自然進化 的英文怎麼說
中文拼音 [zìránjìnhuà]
自然進化
英文
natural evolution-
Edm has some remarkable advantages over traditional models, includes using implicit causal models, self - learning capacity, weak dependence on domain knowledge, wide applicability, robustness, self - adaptability, and population - based searching, etc. tracing back its intrinsical ideas, edm is just making use of the nature ' s decision making strategy, natural selection, to solve the decision making problems faced by human or the intelligent agents
進化決策主要利用了進化演算法與形式化計算模型相結合所具備的自動建模能力，它具有隱式因果模型、自學習、弱知識依賴、應用廣泛、穩健性、自適應和群體搜索等優勢。追根溯源，進化決策的基本思想正是利用大自然的決策機制（自然選擇）來解決客觀世界所提出的決策問題，而自然進化又是已知的能力最強的問題求解范型。In the analysis of ecological relationship between vegetation and environment, we got 11 community types by combining twinspan with dca. the first axis of oca indicated the elevation level and heat gradient while the second axis indicated slope factor. the analysis shows that the resource of tourism in pangquan gully is abundant and the construction is rational
第一軸基本上反映了各植物群落所在環境的海拔和熱量梯度，從左到右，海拔在體呈升高趨勢，熱量呈下降趨勢；第二軸基本反映了各植物群落所在的坡度梯度，從下到上呈良好的發展趨勢，從群落類型來看，各群落類型在排序圖上有規律地分佈，得出龐泉溝植被結構合理，分佈符合自然進化規律，龐泉溝生態旅遊資源未受到破壞，人為因素不明顯。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。At first, in order to prevent the premature convergence of genetic algorithm effectively, the author brings forward a novel dyadic floating - point supplementary mutation operator. then, simulating the natural evolution, the author presents a novel topology, unoriented - connected topology, for parallel genetic algorithm. in the end, an interval decomposed optimization method is brought forward for ipga, which can improve the optimization performance of the algorithm
為提高演算法的性能，作者對遺傳演算法進行三種改進：首先，為克服遺傳演算法早熟收斂，作者提出一種新的二元浮點補碼變異運算元；其次，模擬生物自然進化模式，為并行遺傳演算法提出了一個新的并行拓撲結構- - - -無定向拓撲連接；最後，作者提出一種區間分解優化思想，來提高對最優解的搜索能力。Genetic algorithm based on natural evolutionism is a good method to resolve complicated nonlinear programming problem
摘要基於自然進化原理的遺傳演算法是一種解決復雜非線性規劃問題十分有前景的方法。Singer billy joe armstrong has said that they chose to write this way because the band has obtained respect and sway in the music world, and that this social commentary is part of their natural evolution as a band
主唱比利?喬?阿姆斯特朗曾經說過，他們之所以選擇以這樣的方式寫歌是因為該樂隊已經在樂界中獲得了尊重和影響力，這種社會評論方式是他們作為一支樂隊進行自然演化的一部分。Ga is a computational models of the human evolution, with implicit parallelism and capacity of using effectively global information
遺傳演算法（ ga ）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能力。Introducing several osl fabrication methods, mainly electric field poling method is investigated, and discussing the limit relation among poling electric field e, poling current i and natural poling intensity ps, and analyze the various factor affecting the osls quality. 4. the experiment of aperiodical litaos multi - wavelength shg is demonstrated
3 、介紹了幾種介質制備的方法，著重對高壓電場極化法進行了理論研究，討論了脈沖電壓，電流及自然極化強度p _ s之間的制約關系，分析了影響成疇質量的幾個物理因素。" anoxia related diseases are the major causes of death in the industrialized world, " said goran nilsson, a professor at university of oslo. " evolution has solved the problem of anoxic survival millions of years ago, something that medical science has struggled with for decades with limited success.
