local optimum 中文意思是什麼
local optimum
解釋
局部最優-
Introduction of prepotency operator in the initialize population step and the improved mutation operator accelerate the convergence process, and the introduction of new operator in forming new population step avoid converging in local optimum, and promote the ability of global convergence
演算法在初始化種群階段引入了「優生」運算元，以及改進的變異操作使演算法的收斂速度大大提高；在形成新種群階段引入新的運算元避免了局部早熟，提高了全局收斂能力。 -
The registration results showed that the subvoxel accuracy could be achieved and this method can avoid getting into the local optimum
實驗表明，該演算法能避免陷入局部最優值，配準結果精度達到亞像素級。 -
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。 -
Traditionally, we used c - means method, clusters similar data instances together into clusters and distance metrics are used on clusters to determine what is an anomaly. but there is some disadvantages in this method, such as the results of the cluster is sensitive to the data input sequence, furthermore, it is a local optimum algorithm
聚類分析是數據挖掘技術中的關鍵技術，但傳統的c ?均值聚類演算法對入侵檢測數據進行處理有很多不盡人意的地方，如該聚類演算法是局部尋優演算法，聚類的結果對數據輸入順序比較敏感等。 -
Ga is less prone to converge to a local optimum even when the initial guess is far away from the exact solution. in recent years, a growing number of researchers in the ga community turn to the study of real - coded genetic algorithm ( rga ) for its simplicity and efficiency, and the reason that a chromosome can be directly represented by real number
然後引入全局優化的搜索方法?遺傳演算法，由於實數遺傳演算法直接用實數表示遺傳個體，而微波成像演算法就是要得出目標的形狀函數，形狀函數的系數既為待求的變量，具有連續搜索空間，因此本文直接採用實數遺傳演算法。 -
In addition, it is useful in some places that contain harmful air and air is needed is needed to input. on the other hand, based on the theory of aerodynamics, the optimum structural factors for contra - rotating axial local fan are studied
根據軸流式通風機空氣動力學理論，在分析了普通軸流式通風機的結構對氣動力性能參數影響的基礎上，對對旋式軸流通風機的有關氣動力參數和結構參數進行了綜合優化分析研究。 -
On the basis of analyzing the aerodynamical property and the construction of usual axial fan, the aerodynamical property and the construction of contra - rotating axial local fan are studied in the paper. moreover, author has designed a kind of contra - rotating local fan, which has the characters of low noise, high efficiency, well aerodynamical performance, optimum structure, and large power
本文在分析了普通軸流式通風機的氣動力特徵和結構的基礎上，研究了對旋式軸流通風機的氣動力特性和結構特點，設計並製造出了一種風量大，風壓高，噪聲低，效率高，氣動性能好，體積小，結構新穎的2 30kw新型大功率對旋式軸流局部通風機樣機。 -
Based on orthogonal experimental avenue, dmm is manufactured by local po, sa, and phosphorus slag flying ash, yellow slag and ect. and formulate optimum mixture program and production technology requirement ; on basis of jcj70 - 90, physical mechanics property is quizzed, adopting chemical analysis, xrd, sem and so on, discuss composition and structure. the researchable result is that mixture program of dmm : a3b2cl ( cement 403 m2 / kg, phosphorus slag357 m2 / kg, activated agent 2 % ), after the condition of c / s1 : 4, adopting ordinary portland cement
採用正交試樣方法，用本地生產的普通硅酸鹽水泥、硫鋁酸鹽水泥、磷渣、粉煤灰、黃砂等原料配製抗滲干拌砂漿，確定最佳的配料方案和生產技術要求；按jcj70 ? 90 《建築砂漿基本性能測試方法》測定砂漿的各項物理力學性能；運用化學分析、 x衍射儀、掃描電鏡等測試手段，檢測配製砂漿的組成和結構。 -
Abstract : a new method, collaborative allocation ( ca ), is proposed to solve the large - scale optimum allocation problem in aircraft conceptual design. according to the characteristics of optimum allocation in aircraft conceptual design. the principle and mathematical model of ca are established. the optimum allocation problem is decomposed into one main optimization problem and several sub - optimization problems. a group of design requirements for subsystems are provided by the main system respectively, and the subsystems execute their own optimizations or further provide the detailed design requirements to the bottom components of aircraft, such as spars, ribs and skins, etc. the subsystems minimize the discrepancy between their own local variables and the corresponding allocated values, and then return the optimization results to main optimization. the main optimization is performed to reallocate the design requirements for improving the integration performance and progressing toward the compatibilities among subsystems. ca provides the general optimum allocation architecture and is easy to be carried out. furthermore, the concurrent computation can also be realized. two examples of optimum reliability allocation are used to describe the implementation procedure of ca for two - level allocation and three - level allocation respectively, and to validate preliminarily its correctness and effectiveness. it is shown that the developed method can be successfully used in optimum allocation of design requirements. then taking weight requirement allocation as example, the mathematical model and solution procedure for collaborative allocation of design requirements in aircraft conceptual design are briefly depicted
