genetic shortcomings 中文意思是什麼
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A novel dynamic evolutionary clustering algorithm ( deca ) is proposed in this paper to overcome the shortcomings of fuzzy modeling method based on general clustering algorithms that fuzzy rule number should be determined beforehand. deca searches for the optimal cluster number by using the improved genetic techniques to optimize string lengths of chromosomes ; at the same time, the convergence of clustering center parameters is expedited with the help of fuzzy c - means ( fcm ) algorithm. moreover, by introducing memory function and vaccine inoculation mechanism of immune system, at the same time, deca can converge to the optimal solution rapidly and stably. the proper fuzzy rule number and exact premise parameters are obtained simultaneously when using this efficient deca to identify fuzzy models. the effectiveness of the proposed fuzzy modeling method based on deca is demonstrated by simulation examples, and the accurate non - linear fuzzy models can be obtained when the method is applied to the thermal processes
針對模糊聚類演算法不適應復雜環境的問題，提出了一種新的動態進化聚類演算法，克服了傳統模糊聚類建模演算法須事先確定規則數的缺陷.通過改進的遺傳策略來優化染色體長度，實現對聚類個數進行全局尋優;利用fcm演算法加快聚類中心參數的收斂;並引入免疫系統的記憶功能和疫苗接種機理，使演算法能快速穩定地收斂到最優解.利用這種高效的動態聚類演算法辨識模糊模型，可同時得到合適的模糊規則數和準確的前提參數，將其應用於控制過程可獲得高精度的非線性模糊模型 -
To overcome shortcomings in current efficiency algorithm, genetic algorithm and reverse algorithm existing in non - standard job - shop scheduling problem, a reverse algorithm of solving nonstandard job - shop scheduling problem ( njssp ) based on redundancy was put forward, the mathematical description of njssp was provided, object function was also given simultaneously
摘要為了克服現有效率演算法、遺傳演算法和逆序演算法等求解非標準作業車間調度問題時存在的不足，提出了一種新的逆序演算法。 -
Considering the shortcomings in the genetic algorithms, some improvements are proposed in order to elucidate its strong optimizing ability, genetic algorithms are used to optimize the pid parameters of ship autopilot. the comparison between the different simulation curves shows the validity of genetic algorithms in looking for the best parameters
本文首先用遺傳演算法來對船舶航向保持自動舵的pid控制參數進行在線優化，通過對用常規工程方法整定的pid控制和用遺傳演算法優化的pid控制的模擬曲線的比較，說明了遺傳演算法強的全局尋優能力。 -
The simulation results indicate the capability of genetic algorithm in fast and steady learning of neural networks, guaranteeing a global convergence and overcoming some shortcomings of traditional error back propagation algorithms, meanwhile prove that this neural networks adaptive control structure is effective to many control problems and it is easy for us to programme and employ the method in the practical system
模擬結果表明遺傳演算法能夠快速穩定地學習神經網路，保證全局收斂西安理工大學碩士學位論文並且能夠克服傳統誤差反傳演算法的一些缺點，也證明了這種神經網路自適應控制結構可以有效解決系統中存在的控制難題，同時編程容易，便於在實際系統中應用。 -
The subject focus on the issues about how to optimize the usage of material for manufacturing, especially on wood plate, the core arithmetic of the system is algorism genetic algorithms using the computer technology, the system is developed to realize the algorithms, which can optimize layout of two - dimensional cutting stock automatically the genetic algorithms overcome shortcomings of some traditional optimization, which can only get the local optimal solutions. the algorithms step out from local optimization to get the global optimization through the gene mutation of chromosome
本課題對目前製造業生產工藝中存在的下料問題，尤其是板式傢具的優化排料問題，進行了深入地分析和研究，將實數型遺傳演算法作為核心演算法，引入到系統設計中，提出了解決板材下料的一套實用演算法，結合計算機編程，實現了二維板材傢具優化下料的自動優化排料系統。 -
Then the paper analyzes the shortcomings of simple aco and proposes an approved aco algorithm, and then analyzes the intensification - diversification schemes of it. moreover experiments on dimacs benchmarks are run and the results show that the approved aco algorithm not only outperforms the simple aco algorithm, but also outperforms ea / g algorithm, the best genetic algorithm for mcp found so far
此外還利用dimacs提供的最大團問題的基準實例，對改進的蟻群優化演算法的性能進行了測試，實驗結果表明，該演算法的性能不僅超過了簡單的蟻群優化演算法，還超過了與其機制類似的迄今為止性能最好的遺傳演算法? ea / g演算法。
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