Abstract
The work of quantifying the problems of abandoned mines is the first step towards the rehabilitation of these mines. As the result, in all countries that have many abandoned mines, researchers and different organizations have been making efforts to develop decision-making tools, methods, and techniques for rehabilitation of abandoned mines. This paper describes the work conducted to incorporate the method for ranking the problems of abandoned mine entries into a rule-based expert system. This is done using the web-based expert system platform provided by expert system (ES)-Builder Shell. The ES is tested by applying it to the case study of the problems of abandoned mine entries in the areas of Giyani and Musina, Limpopo Province of South Africa. This paper gives details of the procedure followed in creating the production rules of the ES for ranking problems of abandoned mine entries (ES-RAME), its attributes, and the results of its application to the selected case study. The use of the ES-RAME is found to be important for setting the objectives and priorities of the rehabilitation of abandoned mine entries. In addition, the incorporation of the ranking method into the expert system ensured that the procedure of the tanking method is clearly communicated and preserved as the rules of the ES. The expert system also has the advantages of being consistent in its guidance, and it gives the user an opportunity to go through the ranking process of the system using any possible fictitious information; this gives the user a feel for the ranking process and the data required when using the ES-RAME.
Highlights
An expert system (ES) is a computer program that deals with decision making in a specific field of knowledge [1]
This paper presents the work conducted with the purpose of implementing the method for ranking the problems of abandoned mines in the rule-based expert system
The example of the production rules of this expert system made it possible that the environmental and physical hazards of the abandoned mine entries, together with their associated socio-economic concerns, could be ranked into four categories, which are High, Moderate, Low, and Negligible. This caused the decision tree developed for the expert system to be broadly divided into three branches, the first of which was responsible for the ranking of the physical hazards and social concerns of the mine entries, while the other assisted with the ranking of the environmental and economic impacts of the mine entries
Summary
An expert system (ES) is a computer program that deals with decision making in a specific field of knowledge [1] It is a branch of artificial intelligence (AI) that uses knowledge and inference procedures to solve problems that generally require human expertise [2]. Expert systems mimic the behavior of human experts [3] They can be created from information gathered from experts or using model-based information [4]. The expert system shell is basically a computer program that, when supplied with a knowledge base, yields an expert system. It reasons with the knowledge in the knowledge base to produce conclusions that are based on entered facts, which seriously reduces the amount of time and labor required for creation of an expert systems. The shells eliminate the need for programming the rules of the expert system using programming languages such as C/C++
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