Non-Conventional Approaches To Property Value Assessment

The results indicate that no single one of the new methods used in evaluating residential property values for a real data set is consistently superior for the given data set.

Abstract

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt;"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">Lack of precision is common in property value assessment. Recently non-conventional methods, such as neural networks based methods, have been introduced in property value assessment as an attempt to better address this lack of precision and uncertainty. Although fuzzy logic has been suggested as another possible solution, no other artificial intelligence methods have been applied to real estate value assessment other than neural network based methods. This paper presents the results of using two new non-conventional methods, fuzzy logic and memory-based reasoning, in evaluating residential property values for a real data set. The paper compares the results with those obtained using neural networks and multiple regression. Methods of feature reduction, such as principal component analysis and variable selection, have also been used for possible improvement of the final results.<span style="mso-spacerun: yes;">  </span>The results indicate that no single one of the new methods is consistently superior for the given data set.</span></span></p>