Neuro-Fuzzy Approach to Explosion Consequence Analysis

An explosion consequence analysis utilizes explosives science and engineering to determine potential hazards to targets through objective processes and scientific evidence. This paper proposes the implementation of adaptive neuro-fuzzy inference system in providing decision support for accurate and effective explosion consequence analysis. The model is trained over data obtained from United Nations SaferGuard platform and incorporates the consequence analysis of seven different types of explosives, on brick structures over a range of twenty meters. The model has been implemented using block diagrams on MATLAB Simulink. This work adds to the body of evidence that soft computing techniques can be implemented in designing accurate artificial intelligence decision support and expert systems for both military and civilian applications.