Determination Of Mineral Mining Exploration Area With Fuzzy Using Genetic Algorithm To Reduce Mining Risk

Paryati, Paryati (2022) Determination Of Mineral Mining Exploration Area With Fuzzy Using Genetic Algorithm To Reduce Mining Risk. In: International Conference on Recent Advances in the Field of Management, Law, Education and Technology: An Interdisciplinary Approach, 2 June 2022, West Bengal, India.

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Abstract

There are many methods that can be used to map the distribution of a mineral reserve element in nature.
One of the approaches used to localize the distribution of an element is by using a mathematical model,
so that it can simplify and speed up the work process, especially when carrying out exploration or
prospecting activities in a very large area. In this mathematical model approach, it is carried out by
carrying out mathematical data processing to describe a systematic variation of a variable or a group of
variables in a field using fuzzy logic and genetic algorithms.
The software design uses the waterfall methodology, which consists of analysis, design, implementation
and testing. The algorithm used is a genetic algorithm. This algorithm is based on genetic processes that
exist in living things, namely the development of generations in a natural population, gradually
following the principle of selection or who is strong will survive. In the exploration system for mapping
the distribution of an element of mineral reserves, the influence of the mineral reserve area results in
uncertainties in part or all of the coefficients on the objective function, such as mining costs or mining
time which cannot be known with certainty. A way to deal with uncertainty in decision making is using
the fuzzy principle. The fuzzy cost parameter uses a Triangular Fuzzy Number (TFN). In the
optimization of multiple criteria, the determination of the optimal value using the Pareto solution. The
Pareto solution is determined based on the ordered fuzzy objective values. Comparison and sorting of
fuzzy numbers, using integral values. The software is implemented in the latest version of the Borland
Delphi programming language environment which is a development of the Pascal language for a
window-based programming environment.
The results of this study indicate that the solution to the problem of mapping the mining of mineral
reserves with multiple criteria can be solved by using a heuristic approach using genetic algorithms.
Genetic algorithms can be used to distinguish spatial data variables into two components, namely trend
or fitting functions (as regional anomalies) and residual values. Difficulties in data interpretation due to
irregular distribution of data from an investigation can be reduced by these mathematical equations. This
will minimize the risk of failure to find the mineral reserve exploration target area. The advantage of
fuzzy logic and genetic algorithms is their ability to follow changes in the pattern of fluctuations in data
values up to the nth order. The results of the research are expected to yield residual values, which are
useful in initial interpretation towards mineral exploration targets. To determine the level of confidence
and significance of the polynomial function used, statistical tests can then be performed.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	Publish
Uncontrolled Keywords:	Exploration, Fuzzy Logic, Waterfall, Genetic Algorithm
Subjects:	T Technology > T Technology (General) > T201 Patents. Trademarks
Divisions:	Faculty of Engineering, Science and Mathematics > School of Engineering Sciences
Depositing User:	ST.,M.Kom PARYATI PARYATI
Date Deposited:	07 Apr 2023 09:26
Last Modified:	07 Apr 2023 09:26
URI:	http://eprints.upnyk.ac.id/id/eprint/33984

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