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Item type:Publication, Algorithm based on grey clustering and Shannon entropy to assess landscape visual quality(IJETAE Publication House, 2022-01-01)Landscape assessment has been limited to methodologies with subjective and qualitative approaches, due to prevailing the concept of landscape as the perception of territory. In this work, the intrinsic visual quality of the landscape was evaluated using an algorithm based on grey clustering and Shannon entropy. The grey clustering method was used to determine the landscape visual quality, and Shannon entropy was applied to calculate wights of criteria used for evaluation. The case study was performed on mining project located in Cajamarca, Peru, where three landscape units were identified and four evaluation criteria were established, before and after the implementation of project. The results revealed that there is a notable effect of the change in landscape visual quality in three evaluated landscapes units. The criteria in order of evaluation were the intrinsic visual quality of the water, relief, vegetation cover, and artificial elements. Consequently, the method showed quantitative and qualitative results that could help the landscape assessment process to make better decisions regarding mining projects. Keywords—Grey clustering, Landscape visual quality, Mining project, Shannon entropy. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Artificial Intelligence Model Based on Grey Clustering to Access Quality of Industrial Hygiene: A Case Study in Peru(MDPI, 2023-03-01)Industrial hygiene is a preventive technique that tries to avoid professional illnesses and damage to health caused by several possible toxic agents. The purpose of this study is to simultaneously analyze different risk factors (body vibration, lighting, heat stress and noise), to obtain an overall risk assessment of these factors and to classify them on a scale of levels of Unacceptable, Not recommended or Acceptable. In this work, an artificial intelligence model based on the grey clustering method was applied to evaluate the quality of industrial hygiene. The grey clustering method was selected, as it enables the integration of objective factors related to hazards present in the workplace with subjective employee evaluations. A case study, in the three warehouses of a beer industry in Peru, was developed. The results obtained showed that the warehouses have an acceptable level of quality. These results could help industries to make decisions about conducting evaluations of the different occupational agents and determine whether the quality of hygiene represents a risk, as well as give certain recommendations with respect to the factors presented.