A rule-based expert system for mining method selection

"In recent years, computer based ""expert systems"" have been taking on large complex tasks for which no exact algorithmic solutions are feasible; tasks previously reserved for human experts requiring empirical knowledge, judgment, experience, developing a ""best solution "" by the use of plausible reasoning. Mining method selection is an appropriate area for the application of an expert system because extensive and detailed knowledge is required to make a ""best"" interpretaion of frequently ambiguous geological information. The expert system model presented here would enable users to apply expert knowledge to the evaluation of methods for coal deposits mineable by underground methods. IntroductionIn an increasingly complex and specialized world, human expertise spanning scientific, economic, social and political issues plays an increasingly important role in all branches of engineering. This is especially true of mining engineering. The number of scientific and professional disciplines involved in mine planning and evaluation, illustrates the problem. A conservative list includes geology, geophysics, geotechnics, hydrology, mining, environment, and economics.Engineers are almost obliged to be experts in at least one of the above disciplines if they are to handle the volume of information required in the planning process. Although computers have become indispensable tools in many endeavours, there is continued reliance on the human expert's ability to identify and synthesize these diverse factors, to form judgments, evaluate alternatives , and make decisions . This is especially true with regard to problems that are not easily amenable to precise formulations.The precious resource of human expert is also fragile and transient. The departure of a crucial expert from an organization ma y cause serious dislocations. Senior experienced people impart their knowledge of younger colleagues, but the demand for their talent may not leave sufficient time for such educational efforts. In recent years, computer based "" expert systems"" have been taking on large complex tasks for which no exact algorithmic solutions are feasible; tasks previously reserved for human experts, requiring empirical knowledge, judgment , experience, developing a ""best solution"" by the use of plausible reasoning."