WASTE-WATER TREATMENT SYSTEMS FROM CASE-BASED REASONING

被引：32

作者：

KROVVIDY, S

WEE, WG

机构：

[1] Department of Electrical and Computer Engineering, University of Cincinnati, Cincinnati, OH

来源：

MACHINE LEARNING | 1993年 / 10卷 / 03期

关键词：

HEURISTIC SEARCH; CASE-BASED REASONING; LEARNING; A-ASTERISK ALGORITHM;

D O I：

10.1023/A:1022643228269

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Case-Based Reasoning (CBR) is one of the emerging paradigms for designing intelligent systems. Preliminary studies indicate that the area is ripe for theoretical advances and innovative applications. Heuristic search is one of the most widely used techniques for obtaining optimal solutions to many real-world problems. We formulated the design of wastewater treatment systems as a heuristic search problem. In this article we identify some necessary properties of the heuristic search problems to be solved in the CBR paradigm. We designed a CBR system based on these observations and performed several experiments with the wastewater treatment problem. We compare the performance of the CBR system with the A* search algorithm.

引用

页码：341 / 363

页数：23

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