A Neuro-Fuzzy Approach to MOPP Open Time Prediction for Chemical Threats in Low-Intensity Conflicts

Abstract

Chemical, Biological, Radiological and Nuclear (CBRN) weapon systems hold the potential to cause great damage to a fighting unit. Chemical warfare agents are cheaper and easier to produce and deploy. Mission oriented protective posture (MOPP) equipment is used to isolate soldiers from the toxic environment . Sustained wearing of MOPP overgarments can put soldiers at the risk of dehydration and heat stress. A hierarchal adaptive neuro-fuzzy inference system (HANFIS) model is proposed to predict worst case MOPP open times for surfaces covered with chemical agent resistant coating (CARC) and sand. The model can provide decision support for commanders when determining MOPP open or unmasking time. From HANFIS simulation results it was concluded that the model can accurately predict MOPP open times according to data present in military field manuals, in a manner which is computationally efficient. and easy to interpret based on linguistic rules and most importantly, easy to customize.