搜神傳 的英文怎麼說
中文拼音 [sōushénzhuàn]
搜神傳
英文
legend of the demigods-
A combined neural network and genetic algorithm with solving stability safety of homogeneous slope was proposed and the finite element method is applied to analysis the progressive failure process of the slope and the maximum equilibrium theory, requests out stability safety of homogeneous slope with the smooth arc radius of difference with the difference below the level coordinate of arc peak, utilizing the neural network algorithm to establish slidng the nonlinear mapping relationship between level coordinate of arc radious and arc peak, being adapted the neural network algorithm to look for along the minimal stability safety of homogeneous slope and corresponding arc radious and arc peak
提出了求解邊坡穩定性安全系數的神經網路與遺傳演算法。該方法採用有限元分析和極限平衡理論，求出不同的滑弧半徑和不同的弧頂水平坐標下的邊坡穩定性安全系數，利用神經網路演算法建立滑弧半徑和弧頂水平坐標與安全系數之間的非線性映射關系，採用遺傳演算法搜索邊坡的最小穩定性安全系數及相應的滑弧半徑和滑弧中心坐標。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。Genetic algorithm ( ga ) is a simple, wide - used, and robust probability searching algorithm, compared to other optimizing methods, ga adopts some particular methods and techonolgies, and is easy to be mixed with other techniques such as neural network, fuzzy reasoning, so it has been used widely
遺傳演算法是一種簡單，通用，魯棒性強的概率搜索演算法。與傳統的優化方法相比，它採用了許多獨特的方法和技術，並且易於和別的技術（如神經網路，模糊推理）相融合，從而應用范圍非常廣泛。Xinyu is the birthplace of the ancient legend ablut " the seven fairies down to the human world ", from which this area got its name as the fairy lake scenic and historic interest area. the spots covers a total land area of 298 sqkm, among which 50sqkm is water covering
新余為古籍《搜神記》中"七仙女下凡"傳說的發祥地，仙女湖風景名勝區因此而得名。景區總面積298平方公里，其中水域面積50平方公里，有大小島嶼100多個，最大的龍王島海撥190米，面積達700畝。Thirdly, considering the characters of bp neural networks which is good at local minimum and bad in global optimization and the feature of ga neural networks which is bad in local minimum and good at global optimization, the paper proposes a new algorithm combined ga with bp, referred as to hybrid intelligence learning algorithm, which is applied to the problem optimizing the connection weight of the feedforward neural networks
第三，針對bp神經網路局部搜索能力強、全局搜索能力差和基於遺傳演算法的神經網路全局搜索能力強、局部搜索能力差的特點，本文提出了一種集bp演算法和遺傳演算法優點為一體的混合智能學習法，並將其應用到優化多層前饋型神經網路連接權問題。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Analyses the incompleteness of medical diagnosis experts knowledge and discusses the method of integrating expert system with neural network for the representation and acquisition of expert knowledge, and the single parameter dynamic searching algorithm which acts as the studying algorithm of neural network and works better than bp algorithm, and then presents an intelligent medical diagnostic system designed by integration of expert system and neural network for clinical diagnostic purpose and concludes from test the results that the method of integrating expert system with neural network is effective for representation and acquisition of expert knowledge for medical diagnosis system
討論了神經網路理論在智能醫療診斷系統方面的應用，在分析醫療診斷專家知識不完備性的基礎上，研究了適應醫療診斷系統專家知識表達與獲取的專家系統與神經網路集成方法.提出了採用單參數動態搜索演算法訓練神經網路，其效果明顯優于傳統的bp演算法.設計了專家系統與神經網路集成的心血管疾病智能醫療診斷系統，在臨床實踐中取得了較好的效果，證明專家系統與神經網路的集成是醫療診斷系統專家知識表達與獲取的有效方法However, the neural network easily falls into local minimum, and weakly search the overall situation. the genetic algorithm ( ga ) has the ability of searching overall situation. the genetic neural network recombines the genetic algorithm ’ s of seeking the superior overall situation and the neural network ’ s nonlinear characteristic and rapid convergence
但神經網路具有易陷入局部極小值以及全局搜索能力弱等缺點;而遺傳演算法具有較好的全局最優搜索能力，遺傳神經網路將兩者結合，既保留了遺傳演算法的全局尋優的特點，又兼有神經網路的非線性特性和收斂的快速性。So the improvement, such as the self - adaptive fitness function combined with the penalty function methods, self - adaptive crossover probability and the bp operator enlightened by neutral network, especially the bp network to improve the local optimal capacity were used
其次結合懲罰函數法對適應度進行了優化。採用自適應交叉概率。受神經網路中bp演算法的啟示，構造bp運算元，提高小種群遺傳演算法的局部搜索尋優能力。Considering self - recursion " structure can work on its inversion effect, so the paper uses contractive mapping genetic algorithm to search its optimal struct
考慮到自遞歸神經網路的結構影響到其反演效果，本文利用壓縮映射遺傳演算法來搜索其最佳的結構。After the mapping of rock parameter and rock displacement is constituted by neural network, genetic algorithm is used to search optimum rock parameter. the result is good
