heuristic searching 中文意思是什麼
heuristic searching
解釋
試探檢索-
Simulated annealing algorithm is a kind of heuristic monte carlo method. in the course of solve the optimum problem, it conquer the blindfold searching mechanism of normal monte carlo method, and based on a appointed theory to guides search, so it can ensure a successful search
模擬退火方法是一種啟發式蒙特卡羅法，在解決優化的問題中，它克服了常規蒙特卡羅方法盲目的隨機搜索機制，而是在一定的理論指導下搜索，故能保證搜索成功。 -
In this paper, a genetic algorithm was presented to solve the problem of the searching of the optimal coalition structure. we designd one - dimension chromosome coding structure and the corresponding improved uniformity crossover operator and the heuristic mutation operator
我們給出了一種求解最佳聯盟結構的gas演算法，設計出了一種簡單的一維自然數染色體編碼結構和改進的均勻交叉運算元以及啟發式變異運算元。 -
To better elucidate the following critical problems - - building the rational mathematics model and searching the effective algorithms, this paper sets forth the basis of algorithms and heuristic algorithm. meanwhile it compendiously introduces the main principles of genetic algorithm and the stimulated annealing algorithm, principal parameters during the course of solving problems and vertex coloring theory
為了更好地說明下文所要解決的關鍵問題? ?建立合理的數學模型和尋找有效可行的演算法，本文闡述了演算法和啟發式演算法的理論基礎，並扼要地介紹了遺傳演算法、模擬退火演算法的主要思想和在解題過程中應用的重要參數，以及圖的著色理論；及其在作業計劃編制中應用的可能性。 -
The main method of the algorithm is using heuristic searching on dynamic network on the basis of all the flights " priority been determined
該演算法解決改航問題的基本方法是在確定航班優先級的基礎上在動態網路流模型中運用啟發式搜索法求得最優解。 -
This thesis, using the heuristic searching algorithm and the rolling planning strategy, mainly focuses on the study of the route planning of mobile robots in complicated environment and its relevant problems, especially the motion planning in unknown static and dynamic environment
本文主要針對復雜環境下移動機器人路徑規劃及其相關的問題展開了研究，著重研究了靜態未知環境下和動態未知環境下機器人路徑規劃問題，採用啟發式搜索演算法以及滾動規劃策略。 -
A heuristic hybrid algorithm called chaotic searching simulated annealing is here proposed, which is mixed by chaotic searching and simulated annealing to evolve balanced boolean functions satisfying high nonlinearity
摘要利用混沌動力系統的良好特性，把它引入傳統的模擬退火中，提出一種稱為混沌搜索模擬退火的新啟發式演算法，用於設計高度非線性平衡布爾函數。 -
In the algorithm, a way of graphical depth - first searching was used for tasks grouping, and then a series of heuristic rules were applied to select the proper group for assignment
該演算法利用圖深度優先搜索方法，將任務進行歸組，然後運用一系列啟發式規則對組進行選擇分配。 -
The csbark algorithm computes the cs of an attribute according to the weighted feature difference and value difference, then searching the minimal reduction of attributes using cs as heuristic information. the cs value not only represents the importance of a condition attribute, but also reveals its relationships with other attributes. the minimal rules set algorithm depends on the value core and integrates the logic relation in the reasoning
前者利用微差距離計算屬性的加權特徵差、利用互信息計算值差，從而求出各條件屬性的上下文敏感度，該值既反映了對應的條件屬性的重要性，同時還反映了該屬性與其它屬性的關聯程度；後者利用值核在生成規則過程中的重要作用，結合推理過程中的邏輯關系求解最小決策規則集，並給出了規則的評價指標支持度和信度的計算方法。 -
Thus, according to mechanics of dealing with stochastic phenomena in programming theory, multi - objective stochastic programming model is developed to dispose parameter uncertainty. as a heuristic monte carlo approach with powerful global searching, genetic algorithm based on stochastic programming is utilized
為了更好的處理實際生產中參數的不確定性，根據數學規劃論中處理隨機現象的機理，建立多目標隨機規劃模型，模型求解採用基於隨機規劃的遺傳演算法。 -
In translation searching process, many ebmt systems can only rely on a heuristic guidance which is given by human. therefore that process will not be objective and always lean much on the intuition of system developer and may be overfitting to a special domain
但是，由於在ebmt系統進行譯文搜索的過程中往往只能依靠人為設定的啟發式函數進行指導，對人為因素的依賴較大，很容易造成對某個限定領域特點的過度擬合。 -
Until now, this type of combinatorial problems are usually solved by linear programming, interger programming, analytical methods, heuristic methods and so on. but these methods have many disadvantages such as. low searching efficiency, converging slowly, converging to local optimization solution easily and not converging
本文針對目前對接入網優化存在著缺乏有效演算法的現狀，確定了採用高效的啟發式搜索演算法? ?遺傳演算法作為優化演算法，著重解決了遺傳運算元的設計和實現問題，並對演算法進行了改進，取得了很好的效果。 -
This paper analyzed the logic in detail and realized the logic automatically with the method of heuristic search based on width - first searching
本文詳細分析了防誤操作閉鎖邏輯的特點，並用啟發式搜索和寬度優先搜索相結合的搜索方法實現了該邏輯的自動生成。 -
Experiments show that our algorithms were better than simulated annealing algorithm or other heuristic searching algorithms. finally, we make the networks visualized
實驗表明，本文的演算法精度高於單純運用模擬退火或者其它啟發式演算法的效能。
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