Fuzzy logic modeling of causal relationships-case study: Reasoning about construction performance

被引：0

作者：

Dissanayake, GM ^{[1
]}

Chen, L ^{[1
]}

Pedrycz, W ^{[1
]}

Fayek, AR ^{[1
]}

Russell, AD ^{[1
]}

机构：

[1] Univ Alberta, Dept Civil & Environm Engn, Edmonton, AB T6G 2G7, Canada

来源：

NAFIPS 2004: ANNUAL MEETING OF THE NORTH AMERICAN FUZZY INFORMATION PROCESSING SOCIETY, VOLS 1AND 2: FUZZY SETS IN THE HEART OF THE CANADIAN ROCKIES | 2004年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Described in this paper is a logic-modeling framework, based on fuzzy neural networks (FNNs) to identify causal relationships among variables. A case study is presented from the industrial construction domain to demonstrate the capability of the proposed system in finding plausible explanations of observed performance failures.

引用

页码：605 / 610

页数：6

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