採用神經網路建立起巖體力學參數與巖體位移之間的映射關系之後，本文應用遺傳演算法對巖體力學參數進行搜索尋優，在計算中取得了較好的效果。Because of ga ' s advantage of globally searching, it can avoid ann ' s problem of local convergence. thus the advantages of both ga and ann are brought into play completely
遺傳演算法有全局搜索的特點，可以避免神經網路局部收斂的問題，充分發揮遺傳演算法和神經網路各自的優勢。Aim at bp arithmetic shortcoming of tend plunging local minimum value, applied amelioration inherit arithmetic in taking object as the approach of searching information to overcome local convergence of nn
針對bp演算法具有易於陷入局部最小值的缺點，應用改進遺傳演算法直接以目標函數值作為搜索信息途徑，克服神經網路的局部收斂的缺陷。Neural network system which can self study and self adapt can well solve the shortcoming, there still have the shortcoming of low training speed ， apt to get into local minimal value and poor macrocosm searching ability for neural network. after studying genetic algorithms, it was found that ga can better mend the shortcoming
但是神經網路存在訓練速度慢，易陷入局域極小值和全局搜索能力弱等缺點。在研究了遺傳演算法后，發現它可以較好地改進以上的缺點。所以在此基礎上，利用進化神經網路，採取bp演算法和遺傳演算法建立了真核生物基因啟動子識別模型。Topics covered include : applications of rule chaining, heuristic search, logic, constraint propagation, constrained search, and other problem - solving paradigms, as well as applications of decision trees, neural nets, svms and other learning paradigms
涉及的主題包括：鏈式規則的應用、啟發式搜索、邏輯、約束傳播、約束搜索和其它問題解決範例，另外還有決策樹的應用、神經網路、向量機（ svm ）以及其它學習範例。With the precondition that neural network model can accurately reflect the operation situation of the systems, the paper discusses how to effectively integrate the neural network and genetic algorithm, by utilizing the comprehensive searching ability, to minimize the energy consumption of the system under a specific load. the controlling state parameters of the system and the calculation results indicate the optimization result of a steady state is satisfactory
在神經網路模型能準確的反應系統運用工況的前提下，本文討論了如何將神經網路與遺傳演算法有效的結合起來，利用遺傳演算法的全局搜索能力，尋找在特定負荷下為使系統的能耗最小，系統中各控制參數的狀態，計算表明系統穩態優化結果令人滿意。The optimal design of water supply networks has been broadly and deeply studied by many domestic and foreign scholars because of its important status in water supply engineering. the scholars advanced many kinds of optimal methods, such as tabu search method, simulated annealing method, genetic algorithms method, artificial neural networks method
由於給水管網優化設計在給水工程中佔有重要地位。國內外學者對其進行了廣泛而深入的研究，提出了多種優化方法，諸如禁忌搜索、模擬退火、遺傳演算法和人工神經網路演算法。After briefly introduce the basic genetic algorithm ( ga ) theory, aimming at the " prematurity " of basic genetic algorithm, we put forward a new improved genetic algorithm, the basic genetic algorithm combine simulate anneal ing ( gasa ), to meliorate the local search ability of basic genetic algorithm. because many design problems, such as the preliminary fuzzy rule and input and output membership fuction are hard to gain and the learni ng process of fuzzy neural network ( fnn ) is slow and local optimization, we design the fuzzy neural network excitation controllers of turbine generators with genetic algorithm combine simulate anneal ing ( gasa )
本文首先介紹了水輪發電機勵磁控制方式和軟計算理論的發展，然後介紹了遺傳演算法的基本理論，針對基本遺傳演算法存在的「早熟」現象，介紹了一種遺傳演算法結合模擬退火的改進型遺傳演算法，改善了基本遺傳演算法的局部搜索能力。鑒于常規模糊神經神經網路勵磁控制器設計方法中存在著初始模糊規則和輸入輸出隸屬度函數難以確定以及模糊神經網路訓練緩慢和難以達到全局最優等問題，利用遺傳演算法結合模擬退火的改進型遺傳演算法來設計模糊神經網路勵磁控制器。Besides, it is not fit with the precise adjustment and is difficult to conform the place. a new adaptive genetic algorithm with bp algorithm to optimize weight is backed up. the algorithm which combines the merits of the global convergence of genetic algorithm with fast local researching of bp algorithm not only intensifies the gradual convergence and evolution ability but also advance the speed of convergence, precision of training and generalization
針對傳統遺傳演算法的搜索過程帶有一定的盲目性，其收斂特性不穩定且收斂速度緩慢，特別是在系統規模較大時，優化效果的明顯改善往往需要相當長的時間，而且不適合候選解的精調，難以確定解的確切位置，提出一種新型自適應性遺傳演算法，並在此基礎上，用bp演算法優化前向神經網路權值，綜合了兩種演算法的優點，即遺傳演算法的全局收斂性和bp演算法局部搜索的快速性，強化了遺傳演算法的漸進收斂和進化能力，全面改善了演算法的收斂性，提高了收斂速度及訓練精度，也擴展了泛化能力。In the procedure of control, pnn studies on - line and gives the signals to fnnc. one of the algorithms to train networks is genetic algorithm which is based on darwinism. to avoid converge ahead of schedule or enter into the super - plane, the ratio of intercross and aberrance is self - adaptive to enhance the efficiency
在神經網路離線訓練時應用了基於達爾文進化論的遺傳演算法，為了解決一般遺傳演算法的早期收斂和陷入超平面等問題，採取對交叉和變異率自適應調整的方法來提高搜索效率。分享友人