基于禁忌搜索算法的VLSI布局

将禁忌搜索算法应用于VLSI门阵列的布局问题，建立了以总线长度和通道拥挤度的布局目标函数，用禁忌搜索算法求解目标函数的最小值，通过实验仿真，将本算法和遗传算法进行了比较，结果表明不论在解的质量和收敛速度方面，禁忌搜索算法优于遗传算法。     

Web Discovery and Filtering Based on Textual Relevance Feedback Learning

We develop a new approach for Web information discovery and filtering. Our system, called WID, allows the user to specify long-term information needs by means of various topic profile specifications. An entire example page or an index page can be accepted as input for the discovery. It makes use of a simulated annealing algorithm to automatically explore new Web pages. Simulated annealing algorithms possess some favorable properties to fulfill the discovery objectives. Information retrieval techniques are adopted to evaluate the content-based relevance of each page being explored. The hyperlink information, in addition to the textual context, is considered in the relevance score evaluation of a Web page. WID allows users to provide three forms of the relevance feedback model, namely, the positive page feedback, the negative page feedback, and the positive keyword feedback. The system is domain independent and does not rely on any prior knowledge or information about the Web content. Extensive experiments have been conducted to demonstrate the effectiveness of the discovery performance achieved by WID.     

A hybrid computational strategy for identification of structural parameters

By identifying parameters such as stiffness values of a structural system, the numerical model can be updated to give more accurate response prediction or to monitor the state of the structure. Considerable progress has been made in this subject area, but most research works have considered only small systems. A major challenge lies in obtaining good identification results for systems with many unknown parameters. In this study, a non-classical approach is adopted involving the use of genetic algorithms (GA). Nevertheless, direct application of GA does not necessarily work, particularly with regards to computational efficiency in fine-tuning when the solution approaches the optimal value. A hybrid computational strategy is thus proposed, combining GA with a compatible local search operator. Two hybrid methods are formulated and illustrated by numerical simulation studies to perform significantly better than the GA method without local search. A fairly large structural system with 52 unknown parameters is identified with good results, taking into consideration the effects of incomplete measurement and noisy data.     

A fast and compact elimination method of empty elements from a double‐array structure

A double‐array is a well‐known data structure to implement the trie. However, the space efficiency of the double‐array degrades with the number of key deletions because the double‐array keeps empty elements produced by the key deletion. This paper presents a fast and compact elimination method of empty elements using properties of the trie nodes that have no siblings. The present elimination method is implemented by C language. From simulation results for large sets of keys, the present elimination method is about 30–330 times faster than the conventional elimination method and maintains high space efficiency. Copyright © 2003 John Wiley & Sons, Ltd.     

Ant colony search algorithms for optimal polygonal approximation of plane curves

This paper presents a new polygonal approximation method using ant colony search algorithm. The problem is represented by a directed graph such that the objective of the original problem becomes to find the shortest closed circuit on the graph under the problem-specific constraints. A number of artificial ants are distributed on the graph and communicate with one another through the pheromone trails which are a form of the long-term memory guiding the future exploration of the graph. The important properties of the proposed method are thoroughly investigated. The performance of the proposed method as compared to those of the genetic-based and the tabu search-based approaches is very promising.     

一个基于关联规则的Web信息检索模型

针对Web信息检索系统在大数据量下的数据存储，数据调度与工作的效率问题，分析了数据挖掘在Internet信息检索中的运用。提出了一个基于关联规则的Web信息检索模型，并以逻辑层次、服务域与数据路由为中心，输出了这个模型的结构、算法与设计思想。     

分布式搜索引擎的设计与实现

在一个分布各地的网站群组成的大系统中，不设立中心数据库的情况下，各网站对等协调工作，实现数据库级共享与搜索是一个难题。文中阐述了用Web Service技术实现分布式搜索的基本原理，并对Web Service代理模式、异地数据存取、大结果集处理、查询数据本地化等关键技术进行了详细介绍。     

数据库通用索引树GiST的研究

介绍一种支持可扩展数据类型及查询集的索引结构——通用索引树GiST，阐述了它的原理和实现方法。着重讨论了GiST的同步控制问题，对扩展链接技术和混合锁技术作了改进。     

态势估计的目标编群问题研究

Problems about target classification in situation assessment are analyzed. This paper presents a synthetic method for fulfilling target classification by using the nearest-neighbor method and field knowledge. The graphical structure formed by target classification is shown by the adjacency list. Based on the structure, breadth-first search algorithm is used for the implementation of dynamic maintenance. The output of target classification is helpful to de-termine the interaction among situation elements, thus interprets actions related to problem field.     

An interactive agent-based system for concept-based web search

Search engines are useful tools in looking for information from the Internet. However, due to the difficulties of specifying appropriate queries and the problems of keyword-based similarity ranking presently encountered by search engines, general users are still not satisfied with the results retrieved. To remedy the above difficulties and problems, in this paper we present a multi-agent framework in which an interactive approach is proposed to iteratively collect a user's feedback from the pages he has identified. By analyzing the pages gathered, the system can then gradually formulate queries to efficiently describe the content a user is looking for. In our framework, the evolution strategies are employed to evolve critical feature words for concept modeling in query formulation. The experimental results show that the framework developed is efficient and useful to enhance the quality of web search, and the concept-based semantic search can thus be achieved.