ABSTRACT
This chapter deals with a description of the underlying principles of neural networks applied to data analysis, and the means by which such methods can form the basis of practical taxation systems. It describes case studies and presents the principles of the application. The chapter aims to provide a pointer towards likely developments of Artificial Intelligence in the future, and how these can be utilized to advantage for professionals who have the task of creating and operating dependable mass appraisal systems. It explains the principles underlying artificial intelligence, and neural networks in particular, and their application to the types of numerical methods and recognition activities relevant to the determination of property values for taxation purposes. The chapter assesses the case studies and proposes various scenarios for the practical implementation of neural networks. It concludes with the likely outcome of present research and commercial developments in the artificial intelligence field relevant to the mass appraisal process.
