Fuzzy rule-based models for decision support in ecosystem management

被引:207
作者
Adriaenssens, V
De Baets, B
Goethals, PLM
De Pauw, N
机构
[1] Univ Ghent, Dept Appl Ecol & Environm Biol, Lab Environm Toxicol & Aquat Ecol, B-9000 Ghent, Belgium
[2] Univ Ghent, Dept Appl Math Biometr & Proc Control, B-9000 Ghent, Belgium
关键词
fuzzy logic; ecology; uncertainty; prediction; modelling;
D O I
10.1016/S0048-9697(03)00433-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
To facilitate decision support in the ecosystem management, ecological expertise and site-specific data need to be integrated. Fuzzy logic can deal with highly variable, linguistic, vague and uncertain data or knowledge and, therefore, has the ability to allow for a logical, reliable and transparent information stream from data collection down to data usage in decision-making. Several environmental applications already implicate the use of fuzzy logic. Most of these applications have been set up by trial and error and are mainly limited to the domain of environmental assessment. In this article, applications of fuzzy logic for decision support in ecosystem management are reviewed and assessed, with an emphasis on rule-based models. In particular, the identification, optimisation, validation, the interpretability and uncertainty aspects of fuzzy rule-based models for decision support in ecosystem management are discussed. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 12
页数:12
相关论文
共 82 条
[1]  
ADRIAENSSENS V, IN PRESS ECOL MODEL
[2]   Describing benthic impacts of fish farming with fuzzy sets: theoretical background and analytic methods [J].
Angel, DL ;
Krost, P ;
Silvert, WL .
JOURNAL OF APPLIED ICHTHYOLOGY-ZEITSCHRIFT FUR ANGEWANDTE ICHTHYOLOGIE, 1998, 14 (1-2) :1-8
[3]  
[Anonymous], 1998, Fuzzy Modelling for Control
[4]   Determination of fuzzy logic membership functions using genetic algorithms [J].
Arslan, A ;
Kaya, M .
FUZZY SETS AND SYSTEMS, 2001, 118 (02) :297-306
[5]  
BAPTIST M, IN PRESS FRESHWATER
[6]  
Bardossy A., 1995, Fuzzy Rule-Based Modeling with applications to Geophysical, Biological and Engineering Systems
[7]   A fuzzy knowledge-based model of population dynamics of the Yellow-necked mouse (Apodemus flavicollis) in a beech forest [J].
Bock, W ;
Salski, A .
ECOLOGICAL MODELLING, 1998, 108 (1-3) :155-161
[8]  
BODENHOFER U, IN PRESS STUDIES FUZ
[9]  
Borri D., 1998, Computers, Environment and Urban Systems, V22, P299, DOI 10.1016/S0198-9715(98)00045-3
[10]   ECOSYSTEM ANALYSIS USING FUZZY SET-THEORY [J].
BOSSERMAN, RW ;
RAGADE, RK .
ECOLOGICAL MODELLING, 1982, 16 (2-4) :191-208