Using expert systems in mine warfare.

Abstract : Historically, sea mines warfare have played an important role in warfare, which a naval officer cannot afford to neglect. During the recent mine campaign in the Middle East involving Iran an Iraq, commanders delayed decisions on whether or not to deploy mine countermeasure (MCM) forces. As a result, damage occurred to ships in a minefield that could have been prevented by the speedy application of MCM. Before the operational mission commenced, there are several uncertain questions in the mind of the commander: Do the mine-fields exist? Which country laid the mines? What type of delivery platform laid the mines? Where are the mines? What kind of mines are they? Do we need to deploy the MCM forces? Previously, these kinds of fuzzy questions were very difficult to answer by a tactical principle. In this thesis, the probabilistic inference network in the expert system environment is used to answer the above questions. The probabilistic inference network method is supported by the certainty factors. Calculations involving quantitative probabilities for answers to the above questions could enable the MCM experts to offer suggestions to the commander for reducing the ship's vulnerability at sea during wartime.