A situation assessment method for rock burst based on multi-agent information fusion ?
The target of this research is assessment situation of rock burst in coal mine. Generally speaking, an assessment approach for the rock burst situation by integrating the Multi-Agent System with data fusion techniques is proposed. To improve the accuracy and reliability of source data, an optimal algorithm for multi-sensor data fusion is discussed. Some intelligent model-based situation quantization methods is described and rock burst situation quantitative assessment model is discussed by improved DempsterShafer theory. The Auto-Regressive and Moving Average Model and HoltWinters model are used to deal with indefinability and inaccuracy in the process of predicting rock burst. Case study results shows the proposed rock burst situation assessment model can give a relatively accurate forecast, and can help coal mine decision-makers to grasp an overview of the development trend of the rock burst.
situation assessment rock burst information fusion multi-agent system forecasting model