本文研究了启发式搜索中加权技术。
This paper studies the weighting techniques in heuristic search.
用启发式搜索方法自动获取最佳分段数。
The number of segments is automatically computed due to the inherent heuristic searching.
本文给出一个高效的启发式搜索算法和有关证明。
This paper presents an efficient heuristic searching algorithm, along with relative proof.
在该系统中，使用了扩充的有限自动机和启发式搜索等技术。
The system includes a extended finite automata and heuristic search technique.
本文提出了一种基于启发式搜索的感知图规划算法的新算法。
This paper makes research on a kind of complex planning problems—uncertain planning problems.
详细研究了启发式搜索算法的产生、构造方法、基本类型等几个方面。
The study includes the generation, construction methods and basic types of heuristics search algorithms.
推理机设计采用启发式搜索，结合正向、反向及双向推理建立专家系统。
The elicitation search and integrated forward direction, reverse direction and bidirectional reasoning was adopted to set up expert system in reasoning machine design.
算例的结果证明了本文所提出的模型的正确性和启发式搜索策略的高效性。
The case result verifies the correctness of the model and the effectiveness of the search strategy.
最后，采用启发式搜索方法连接视频对象轮廓边缘点，进而提取出视频对象。
Finally, we applied heuristic search method to link video object contour's edge points, sequentially extracted video object.
该算法利用网格来构造搜索图，并对它进行启发式搜索来获得运动指令序列。
This algorithm utilizes the grid to construct the search graph, which is heuristically searched to obtain the movement instruction series.
定向搜索是一种启发式搜索算法，它是对减少内存需求的最佳优先搜索的优化算法。
Beam search is a heuristic search algorithm that is an optimization of best-first search that reduces its memory requirement.
粒子群优化(PSO)算法是一种基于群体智能的启发式搜索方法，应用领域很广。
Particle swarm optimization (PSO) is a heuristic search method based on swarm intelligence, and has been widely used to solve various problems in engineering fields.
基于从该位置管理方案获取的全网拓扑信息，采用启发式搜索算法实现最优地理路由。
Based on the whole network topology information obtained by the K-hops clustering location management scheme, it adopts a heuristic search algorithm to realize optimal geo-routing.
针对该问题，提出基于启发式搜索算法的查询优化方案并成功应用于原有的查询系统。
In order to improve the search efficiency, this paper presents an optimization solution based on heuristic search algorithm and applies it in the original system successfully.
这种方法的主要特征是正反馈、分布式计算以及富有建设性的贪婪启发式搜索的运用。
The main characteristics of this method are positive feedback, distributed computation, and the use of a constructive greedy heuristic.
通过启发式搜索算法使增加的额外约束得到最大化满足，从而寻找到符合用户意图的解。
The heuristic searching algorithm maximizes the fitness of the additional constraint set, thereby reaches the final result that can satisfy the user's expectation.
基于生物激励神经网络、滚动窗口和启发式搜索，提出了一种新的完全遍历路径规划方法。
A new approach to complete coverage path planning for mobile robots, which integrates biologically inspired neural network, rolling window and heuristic searching, is presented.
附加的启发式搜索计算当前位置进行的比较的次数，然后从“良好后缀”移动中减去这个数。
The additional heuristic calculates the number of comparisons made in the current position and subtracts that from the GOOD SUFFIX shift.
该方法给出冲突矩阵表示对象流入流水线的限制，通过启发式搜索寻找面向目标优化的调度策略。
The method gives out the presentation be constrained to objects into pipeline by using collision matrix, and findsout scheduling model with goal-oriented optimization by heuristic search.
这个算法以布线平面上的障碍信息为基础，采用了人工智能中的启发式搜索技术，时空效率很高。
On the basis of obstruction information on a routing plane, this router has a high efficiency in time and and space by using the heuristic technique in artificial intelligence.
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。
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.
该系统改进了信息搜索引擎，实现了多线程分布启发式搜索策略，并提出了目标文本模糊搜索空间模型。
A search engine of document information is improved and a heuristic search strategy with multithreading and distributing is implemented. It introduces fuzzy retrieval model on the object documents.
在普通的文本和二进制文件中重复的字符序列是很常见的，所以需要有附加的启发式搜索来处理这种情况。
The is the need to produce an addition heuristic to handle the occurrence of repeated sequences of characters which is common in both plain text and binary files.
特征子集选择问题是机器学习的重要问题。而最优特征子集的选择是NP困难问题，因此需要启发式搜索指导求解。
The feature subset selection is an important problem in machine learning, but the optimal feature subset selection is proves to be a NP hard one.
本文详细分析了防误操作闭锁逻辑的特点，并用启发式搜索和宽度优先搜索相结合的搜索方法实现了该逻辑的自动生成。
This paper analyzed the logic in detail and realized the logic automatically with the method of heuristic search based on width-first searching.
在本文中，提出使用人工智能中的启发式搜索来获取特定的信息，这样可以极大地减少遍历的链接数量，使被访问到的链接尽量地指向有用的信息。
In this article we use the heuristic search to get the specific information. This can reduce the links largely and make the links visited by WebCrawler point to useful information.
通过使用所有可搜索部分的子集，可以从搜索中获得所需的结果，并向用户提供所需的结果，而不必采用启发式方法。
By using a subset of all the text-searchable parts, you can obtain the desired result from search and present to the user the expected result, without needing to take an heuristic approach.
选择搜索解决方案时要使用的启发式分支。
Pick a branch heuristic to use while searching for a solution.
选择搜索解决方案时要使用的启发式分支。
Pick a branch heuristic to use while searching for a solution.
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