NDLI: A PSO-ANN Integrated Model of Optimizing Cut-Off Grade and Grade of Crude Ore

Content Provider	IEEE Xplore Digital Library
Author	Sixin Xu Yong He Kejun Zhu Ting Liu Yue Li
Copyright Year	2008
Description	Author affiliation: Sch. of Econ. & Manage., China Univ. of Geosci., Wuhan (Sixin Xu; Yong He; Kejun Zhu; Ting Liu; Yue Li)
Abstract	This work proposes a particle swarm optimization (PSO) and artificial neural networks (ANN) integrated model to simulate the highly complexity and non-linear mine system, to optimize the cut-off grade and grade of crude ore. The inner layer of nesting is neural networks, which is used to compute loss rate, metal utilization rate and total cost; the outer layer is PSO algorithm, with cut-off grade and grade of crude ore as a particle, which is used to get the revenue. These two layers carry out the optimization of cut-off grade and grade of crude ore jointly. Take Daye Iron Mine as a case, the result shows that: During the period of January to November in the year 2007, the optimal cut-off grade is 17.83%, and optimal grade of crude ore is 46.4%. Comparing with the present scheme (cut-off grade is 18%, grade of crude ore is 41-42%), the optimized scheme can increase the amount of concentrate by 139200 tons, and improve the net present value by 6.698 million Yuan.
Starting Page	275
Ending Page	279
File Size	348113
Page Count	5
File Format	PDF
ISBN	9780769533049
DOI	10.1109/ICNC.2008.684
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Costs Geology Optimization methods Artificial neural networks PSO algorithm Iron Particle swarm optimization Grade of crude ore Optimization Ores Neural networks Milling Production Computer networks Cut-off grade
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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