挪威奧斯陸大學的高蘭尼爾森教授說： 「與缺氧有關的疾病是造成工業化社會人類死亡的主要原因，醫學界對此進行了幾十年研究卻成果甚微，而自然進化卻早幾百萬年前就解決了缺氧存活的問題。 」He suggested that robots might naturally evolve
他說機器人也許會自然進化I ' m a natural progression of the species
我是人類自然進化（的結果） 。It is a natural evolutionary cycle where the energy will be redistributed
它是一個能量將被重新分配的自然進化的周期。That means evolution is busy selecting for antlers, aggression and alloy wheels in males, at the expense of longevity
這就意味著自然進化法則在雄性動物的選擇上會青睞犄角，侵略和合金車輪，其代價就是壽命。First, we human beings have gone through many trials and tribulations, and through this process of natural evolution, we have become more intelligent and can react more quickly
第一，因為我們人類經過很多考驗和奮斗，經過很多自然進化的過程就會變得更聰明反應更快。Though no evidence can ever be mustered to support such gigantic assumptions, this is the way that almost every philosopher of naturalistic evolutionism deals with this critical issue
雖然搜集的證據當中沒有能支持這個重大的假設，但是這幾乎是每一個自然進化主義的哲學家處理關鍵事物的方式The genetic algorithm, which simulates the evolutional process of the nature, is a global and robust algorithm, and the construction of orthogonal multiwavelets via genetic algorithm makes the guideline to determine multiwavelets clear and simple. 2
遺傳演算法是模擬自然進化過程的全局性魯棒優化演算法，利用遺傳演算法來確定由短序列正交多尺度函數所生成的正交多子波，使確定多子波的思路變得清晰而簡單。The evolutive principle and the survival mechanism are applied in the algorithm. as a result, the best result can be fast achieved with high probability. the dissertation starts by explaining the basic notions of iterative function system and evolutionary algorithms
在進化過程中，它引入了自然進化和適者生存的原理，在復雜和變化的環境中尋找最有利的生存方式，可以以較大的概率較快速地找到最優解。3. in order to improve searching quality of restricting optimization, good and bad gene code method has been brought forward. its focus lays in emphasizing the value of gene to targets and more precisely simulate evolvement mechanism so that useful information in problem space will be used completely
為提高約束優化的搜索質量，提出了基因優劣編碼，其重點是精確模擬自然進化機制，著重強調各基因位對優化目標的價值作用，越有利於優化目標的基因位越有價值，從而使問題空間的有益信息得到了充分利用。It clearly allows us to engineer enzymes with novel functions and features by strategies, such as error - prone pcr, dna shuffling and stagger extension process ( step ), when very little is known about spatial configuration of proteins. therefore millions of years in nature can in principle be accomplished in the test within several years. according to the basic idea of directed evolution, we modified the a - aldc gene by error - prone pcr
它不需要事先了解酶的空間結構和催化機制，而通過在體外模擬自然進化機制（隨機突變，重組和自然選擇） ，利用易錯pcr ， dna改組，交錯延伸等方法，改造酶基因，定向選擇（或篩選）有價值的非天然酶，短期內在試管中完成在自然界需要幾百萬年的進化過程。As we can see, they are different even opposite on the basic subject of some economic theories, mainly on different comprehension of rationality, equilibrium, heterogeneity, uncertainty, etc. and, their model technique also has lots of variance. neoclassical endogenous growth theory applies lots of dynamic optimization method to solve balance growth path, and evolutionary growth theory is evolved by micro individual, technology search within uncertainty terms, natural selection of market to decide growth path. neoclassical endogenous growth theory and evolutionary growth theory have same object together, that is understand economic growth better, particularly kernel object : technological progress
包括:基於水平創新的內生增長進化模型，用於分析家庭儲蓄策略的進化對人均產出的影響;基於垂直創新的內生增長進化模型，用於分析壟斷企業定價策略的進化對人均產出的影響;開放條件下的內生增長進化模型，關注于技術的生產過程，並考查開放經濟中國與國之間研發部門的聯合進化問題;轉軌條件下的內生增長進化模型，考查經濟增長從實物資本驅動到人力資本驅動再到人力資本與創新聯合驅動的兩次轉軌動態，並把兩次轉軌看成是經濟主體內生的自然進化過程。分享友人