Most soil and water conservation facilities are located in remote areas, posing measurement difficulties for precision instruments. Therefore, visual inspection, which is advantageous because of its high speed, is the primary assessment method for such facilities. However, the degree of infrastructural damage subjectively assessed by various inspectors may vary. Therefore, to overcome the problem induced by inspectors’ subjectivity in assessing facilities, this study adopted the concept of fuzzy set theory to establish a soil and water conservation facility assessment model that can define the membership functions of specific semantic ranges. This study applied semantics to infer current facility conditions, which were classified into various levels. The results can serve as a basis for managerial decisions regarding soil and water conservation facilities or for maintenance applications

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