Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This pa...Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR （Geo-CBR）. First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.展开更多
Coal mining activity is often restricted by geologic structural conditions, so it is very important to know the distribution situation of mine structures in advance of mining. For this reason, traditional qualitative ...Coal mining activity is often restricted by geologic structural conditions, so it is very important to know the distribution situation of mine structures in advance of mining. For this reason, traditional qualitative procedure must give way to quantitative prediction method backed by mathematics theory and computer technology. This paper explores some relevant problems with the method, introducing a software, MSPS, used to predict automatically and quantitatively the relative complexities of geologic structures in different blocks of a coal mining area, with an application example employing the software to select the most suitable mining sites.展开更多
文摘Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR （Geo-CBR）. First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.
文摘Coal mining activity is often restricted by geologic structural conditions, so it is very important to know the distribution situation of mine structures in advance of mining. For this reason, traditional qualitative procedure must give way to quantitative prediction method backed by mathematics theory and computer technology. This paper explores some relevant problems with the method, introducing a software, MSPS, used to predict automatically and quantitatively the relative complexities of geologic structures in different blocks of a coal mining area, with an application example employing the software to select the most suitable mining sites.
