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A Neural-CBR System for Real Property Valuation

Musa , A.G and Daramola, Olawande and Owoloko, E. A. and Olugbara, O. O. (2013) A Neural-CBR System for Real Property Valuation. Journal of Emerging Trends in Computing and Information Sciences, 4 (8). pp. 611-622. ISSN 2079-8407

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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.

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mr Solomon Bayoko
Date Deposited: 15 Jan 2014 06:28
Last Modified: 04 May 2017 13:09

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