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In recent years,the application of artificial intelligence technique tounderwater acoustic environment obtains great attention.This paper presentsthe work on developing a Micro-Expert System for underwater target classifl-cation.The major contributions include that:1)A new tri-symbol codingmethod for symbolic representation of waveforms is proposed,and successfullyapplied to knowledge-based waveform analysis;2)The properties,featuresand deployment conditions of a variety of underwater ECM(electriccounter-measure)equipments together with target features are collected andsummarized and a combined knowledge representation approach is developedfor application in underwater acoustic environment;3)A suitable Blackboardmodel inference mechanism is developed to cope with time sequence anduncertainty information and 4)A Micro-Expert System Shell for underwatertarget classification is developed through integrating the above special tech-niques.The current system shell is flexible,friendly with user-interface,andea
In recent years, the application of artificial intelligence technique tounderwater acoustic environment obtains great attention.This paper presentsthe work on developing a Micro-Expert System for underwater target. The major contributors include that: 1) A new tri-symbol codingmethod for symbolic representation of waveforms is proposed, and successfully applied to knowledge-based waveform analysis; 2) The properties, featuresand deploymentconditions of a variety of underwater ECM (electriccounter-measure) equipments together with target features are collected andsummarized and a combined knowledge representation approach is developed for application in underwater acoustic environment; 3) A suitable Blackboard model inference mechanism is developed to cope with time sequence and ununitary information and 4) A Micro-Expert System Shell for underwater match classification is developed through integrating the above special tech-niques. current system shell is flexible, friendly with u ser-interface, andea