隱性遺傳變化 的英文怎麼說
中文拼音 [yǐnxìngyízhuànbiànhuà]
隱性遺傳變化
英文
cryptic genetic change- 隱 : Ⅰ動詞（隱瞞; 隱藏） hide; conceal Ⅱ形容詞1 （隱藏不露） hidden from view; concealed 2 （潛伏的; ...
- 性 : Ⅰ名詞1 （性格） nature; character; disposition 2 （性能; 性質） property; quality 3 （性別） sex ...
- 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）...
- 隱性 : 1 [語言學] covert gender2 [遺傳學] recessivity; recessiveness隱性詞 opaque word; 隱性基因 recessi...
- 遺傳 : [生物學] heredity; hereditary; inheritance; inherit
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From 19 arabidopsis male sterile lines isolated from an ethyl methanesulphonate - induced ( ems - induced ) population, a total of four male sterile mutants were screened with each mutant controlled by a single recessive gene
首先對19個經化學誘變劑ems處理得到的雄性不育突變體進行背景純化和遺傳分析，從中篩選到四個單個隱性基因控制的雄性不育突變體（ ec2 - 157 、 ec1 - 188 、 ec2 - 115和ec2 - 214 ） 。Control systems in modern automatic engineering are nonlinear, time - changed and indefinite. lt is difficult to model by traditional method, even sometime impossible. under these circumstances we should apply model identification to gain the approximate model of object for effective control, there are many models to be chosen, fuzzy model is one of them, it is put forward with the development of fuzzy control. fuzzy model has characteristics of general approximation and strong nonlinear, it is fit for describing complex, nonlinear systems. to avoid rules expansion when the number of input values are very big. in this paper we apply hierarchical fuzzy model to resolve this problem, we also illustrate it has general approximation to any nonlinear systems. genetic algorithm is a algorithm to help find the best parameters of process. lt has abilities of global optimizing and implicit parallel, it can be generally used for all applications. in our paper we use fuzzy model as predictive model and apply ga to identify fuzzy model ( including hierarchical fuzzy model ), we made experiments to nonlinear predictive systems and got very good results. the paper contains chapters as below : chapter 1 preface
現代控制工程中的系統多表現為非線性、時變和不確定性，採用傳統的建模方法比較困難，或者根本無法實現，在這種情況下，要實現有效的控制，必須採用模型辨識的方法來獲取對象的近似模型，並加以控制，目前用於系統辨識的模型種類很多，模糊模型是其中的一種，它隨著模糊控制的發展而被人提出，模糊模型具有萬能逼近和強非線性的特點，比較適合於描述復雜非線性系統，為了解決模糊模型在輸入變量較多時規則數膨脹的問題，文中引入遞階型模糊模型，並引證這種結構的通用逼近特性。遺傳演算法是模擬自然界生物進化「優勝劣汰」原理的一種參數尋優演算法，它具有隱含并行性和全局最優化的能力，並且對尋優對象的要求比較低，在工程應用和科學研究中，得到了廣泛的應用，本文將遺傳演算法引入模糊模型的辨識，取得了很好的效果。Finally, genetic optimization research is summarized on several typical production scheduling problems. after expounding the general idea of genetic algorithm, the comparative advantages in contrast to the traditional algorithm, the basic characteristics of genetic algorithm and its theoretical base, the paper puts emphasis on the efficiency of genetic algorithm in the scheduling of flow shop, and puts forward an improving genetic algorithm : the ordinal genetic algorithm based on the heuristic rules. the new algorithm introduces into the initial group the solution of heuristic algorithm, and in the group structure adopts a strategy of first ordering according to the priority of the adaptive solution, and then defining a new way of choosing probability by segments, which provides more hybridizing opportunity for optimized individuals, and designs variation - control rule to prevent single population and partial optimal solution
在論述了遺傳演算法的思想、與傳統搜索演算法的比較優勢、遺傳演算法的基本特徵和遺傳演算法的理論基礎（包括模式定理、隱含并行性、基因塊假設、欺騙問題和收斂性定理）后，重點探討了遺傳演算法在flowshop調度問題中的潛力和有效性；結合啟發式規則，提出了一個改進的遺傳演算法?基於啟發式規則的有序遺傳演算法，新演算法在初始種群中引入了啟發式演算法的解，在種群結構上採用了先按適應值優劣排序再分段確定選擇概率的新策略，使優質個體有更多的雜交機會，在變異中設計了變異控制規則，以防種群單一化，而陷入局部優化解。
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