Using Artificial Intelligence Techniques to Improve the Prediction of Copper Recovery by Leaching
المؤلفون المشاركون
Flores, Victor
Keith, Brian
Leiva, Claudio
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-02-07
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
Copper mining activity is going through big changes due to increasing technological development in the area and the influence of industry 4.0.
These changes, produced by technological context and more controls (e.g., environmental controls), are also becoming visible in Chilean mining.
New regulations from the Chilean government and changes in the copper mining industry (such as a trend to underground mining) are fostering the search for better results in typical processes such as leaching.
This paper describes an experience using artificial intelligence techniques, particularly random forest, to develop predictive models for copper recovery by leaching, using data from an enterprise present in northern Chile for more than 20 years.
Two models, one of them with actual operational data and another one with data generated in a controlled environment (piling) are presented.
Well-classified values of 98.90% for operational data and 98.72% for pile/piling data were obtained.
The methodology devised for the study can be transferred to piling columns or piles with other characteristics, though the operation must focus on copper leaching.
It can even be transferred to other leaching processes using another type of mineral, with proper adjustments.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Flores, Victor& Keith, Brian& Leiva, Claudio. 2020. Using Artificial Intelligence Techniques to Improve the Prediction of Copper Recovery by Leaching. Journal of Sensors،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1190364
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Flores, Victor…[et al.]. Using Artificial Intelligence Techniques to Improve the Prediction of Copper Recovery by Leaching. Journal of Sensors No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1190364
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Flores, Victor& Keith, Brian& Leiva, Claudio. Using Artificial Intelligence Techniques to Improve the Prediction of Copper Recovery by Leaching. Journal of Sensors. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1190364
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1190364
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر