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• W2159177827 abstract "In recent times, the application of artificial intelligence (AI) techniques for real property valuation has been on the increase. Some expert systems that leveraged on machine intelligence concepts include rule -based reasoning, case-based reasoning and artificial neural networks. These approaches have proved reliable thus far and in certain cases outperformed the use of statistical predictive models such as hedonic regression, logistic regression, and discriminant analysis. However, individual artificial intelligence approaches have their inherent limitations. These limitations hamper the quality of decision support they proffer when used alone for real property valuation. In this paper, we present a Neural -CBR system for real property valuation, which is based on a hybrid architecture that combines Artificial Neural Networks and Case Based Reasoning techniques. An evaluation of the system was conducted and the experimental results revealed that the system has higher satisfactory level of performance when compared with individual Artificial Neural Network and Case Based Reasoning systems." @default.
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• W2159177827 date "2013-08-01" @default.
• W2159177827 modified "2023-09-27" @default.
• W2159177827 title "A Neural-CBR System for Real Property Valuation" @default.
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