As with the MMS problem, the expert system and fuzzy algorithms were successfully applied to the ESP in combination with other MCDM and auxiliary methods. In addition, GA was recently practically utilised in the actual ESP. However, because the ESP is a part of mine-production planning, it would be useful to include mine production scheduling as well. Additionally, further discussions are required to include equipment salvage and services for long- and short-term equipment purchasing strategies.
Typical rock mechanics subjects that use SC technologies werere viewed in the second section of chapter three. ANN was consistently applied to identify strengths and the deformation modulus of rock masses, predict rock mass performance, and estimate their stability. Fuzzy algorithms and GAs were often employed with various auxiliary methods. Fuzzy algorithms were principally utilised in the rock mass classification problem. In some cases, the expert system was also applied. As discussed, the SC technologies have taken an important role in rock mechanics, and their abilities to address uncertainties, insufficient information, and ambiguous linguistic expressions stand out in treating complex natural rock masses.
Rock blasting is an uncertain activity in indistinct rock masses. To overcome the difficulties, several studies consistently employed ANN to predict some important blasting-related effects. Fuzzy algorithms, GAs, neuro-fuzzy algorithms, and support vector machine technologies were often adopted as well. The superiority of SC technologies has been verified by comparing results from SC applications with conventional statistical and mathematical prediction methods.
Each soft computing technology has advantages and disadvantages. For instance, ANN normally shows excellent nonlinear approximation performance but it is hard to enlighten the inputs and outputs relationship as often it called as ‘black box’. As well as each mining conundrum has a different aspect of problem and solution. For example, mining method selection (MMS) can be recognised as a multiple-attribute decision-making (MADM) problem that can be efficiently handled by a method that can represent significance and ranking of criteria. From this point of view, fuzzy algorithm is much more suitable algorithm than ANN for MMS. Thus, it is important to cautiously concern the attribute of a problem to amplify the advantages of applied soft computing method.
Precise data and information is expensive, and exact geological and geotechnical data are practically impossible to obtain and organise. In addition, the weighted effects of associated factors of certain mining problems are still unclear. Their mutual interactions increase the complexity of problems. However, mining engineers frequently encounter many decision-making problems due to all the uncertainties and impreciseness previously described. A remedy for those problems may be to adopt advanced SC technology, which may play a large role in mining engineering.