Presenter/Author Information

Shady Aly
Ivan Vrana

Keywords

fuzzy expert systems, outputs combination/aggregation, analytical hierarchy process, multiple parallel processing, binary group decision-making, consensus analysis

Start Date

1-7-2008 12:00 AM

Description

An Environmental Impact Assessment (EIA) is an assessment of the likely positive and/or negative influences an industrial project may have on the human health or environment. The assessment can have several dimensions like Air pollution impact, Noise/vibration impact, Water pollution impact, Ecological impact (Geological hazard impact and Endangered species impact), etc. Actually, there is a wide prevalence of situations of environmental impact and human risk assessment. This paper attempts to present a non-conventional solution for treating the complex EIA decision problem. It is typically a complex ill-structured decision making problem that involves: huge quantities of data to manipulate, low quality of data (uncertainty, measurement errors, missing data), different spatial and temporal scales (from seconds to years, from local to global), dynamic and stochastic behavior, and being at the crossroad among many disciplines/domains, and so many qualitative or subjective factors. In addition, the mentioned environmental dimensions often include non-homogenous subsets of input factors or variables. Consequently, in these situations, the decision-making problem becomes so complicated when we need to assess the overall environmental impact of a newly proposed or existing industrial project, specifically, we need to decide whether to adopt or proceed with the project. Such a binary, YES/NO, decision problem requires assessing the influences of all non-homogeneous inputs factors within the given relevant environmental dimensions or views. One way to obtain a reliable solution to such a complex, critical decision problem is to rely on the knowledge, heuristics, and experience of different expertise’s corresponding to each environmental dimension. In this paper, we propose a modular intelligent environmental decision support system that makes use of fuzzy logics and appropriate human expertise’s in rigorously assessing the impacts of the proposed or existing project on the surrounding environment or human health. The proposed system includes multiple fuzzy expert systems (FESs), each of which contains the homogenous and aggregated knowledge and expertise’s relevant to a one relevant environmental dimension. An objective numerical scale is established to assess the decision outputs of each individual system, expressing the degree of bias to “Positive” or “Negative” environmental impacts. Consequently, for a project to be adopted or accepted it must attain a combined or aggregate value in favor of the “Positive” impact outcome; otherwise the project will be rejected.

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Jul 1st, 12:00 AM

An Intelligent Decision Support System for Environmental Impact Assessment of Industrial/Agricultural Projects

An Environmental Impact Assessment (EIA) is an assessment of the likely positive and/or negative influences an industrial project may have on the human health or environment. The assessment can have several dimensions like Air pollution impact, Noise/vibration impact, Water pollution impact, Ecological impact (Geological hazard impact and Endangered species impact), etc. Actually, there is a wide prevalence of situations of environmental impact and human risk assessment. This paper attempts to present a non-conventional solution for treating the complex EIA decision problem. It is typically a complex ill-structured decision making problem that involves: huge quantities of data to manipulate, low quality of data (uncertainty, measurement errors, missing data), different spatial and temporal scales (from seconds to years, from local to global), dynamic and stochastic behavior, and being at the crossroad among many disciplines/domains, and so many qualitative or subjective factors. In addition, the mentioned environmental dimensions often include non-homogenous subsets of input factors or variables. Consequently, in these situations, the decision-making problem becomes so complicated when we need to assess the overall environmental impact of a newly proposed or existing industrial project, specifically, we need to decide whether to adopt or proceed with the project. Such a binary, YES/NO, decision problem requires assessing the influences of all non-homogeneous inputs factors within the given relevant environmental dimensions or views. One way to obtain a reliable solution to such a complex, critical decision problem is to rely on the knowledge, heuristics, and experience of different expertise’s corresponding to each environmental dimension. In this paper, we propose a modular intelligent environmental decision support system that makes use of fuzzy logics and appropriate human expertise’s in rigorously assessing the impacts of the proposed or existing project on the surrounding environment or human health. The proposed system includes multiple fuzzy expert systems (FESs), each of which contains the homogenous and aggregated knowledge and expertise’s relevant to a one relevant environmental dimension. An objective numerical scale is established to assess the decision outputs of each individual system, expressing the degree of bias to “Positive” or “Negative” environmental impacts. Consequently, for a project to be adopted or accepted it must attain a combined or aggregate value in favor of the “Positive” impact outcome; otherwise the project will be rejected.