FLOREON+: Using Case-Based Reasoning In A System For Flood Prediction
Free (open access)
T. Kocyan, J. Martinovic, J. Unucka & I. Vondrak
Human consumption and other natural factors are changing our climate and the world we live in. The changing climate and the increased risk of flooding around the world are among some of today’s most urgent social issues. There are many resources and technology available to assist in damage reduction and minimizing consequences related to this natural phenomenon. This is possible because the development of information technology has expanded into many branches of human life. This article describes the development of a knowledge system created to assist in limiting cases of natural disasters. Our goal is to design and create a system to be used by either professional and non-professional organizations, or individuals, as a tool for exchanging knowledge. Our Disaster Prevention system (DIP) combines data mining and the analysis of past events to predict future natural disasters. We apply the Case-Based Reasoning (CBR) method. The principle of this method is based on collecting data (knowledge, experiences, etc.) and then applying this information to achieve new solutions. Tests have shown that by using information about past events, it is possible to determine future patterns of nature (e.g. weather conditions on specific land surfaces). These patterns can be used for describing the risk of future natural disasters and enables us to deduce the threat imposed by them. Analyzing this data and creating new solutions may assist in the fight to minimize damage incurred by these disasters. Keywords: Case-Based Reasoning, disaster management, case-based prediction, information retrieval.
Case-Based Reasoning, disaster management, case-based prediction, information retrieval