Environmental impact assessment using the evidential reasoning approach

We consider the situation where there are several alternatives for investing a quantity of money to achieve a set of objectives. The choice of which alternative to apply depends on how citizens and political representatives perceive that such objectives should be achieved. All citizens with the right to vote can express their preferences in the decision-making process. These preferences may be incomplete. Political representatives represent the citizens who have not taken part in the decision-making process. The weight corresponding to political representatives depends on the number of citizens that have intervened in the decision-making process. The methodology we propose needs the participants to specify for each alternative how they rate the different attributes and the relative importance of attributes. On the basis of this information an expected utility interval is output for each alternative. To do this, an evidential reasoning approach is applied. This approach improves the insightfulness and rationality of the decision-making process using a belief decision matrix for problem modeling and the Dempster-Shafer theory of evidence for attribute aggregation. Finally, we propose using the distances of each expected utility interval from the maximum and the minimum utilities to rank the alternative set. The basic idea is that an alternative is ranked first if its distance to the maximum utility is the smallest, and its distance to the minimum utility is the greatest. If only one of these conditions is satisfied, a distance ratio is then used.A. Mateos · A. Jiménez-Martín (B) · S. Ríos-Insua

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“…Both citizens and political rep- Wang et al (2006a), which analyses an environmental impact assessment problem, is shown in Table 1.…”

Section: Belief Decision Matrixmentioning

confidence: 99%

A Group Decision-Making Methodology with Incomplete Individual Beliefs Applied to e-Democracy

2014

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“…(8). The distance of the two values is represented by the absolute value u l i i    which denotes the largest fuzzy degree of the relative importance assigned to i e .…”

Section: Dempster-shafer's Evidence Theorymentioning

confidence: 99%

“…(9). The ER approach provides both the recursive 7 and analytical algorithms 8 to aggregate the assessments on multiple factors. Each of the algorithms has its own merits and can be applied in different decision situations.…”

Section: The Analytical Er Algorithmmentioning

confidence: 99%

“…2,3,[6][7][8] It uses a belief decision matrix (BDM) where each of its elements is a vector of belief degrees assessed to a set of evaluation grades in contrast with a conventional decision matrix where a single value is used to assess an alternative on each attribute in most other MADA methods. The ER approach is developed on the basis of the D-S evidence theory discussed in section 2.…”

Section: The Analytical Er Algorithmmentioning

confidence: 99%

“…The analytical ER algorithm is then proposed 8 based on the recursive algorithm and Yen's combination rule, 9 in which only one step of calculation is to be conducted to generate the overall performance. Secondly, the ER approach has been applied to many real world decision making issues, for instance, motorcycle and car evaluation, 2,3,7 large engineering product evaluation, 10 general cargo ship design, 11 supplier selection in VMI alliance circumstance, 12 contractor selection, 13 safety analysis, 14,15 self assessment, 16,17,18 environmental impact assessment, 8 pipeline leak detection, 19 strategic R&D project assessment, 20 new product development, 21 bridge condition assessment, 22 consumer preference prediction, 23 and so on. Thirdly, on the implementation of the ER approach, a window-based and graphically designed decision support software package called intelligent decision system (IDS) is developed on the basis of the ER approach.…”

Section: Introductionmentioning

confidence: 99%

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Group Evidential Reasoning Approach for MADA under Fuzziness and Uncertainties

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Multiple attribute decision analysis (MADA) problems often include both qualitative and quantitative attributes which may be either precise or inaccurate. The evidential reasoning (ER) approach is one of reliable and rational methods for dealing with MADA problems and can generate aggregated assessments from a variety of attributes. In many real world decision situations, accurate assessments are difficult to provide such as in group decision situations. Extensive research in dealing with imprecise or uncertain belief structures has been conducted on the basis of the ER approach, such as interval belief degrees, interval weights and interval uncertainty. In this paper, the weights of attributes and utilities of evaluation grades are considered to be fuzzy numbers for the ER approach. Fuzzy analytic hierarchy process (FAHP) is used for generating triangular fuzzy weights for attributes from a triangular fuzzy judgment matrix provided by an expert. The weighted arithmetic mean method is proposed to aggregate the triangular fuzzy weights of attributes from a group of experts. α-cut is then used to transform the combined triangular fuzzy weights to interval weights for the purpose of dealing with the fuzzy type of weight and utility in a consistent way. Several pairs of group evidential reasoning based nonlinear programming models are then designed to calculate the global fuzzy belief degrees and the overall expected interval utilities of each alternative with interval weights and interval utilities as constraints. A case study is conducted to show the validity and effectiveness of the proposed approach and sensitivity analysis is also conducted on interval weights generated by different α-cuts.

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A New Interpretable State‐of‐Health Assessment Model for Lithium‐Ion Batteries With Multidimensional Adaptability Optimization

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The state‐of‐health (SOH) assessment of lithium‐ion batteries is critical to the development and optimization of maintenance strategies. To ensure the accuracy of the assessment results, it must not only address a variety of uncertainties but also rationalize and transparently conduct the assessment process, as well as make the results interpretable and traceable. These requirements are necessary to ensure that the battery operates safely and steadily. As an interpretable modeling method, belief rule base (BRB) has been widely used in lithium‐ion battery SOH assessment. However, current BRB‐based models face two problems: (1) The initial reference values provided by experts often have limited accuracy due to complex internal chemistry. (2) The multidimensionality of the parameters in the interpretable optimization process and the differences in their properties should be fully considered. Therefore, this paper proposes a new SOH assessment model for lithium‐ion batteries based on an interpretable BRB with multidimensional adaptability optimization (IBRB‐mao). First, an interpretable knowledge and data dual‐driven reference value generation method is proposed to address the issue of imprecise reference values. Expert knowledge is maintained when generating reference values using this method. Second, two interpretable multidimensional constraint strategies are proposed to ensure interpretability in the optimization process. Finally, the NASA lithium‐ion battery data set is taken as a case study to validate the effectiveness of the proposed method.

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Environmental impact assessment using the evidential reasoning approach

Cited by 454 publications

References 116 publications

A Group Decision-Making Methodology with Incomplete Individual Beliefs Applied to e-Democracy

A Group Decision-Making Methodology with Incomplete Individual Beliefs Applied to e-Democracy

Group Evidential Reasoning Approach for MADA under Fuzziness and Uncertainties

A New Interpretable State‐of‐Health Assessment Model for Lithium‐Ion Batteries With Multidimensional Adaptability Optimization

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