A prototype of knowledge base system for weather monitoring and forecasting

• Autores: Oluwole Charles Akinyokun, T. N. Anyiam
• Localización: International journal of the computer, the internet and management, ISSN 0858-7027, Vol. 9, Nº. 1, 2001, págs. 13-23
• Idioma: inglés
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• Resumen

  • We present the model of both structured and unstructured knowledge of weather features in this paper. An inference engine that simulates the model which is empowered to dynamically acquire knowledge is proposed. The output of the inference engine serves as input to the user-friendly, interactive, intelligent and menu-driven decision support engine. The decision support engine is characterized by a cognitive filter and an emotional filter and it is built to objectively and subjectively access and evaluate the alternative weather forecasts produced by the inference enigine with a view to arriving at the 'best' weather forecast. The case study of the system has been carried out using the data collected from the Meteorological Data Distribution (MDD) system installed at the Murtala Mohammed International Airport, Ikeja, Lagos, Nigeria. The results obtained from the weather forecast for Lagos are presented. The objective of the study is to provide an intelligent, symbiotic and convivial system that would combine the skill of human experts in meteorology and the power of computing system in the bid to carry out the task of weather monitoring and forecasting. Moreover, the proposed framework can serve as a Computer Aided Learning (CAL) system for weather monitoring and forecasting by the students of meteorology.