Abstract
Many industries are yet being faced with the critical problems connected with prediction and prevention of process equipment accidents and hazardous events, including coal mines and transportation systems. Specific interest lies in prediction of the remaining life of mining equipment in the period of its operation. The authors try to attempt an integration of the self-organization and fuzzy logic methods to enhance reliability of forecasts for mining equipment status given the monitoring data uncertainty. The algorithm is proposed for the adaptive introduction of excessive information using a few forecast models. As a result, complexing of forecasts by two–three analogs of the variation criterion in selection of efficient forecast of multi-dimensional nonstationary events is explained. Considering the importance of haulage processes in the mining industry, the integrated forecast models can be extended for motor road and rail transport. In motor road and rail transportation, the traffic timing is strict; however, accidents yet occur and can lead to injuries and even death. In the aggregate, the managerial solutions on safety can be better substantiated.
Published Version
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