文摘:探討了一種新的設計指標最優分配方法- -協同分配法，用於處理飛機頂層設計中的大規模設計指標最優分配問題.分析了飛機頂層設計中的設計指標最優分配特徵，據此給出了協同法的原理並建立了數學模型.協同法按設計指標分配關系將最優分配問題分解為主系統優化和子系統優化，主優化對子系統設計指標進行最優分配，子優化以最小化分配設計指標值與期望設計指標值之間的差異為目標，進行子系統最優設計，或對底層元件（如飛機翼梁、翼肋和翼盒等）進行設計指標最優分配，並把最優解信息反饋給主優化.主優化通過子優化最優解信息構成的一致性約束協調分配量，提高系統整體性能，並重新給出分配方案.主系統與子系統反復協調，直到得到設計指標最優分配方案.兩層可靠度指標分配算例初步驗證了本文方法的正確性與可行性，三層可靠度指標分配算例證明了本文方法的有效性.最後，以重量指標分配為例，簡要敘述了針對飛機頂層設計中設計指標協同分配的數學模型和求解思路 -
Aim at the neural network get local optimum easily, the speed of convergence is slow, the quantity of training excessive and so on. this paper adopted the ga optimize the nn firstly, and then the nn algorithm
針對神經網路易出現局部最優點、收斂速度慢和訓練量過大等問題，本文先利用遺傳演算法對神經網路進行優化后，再執行神經網路的演算法步驟。 -
That they are easy to fall into a local optimum is the shortcoming of conventional optimization methods
傳統的優化方法，即所謂的確定性優化方法的突出缺陷是容易陷入局部最優解。 -
Experimental results verify the theoretical performance analysis and show that the performance of the local optimum detector is better than that of the linear correlate detector
實驗驗證了圖像水印檢測理論的有效性以及本文的局部優化檢測器性能的優良性。 -
The basic principle of cpso algorithm is that chaos initialization is adopted to improve individual quality and chaos perturbation is utilized to avoid the search being trapped in local optimum
該演算法的思想是採用混沌初始化進行改善個體質量和利用混沌擾動避免搜索過程陷入局部極值。 -
In the hybrid approach, based on the global search ability, discrete artificial immune algorithm is used to search the optimal solution and simulated annealing is applied to avoid getting into a local optimum
該方法利用離散人工免疫演算法的全局搜索能力來尋找全局最優解，利用模擬退火方法來避免陷入局部最優。 -
The last one is delay - bound constraint multicast routing algorithm based on clone selection and ant colony algorithm, it overcomes the drawbacks of slow convergence rate and easily falling into the local optimum
第三種演算法是基於克隆蟻群的組播路由演算法，該演算法克服了蟻群演算法收斂速度慢，且易陷入局部最優的缺陷。 -
Premature convergence is still the prominent problem in genetic algorithms. some excellent individuals or genes are lost due to premature convergence, which causes local optimum. a parameter adaptive genetic algorithm based on the entropy estimating is advanced in this paper
自適應遺傳演算法的控制參數可以根據個體的適應度大小進行自適應調整，體現了生物進化中「優勝劣汰」的思想，使其收斂速度較基本遺傳演算法有了很大提高。 -
Considering there exists such problems with traditional optimization method that solving process is complicated and only local optimum solution is acquired, genetic algorithm and direct search toolbox of matlab software is adopted to solve the optimization model and optimization process is simplified and global optimum solution is found
由於傳統的優化方法存在著求解過程復雜和尋優過程容易陷入局部最優解的問題，故應用matlab遺傳演算法工具箱尋求問題最優解，使求解過程得到簡化，能可靠地獲得全局最優解。 -
In the third part, in order to prevent shortcoming of the entrapment in local optimum of ordinary bp and the premature convergence of basic ga, a new algorithm which combines bp with ga is presented, which is used to detect the rotor winding short
神經網路採用bp演算法易陷入局部最優，而基本的ga易出現早熟，將bp和ga相結合用於故障診斷，並通過算例驗證了該方法的可行性。 -
( 2 ) considering the problem that genetic algorithm running result is affected greatly by the initial parameter and it ’ s easy to trap in local optimum, based on its mathematic theory, studied deeply on self - adaptive genetic algorithm, presented a new viewpoint - - superiority inheritance, furthermore, designed adaptive genetic algorithm based on superiority inheritance. the experiment showed that this algorithm could find the global best solution, and had strongly global hunting capability. it is prior to traditional adaptive genetic algorithms on aspects of accuracy, stability, and repeatability etc. it was applied in fast image
（ 2 ）針對遺傳演算法的初始參數對演算法結果影響較大和易陷入局部最優的問題，在闡述基本數學理論模式定理的基礎上，對自適應遺傳演算法進行了深入的研究，提出了一種優勢遺傳的新觀點，由此設計了基於優勢遺傳的自適應遺傳演算法，通過實驗表明，該演算法能夠達到理想全局最優解，有很強的全局搜索能力，在準確性、穩定性和重復性方面優于當前自適應遺傳演算法。 -
In this paper, an improved genetic algorithm ( ga ) was applied to the design of high performance e - plane waveguide filters at the first time. for dealing with the shortcoming of ga as low efficiency in local optimum searching, the idea based on parallel genetic algorithm ( pga ) known as separate local optimization was presented. by separating the whole population into sub - populations, and adding a new operator known as crossover between two sub - population, the new method can provide as 2 3 times quickly as traditional ga. all numerical examinations illustrated the high convergence speed and good global searching of the new algorithm, and proved the validity of it
由於遺傳演算法表現出良好的全局搜索性能，因此本文將其應用於高性能e面波導濾波器的設計中.針對傳統遺傳演算法所存在的局部搜索能力差的缺點，本文在并行遺傳演算法的基礎上，通過將原有群體劃分為多個子群體，利用多個子群進行局部極值點的搜索，並利用群間遷徙，使改進后的演算法收斂速度平均提高了2 3倍.數值實驗表明演算法具有較快的收斂速度和較好的全局搜索性能，證明了演算法的有效性
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