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 heuristic search algorithms 启发式搜索算法(9)启发式搜索策略(1)
 启发式搜索算法
 Learning Heuristic Search Algorithms Learning-IDA & Learning-PIDA Based on Iterative-Deepening 基于反复加深的学习式启发式搜索算法Learning-IDA和Learning-PIDA 短句来源 Parallel Heuristic Search Algorithms PNAO and PBHAO 并行启发式搜索算法PANO和PBHAO 短句来源 Iterative-Deepening Fuzzy Heuristic Search Algorithms and Their Learning Investigation 基于反复加深的模糊启发式搜索算法及其学习性质研究 短句来源 In this paper, the formula of heuristic search algorithms is generalized,and a weighted heuristic QoS routing selection algorithm based on cost and delay is presented. 本文推广启发式搜索算法公式 ,提出了一种基于费用和延迟的加权启发式QoS路由选择算法。 短句来源 Based on iterative-deepening and modifying heuristic evaluation function dynamically,fuzzy heuristic search algorithms FIDA and Improved-FIDA are presented. The learning algorithm LFIDA is also presented to overcome the difficulty to design fuzzy heuristic evaluation function h (n) 本文基于反复加深和动态修改启发式估价函数这一机制，提出了模糊启发式搜索算法FIDA和Improved－FIDA．针对模糊启发式估价函数通常难以设计这一问题，提出了可用于模糊启发式估价函数学习的学习算法LFIDA． 短句来源 更多
 启发式搜索策略
 Three heuristic search algorithms are proposed: (1) Maximum Likelihood First (MLF) search; 本文提出了三种启发式搜索策略:(1)最大似然优先搜索(MLF); 短句来源
 “heuristic search algorithms”译为未确定词的双语例句
 The Genetic algorithms, Simulated Annealing algorithms and Heuristic search algorithms are used in operation scheduling. 把遗传算法、模拟退火算法、随机搜索算法应用于作业计划调度优化中。 短句来源 Ant colony algorithm is a class of heuristic search algorithms that have been successfully applied to solving NP hard problems. 蚁群算法作为一类启发式算法，已经成功地应用于求解TSP问题。 短句来源

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 heuristic search algorithms
 For the general case (k>amp;gt;1), which is NP-hard, we review heuristic search algorithms including local search, iterative local search, and simulated annealing. For the general case (k >amp;gt; 1), which is NP-hard, we review heuristic search algorithms including local search, iterative local search, and simulated annealing. The optimal heuristic search algorithms like CASS and CABOB proposed for solving the WDP take a lot of CPU time for solving large problem instances. Completeness and Admissibility for General Heuristic Search Algorithms-A Theoretical Study: Basic Concepts and Proofs This paper compares three heuristic search algorithms: genetic algorithm (GA), simulated annealing (SA) and tabu search (TS), for hardware>amp;amp;#x2013;software partitioning. 更多
 This paper presents an efficient heuristic searching algorithm, along with relative proof. The advantage of this algorithm is that the searching time and space are not connected with the size of the maze space, but with the relative position between the obstacles only. If we neglect some secondary factors, the searching time and space will only be the linear functions of the optimal path. 本文给出一个高效的启发式搜索算法和有关证明。本算法的优点是搜索的时间和空间,与迷宫空间的大小无关,仅与障碍的相对位置有关。如果忽略一些次要的因素,搜索的时间和空间仅是最佳路径的线性函数。 Under certain hypothesis a heuristic search can be considered as a random sampling process. Thus, it is possible to transfer the statistical inference method to the heuristic search. Based on the idea above, in [1] -[4] we have incorporated some specific statistical inference method into heuristic searches, and obtained some new statistical heuristic search algorithms - SA, WSA etc. The characteristics and the details of the algorithms have also been discussed.In this paper we go further into the... Under certain hypothesis a heuristic search can be considered as a random sampling process. Thus, it is possible to transfer the statistical inference method to the heuristic search. Based on the idea above, in [1] -[4] we have incorporated some specific statistical inference method into heuristic searches, and obtained some new statistical heuristic search algorithms - SA, WSA etc. The characteristics and the details of the algorithms have also been discussed.In this paper we go further into the subject and discuss the combination of the two techniques over a wider range. 在一定的假设下,可以把启发式搜索看作一种随机取样的过程,从而可以把统计推断方法引进搜索。根据上述思想,我们在文[1—4]中,讨论了个别统计推断法与一般图(或树)搜索的结合,得到一些新的统计启发式搜索算法——如SA,WSA算法等,探讨了这类算法的优点及程序细节,本文将从理论上进一步阐述这一思想,并从更广泛的范围讨论这两种技术的结合问题。 This paper describes a new heuristic search algorithm with modifiable estimate.This algorithm uses the information gathered by node expansions to improve theheuristic estimate and so it keeps the so called‘consistency assumption’holding on thesearch tree constantly.The new algorithm is admissible and it reduces the worst casecomplexity of search from O(N~2)of algorithm B′(L.Méró,1984)to its O(N).(N isthe size of the searched graph.)In the other part of the paper,a comparison... This paper describes a new heuristic search algorithm with modifiable estimate.This algorithm uses the information gathered by node expansions to improve theheuristic estimate and so it keeps the so called‘consistency assumption’holding on thesearch tree constantly.The new algorithm is admissible and it reduces the worst casecomplexity of search from O(N~2)of algorithm B′(L.Méró,1984)to its O(N).(N isthe size of the searched graph.)In the other part of the paper,a comparison between algorithm B' and the newalgorithm is made. 本文描述了一个能够改善启发函数的启发式图搜索算法。它利用搜索过程中的信息,改动启发函数 h,保持搜索树上始终满足单调限制条件,使算法的最坏复杂度从 B′的 O(N~2)(L.Mér(?),1984)降为 O(N)。本文还证明了新算法的可采纳性、线性的复杂度,并同算法 B′作了性能比较。 << 更多相关文摘
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