【作者】 刘芳；

【导师】 林和；

【作者基本信息】 兰州大学 ， 计算机软件与理论， 2008， 硕士

【摘要】 随着人工智能技术的不断发展,机器学习、数据挖掘、粗糙集、证据理论等理论方法的不断深入和完善,使智能决策支持系统的体系结构和智能化程度得到了较大的提高。然而随着Internet的普及应用,人们所掌握信息数据数量的剧增,给决策支持提供了丰富的信息资源和方便的互动交流平台,也使得更多的专家可以参与决策。基于智能技术的决策系统研究已经成为当前一个热点研究领域。目前智能决策支持系统研究面临的主要问题之一为:越来越多半结构化、非结构化的、不确定的和相关的信息影响决策,决策专家很难凭借大脑的知识和经验准确、全面和快速地解决、分析信息,形成决策方案,而需要利用智能技术来辅助决策问题求解。本文在分析目前智能决策支持系统现状和存在问题基础上,将基于案例推理的技术与智能决策支持系统相结合,提出了基于CBR的智能决策支持系统,并在法律咨询领域得到实际应用。采用基于事例推理(CBR)的方法,对事例表示、检索推理及启发式学习进行了研究,建立了基于CBR的法律咨询系统,并进行了实例分析,证明了CBR预测的正确性。更多还原

【Abstract】 Recently, the architecture of intelligent decision support system has been greatly improved when artificial intelligence, including machine learning, data mining, rough set theory, Dumpster-Shafer theory and so on, was developed rapidly. At the end of last century and the very beginning of this century, we can acquire more and more information with the popularization of Internet, and Plenty of information and convenient communication platform are provided, and more experts can participate in decision activities. Research on intelligent decision theory and methods nowadays become an active research area.Currently, one of the key problems of research on intelligent decision theory and methods mainly include: a mass of semi-structured, unstructured, uncertain and correlative information will affect decision. Experts hardly exactly, roundly and fast grasp and analyze all information by the knowledge and experience buried in their mind, and need intelligent methods to help resolving decision Problem, and then form a decision opinion.This paper investigates and analyzes the research about intelligent decision support system, then discusses the application of CBR in IDSS and its key technique. This paper adopts the method Case-Based Reasoning(CBR), studies on the case reasoning、retrieval reasoning and learning, forwards the legal advisory system based on CBR, demonstrate of the CBR technology for successfully utilizing existing expertise to solve the complex problem.更多还原