03 خرداد 1403
مهيار يوسفي

مهیار یوسفی

مرتبه علمی: دانشیار
نشانی:
تحصیلات: دکترای تخصصی / مهندسی معدن-اکتشافات معدن
تلفن:
دانشکده: دانشکده فنی مهندسی

مشخصات پژوهش

عنوان
Particle Swarm Optimization Algorithm for Neuro-Fuzzy Prospectivity Analysis Using Continuously Weighted Spatial Exploration Data
نوع پژوهش مقاله چاپ شده
کلیدواژه‌ها
Continuous weighting, Exploration targeting, Neuro-fuzzy, Particle swarm optimization algorithm.
سال
2019
مجله Natural Resources Research
پژوهشگران مهیار یوسفی

چکیده

Classification of spatial exploration data for exploration targeting using neuro-fuzzy models means that the many spatial values have to be simplified and assigned to a few classes. The simplification of complex geological information, which illustrates a high degree of variability, results in overly simplistic models based on the presumption of homogeneous earth. However, such an assumption is not valid. In this paper, we illustrate the superiority of using continuously weighted spatial evidence values compared to discretely weighted evidence data, and how continuously weighted spatial evidence values can increase the efficiency of neuro-fuzzy exploration targeting models. The results of this study demonstrate that neurofuzzy targeting model generated with continuously weighted spatial evidence values is superior to that of the neuro-fuzzy model generated with discretely weighted exploration evidence data.