FESAEI: a fuzzy rule-based expert system for the assessment of environmental impacts

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Title: FESAEI: a fuzzy rule-based expert system for the assessment of environmental impacts
Authors: Tomás Sánchez, José Enrique de | Tomás Marín, Sergio de | Peiro, Victoriano
Research Group/s: Ecología Espacial y del Paisaje (EEP)
Center, Department or Service: Universidad de Alicante. Departamento de Ecología
Keywords: Fuzzy logic | Environmental impact assessment | Fuzzy inference | Crisp numbers
Knowledge Area: Ecología
Issue Date: Sep-2018
Publisher: Springer International Publishing
Citation: Environmental Monitoring and Assessment. 2018, 190:528. doi:10.1007/s10661-018-6907-9
Abstract: Currently, the method mostly used by practitioners of environmental impact assessment (EIA) is the “crisp numbers” method. Nevertheless, this arithmetic method is far away of giving correct values due to its rigidity and the lack of consideration of important aspects as the imprecision and incompleteness of data and the uncertainty that usually pervade our knowledge of environment. A more flexible model that considers uncertainty of knowledge and imprecision of data is necessary. Among the different approaches for the assessment of environmental impacts, the fuzzy logic-based one takes account of the aspects said before; this was our primal assumption. On this paper, we explain the structure and performance of the fuzzy rule-based inference model we built, how it works, and what can be obtained when used to assess environmental impacts. Our fuzzy expert system for the assessment of environmental impacts (FESAEI) is built as the combination of five subsystems, using a total of 120 fuzzy rules, and being the output and input for the next subsystem. We assessed the parameters of rarity, robustness, quality, recoverability, intrinsic value, extension, intensity, persistence, impact_character, cumulativeness, transmissivity, and impact prevalue in four subsystems. The fifth subsystem gives the definitive impact value corresponding to the impact type of “compatible,” “moderate,” “severe,” and “critical.” The model is verified and statistically validated. Weighted Cohen’s kappa shows an almost perfect concordance among experts and FESAEI’s evaluations.
URI: http://hdl.handle.net/10045/79234
ISSN: 0167-6369 (Print) | 1573-2959 (Online)
DOI: 10.1007/s10661-018-6907-9
Language: eng
Type: info:eu-repo/semantics/article
Rights: © Springer Nature Switzerland AG 2018
Peer Review: si
Publisher version: https://doi.org/10.1007/s10661-018-6907-9
Appears in Collections:INV - EEP - Artículos de Revistas

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