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International Journal of Mining and Geo-Engineering، جلد ۵۲، شماره ۱، صفحات ۳۱-۳۶
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عنوان انگلیسی Utilization of Soft Computing for Evaluating the Performance of Stone Sawing Machines, Iranian Quarries
چکیده انگلیسی مقاله The escalating construction industry has led to a drastic increase in the dimension stone demand in the construction, mining and industry sectors. Assessment and investigation of mining projects and stone processing plants such as sawing machines is necessary to manage and respond to the sawing performance; hence, the soft computing techniques were considered as a challenging task due to stochastic optimization of this issue and to handle complex optimization problems. In this study, Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms as soft computing techniques were used to classify the dimension stones based on physical and mechanical properties and ampere consumption. For this purpose, varieties of dimension stones from 12 quarries located in Iran were investigated. Studied dimension stones were classified into two and three separate clusters using the optimization clustering techniques. The results showed that the applied soft computing technique makes it possible to evaluate the performance of sawing machines in different complex conditions and uncertain systems.
کلیدواژه‌های انگلیسی مقاله
نویسندگان مقاله Ahmad Aryafar |
birjand

Reza Mikaeil |
Faculty of Engineering, Department of Mining Engineering Urmia University of Technology, Urmia, Iran

Sina Shafiee Haghshenas |
Member of Young Researchers and Elite Club

sami shafiei haghshenas |
Islamic Azad university, Yazd branch

نشانی اینترنتی https://ijmge.ut.ac.ir/article_65766_ad97858521a20d60107f06cd1155220e.pdf
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زبان مقاله منتشر شده en
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