Keyvan Habibi - School of Engineering, Department of Civil and Environment Engineering, Shiraz University,Shiraz, Iran
Seyyed Hosein Afzali - School of Engineering, Department of Civil and Environment Engineering, Shiraz University,Shiraz, Iran

The most prevalent techniques based on policy demarcation are inherently arbitrary,although screening is a crucial stage in environmental impact assessment (EIA). A caseby-case approach can be difficult, time-consuming, and costly. This work proposes a hybrid approach that is computational intelligence based on a Takagi-Sugeno-Kang fuzzyrule-based system (TSK-FRBS) that combines data-driven and expert knowledge, with the goal of evaluating its capacity to facilitate case-by-case screening in project assessment. A dataset comprising assessment characteristics of highway construction was made accessible for empirical research by a Brazilian environmental protectionorganization (EPA). According to the confusion matrix, a solution based on fuzzy modeling might handle this complexity, resulting in nearly complete agreement amongstEPA specialists' categorization. Consequently, the hybrid fuzzy inference system might be considered a suitable addition to a project review on a case-by-case basis.

environmental impact assessment, screening, TSK-FRBS, fuzzy, neural network