實例驗證了該模型具有一定的理論和應用價值。
  11. The main factors of probabilistic neural network including the hidden neuron size, hidden central vector and the smoothing parameter, to influence the pnn classification, are analyzed ; the xor problem is implemented by using pnn. a new supervised learning algorithm for the pnn is developed : the learning vector quantization is employed to group training samples and the genetic algorithms ( ga ’ s ) is used for training the network ’ s smoothing parameters and hidden central vector for determining hidden neurons. simulations results show that, the advantage of our method in the classification accuracy is over other unsupervised learning algorithms for pnn

    本文主要分析了pnn隱層神經元個數，隱中心矢量，平滑參數等要素對網路分類效果的影響，並用pnn實現了異或邏輯問題;提出了一種新的pnn有監督學習演算法:用學習矢量量化對各類訓練樣本進行聚類，對平滑參數和距離各類模式中心最近的聚類點構造區域，並採用遺傳演算法在構造的區域內訓練網路，實驗表明:該演算法在分類效果上優于其它pnn學習演算法
  12. To calculate the definite value of every kind of factor that influence comprehensive intension of stock in short - term by genetic al. to simulate rise and decline of stock price by comprehensive intension of stock exponent in order to predict short - term stock price in a certain degree. 4

    用遺傳演算法計算出短期內影響股票綜合強度的各種因素的確定值，從而用股票指數的綜合強度模擬出股票的漲跌，以達到在一定程度上對股票價格進行短期預測的作用。
  13. A preliminary probe into non - genetic factors that influence birth weight of hainan black goats

    影響海南黑山羊初生重的非遺傳因素初探
  14. Although genetic factors influence your chances of developing osteoporosis, there is much individuals can do to overcome this

    盡管遺傳因素會影響骨質疏鬆發生的危險性，但很多措施都可以減輕這種危險。
  15. But what influence on earth did the development of genetic technology bring about the protection system of patent

    但基因技術的發展，到底給現行的專利保護制度帶來了怎樣的沖擊呢
  16. This thesis is focused on the following flve topics. first, comparative analysis of binary encoding and float encoding is made, the advantage and disadvantages of two encoding modes and their influence on genetic operators are clarified, thus the basis for reasonable description of the problems is provided. secondly, as genetic operators have an important influence on performance of algorithms, this thesis demonstrates that the simulated binary crossover can keep the mean of population unchanged, and under some conditions

    作者在論文期間的工作主要集中在以下幾個方面：對遺傳演算法中的二進制編碼和浮點數編碼進行對比分析，闡明兩種編碼方法的優缺點和對遺傳操作運算元的影響，為合理地描述待解決的問題提供一定的依據；遺傳操作運算元對演算法的性能有重大的影響，文中對模擬二進制交叉運算元對群體的分佈影響進行了分析論證，得出模擬二進制交叉能保持群體的均值，並在滿足一定條件下使群體方差變大的結論；如何保持群體的多樣性，一直是進化演算法研究的主要內容。
  17. Influence of zuojin pill modified on genetic expression of rats with anterior pathologic change of gastric carcinoma

    加味左金丸對大鼠胃癌前病變基因蛋白表達的影響
  18. The stanford researchers will also collect blood from the patients, which they hope to eentually use to identify genetic markers that influence the outcome of if

    研究人員還將採集患者血樣，希望最終能夠確定影響if成功率的遺傳學標記。
  19. This paper, firstly, expatiates the content and sense about optimal design of water supply networks, briefly introduces all optimal methods which have been advanced, analyzes these methods and points out their limitation, summarizes the factors which influence the results in optimal design of water supply networks ; secondly, it introduces the principle of genetic algorithms. it takes yearly expenditure converting value as target function and sets up the genetic algorithms model on optimal design of water supply networks based on simple genetic algorithms by means of taking some effective measures on selection oper ator, crossover operator, mutation operator and some parameters setting ; finally, the genetic algorithms model is verified by its application on engineering project

    簡要介紹了已有的優化方法，分析比較了各種優化方法並指出其存在的不足，歸納總結了影響給水管網優化設計結果的各種因素；接著，介紹了遺傳演算法的基本原理，然後在標準遺傳演算法的基礎上，通過對選擇運算元、交叉運算元、變異運算元以及部分參數的設置採取改進措施，並以年費用折算值為目標函數，建立了給水管網優化設計的遺傳演算法模型；最後，通過工程實例驗證了該模型具有一定的理論和應用價值。
  20. The problem of genetic influence of the fruits and vegetables produced by quite a few newly developed techniques of bioengineering on human body, including ling term genetic variations, either favorable or unfavorable, and the possible diseases resulted from these foods, has rationally attracted much medical research interest worldwide

    利用若干新近發展的人體生物工程技術（包括長期基因變異，含有利變異和不利變異）培育出的水果蔬菜導致的基因影響和可能由此造成的疾病問題自然而然地引起了全世界范圍內醫學研究者的濃厚興趣。
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