{"id":{"repo_id":"southwales","oai_identifier":"oai:pure.atira.dk:studenttheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a"},"canonical_url":"https://search.dev.ndltd.org/etd/southwales/oai:pure.atira.dk:studenttheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a","repository":{"repo_id":"southwales","name":"University of South Wales","base_url":"https://pure.southwales.ac.uk/ws/oai"},"display":{"title":"Immovable property taxation and the development of an artificial neural network valuation system for residential properties for tax purposes in Cyprus","abstract":"The last General Valuation in Cyprus, in 1980, took about twelve years to be completed by the Lands and Surveys Department. The comparison method was adopted and no computerised (mass appraisal) method or tool was used to assist the whole process. Although the issue of mass appraisal was raised by Sagric International, who had been invited to Cyprus as consultants, and
recently by DataCentralen A/S with the development of a mass appraisal system based on regression analysis, there has been little literature and no research directly undertaken on the problems and the analysis of immovable property taxation in Cyprus and the development of an artificial neural networks valuation system for houses and apartments.
The research project approached the issue of property taxation and mass appraisal through an investigation into Cyprus's needs for an up-dated tax base for equitabileness and for an assessment system capable of performing an effective revaluation at a certain date, with minimum acceptable mean error,
minimum data and minimum cost.
Investigation within Cyprus and world-wide indicated that this research project is a unique study in relation to Cyprus's property taxation and the development of a computer assisted mass appraisal system based on modular artificial neural networks. An empirical study was carried out, including prototyping and testing.
The system results satisfy IAAO criteria for mass appraisal techniques, compare favourably with other studies and established a framework upon which future research into computer assisted mass appraisal for taxation purposes can be developed.
In conclusion, the project has contributed significantly to the available literature on the immovable property taxation in Cyprus and the development of a computer assisted mass appraisal system for houses and apartments based on modular artificial neural network method. The proposed approach is novel not only in the context of Cyprus but also world-wide.","abstract_html":"The last General Valuation in Cyprus, in 1980, took about twelve years to be completed by the Lands and Surveys Department. The comparison method was adopted and no computerised (mass appraisal) method or tool was used to assist the whole process. Although the issue of mass appraisal was raised by Sagric International, who had been invited to Cyprus as consultants, and<br/>recently by DataCentralen A/S with the development of a mass appraisal system based on regression analysis, there has been little literature and no research directly undertaken on the problems and the analysis of immovable property taxation in Cyprus and the development of an artificial neural networks valuation system for houses and apartments.<br/><br/>The research project approached the issue of property taxation and mass appraisal through an investigation into Cyprus's needs for an up-dated tax base for equitabileness and for an assessment system capable of performing an effective revaluation at a certain date, with minimum acceptable mean error,<br/>minimum data and minimum cost.<br/><br/>Investigation within Cyprus and world-wide indicated that this research project is a unique study in relation to Cyprus's property taxation and the development of a computer assisted mass appraisal system based on modular artificial neural networks. An empirical study was carried out, including prototyping and testing.<br/><br/>The system results satisfy IAAO criteria for mass appraisal techniques, compare favourably with other studies and established a framework upon which future research into computer assisted mass appraisal for taxation purposes can be developed.<br/><br/>In conclusion, the project has contributed significantly to the available literature on the immovable property taxation in Cyprus and the development of a computer assisted mass appraisal system for houses and apartments based on modular artificial neural network method. The proposed approach is novel not only in the context of Cyprus but also world-wide.","abstract_has_math":false,"creators":["Panayiotiou, Panayiotis Andrea"],"institution":null,"degree_name":"Doctoral Thesis","degree_level":"Student thesis","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1999,"date_issued":"1999","date_published":"1999","updated_at":"2026-07-24T04:38:53Z","subjects":["Artificial Neural Networks","ANNs","Valuation System","Immovable property taxation","Cyprus","mass appraisal techniques"],"languages":["eng"],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.atira.dk:studenttheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a"],"render_values":[{"text":"oai:pure.atira.dk:studenttheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a","href":null,"code":true}]}]},"links":{"outbound_url":"https://pure.southwales.ac.uk/en/studentTheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Panayiotiou, Panayiotis Andrea"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["1999"]},{"key":"dc:date.issued","label":"Date","values":["1999"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://pure.southwales.ac.uk/en/studentTheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["Student thesis"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Doctoral Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Artificial Neural Networks","ANNs","Valuation System","Immovable property taxation","Cyprus","mass appraisal techniques"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["oai:pure.atira.dk:studenttheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a","https://pure.southwales.ac.uk/en/studentTheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://pure.southwales.ac.uk/files/2069080/P._A._Panayiotou_1999_2059389.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The last General Valuation in Cyprus, in 1980, took about twelve years to be completed by the Lands and Surveys Department. The comparison method was adopted and no computerised (mass appraisal) method or tool was used to assist the whole process. Although the issue of mass appraisal was raised by Sagric International, who had been invited to Cyprus as consultants, and
recently by DataCentralen A/S with the development of a mass appraisal system based on regression analysis, there has been little literature and no research directly undertaken on the problems and the analysis of immovable property taxation in Cyprus and the development of an artificial neural networks valuation system for houses and apartments.
The research project approached the issue of property taxation and mass appraisal through an investigation into Cyprus's needs for an up-dated tax base for equitabileness and for an assessment system capable of performing an effective revaluation at a certain date, with minimum acceptable mean error,
minimum data and minimum cost.
Investigation within Cyprus and world-wide indicated that this research project is a unique study in relation to Cyprus's property taxation and the development of a computer assisted mass appraisal system based on modular artificial neural networks. An empirical study was carried out, including prototyping and testing.
The system results satisfy IAAO criteria for mass appraisal techniques, compare favourably with other studies and established a framework upon which future research into computer assisted mass appraisal for taxation purposes can be developed.
In conclusion, the project has contributed significantly to the available literature on the immovable property taxation in Cyprus and the development of a computer assisted mass appraisal system for houses and apartments based on modular artificial neural network method. The proposed approach is novel not only in the context of Cyprus but also world-wide."]},{"key":"dc:title","label":"Title","values":["Immovable property taxation and the development of an artificial neural network valuation system for residential properties for tax purposes in Cyprus"]}]}],"canonical_facts":{"dc:creator":["Panayiotiou, Panayiotis Andrea"],"dc:date":["1999"],"dc:date.issued":["1999"],"dc:description.abstract":["The last General Valuation in Cyprus, in 1980, took about twelve years to be completed by the Lands and Surveys Department. The comparison method was adopted and no computerised (mass appraisal) method or tool was used to assist the whole process. Although the issue of mass appraisal was raised by Sagric International, who had been invited to Cyprus as consultants, and
recently by DataCentralen A/S with the development of a mass appraisal system based on regression analysis, there has been little literature and no research directly undertaken on the problems and the analysis of immovable property taxation in Cyprus and the development of an artificial neural networks valuation system for houses and apartments.
The research project approached the issue of property taxation and mass appraisal through an investigation into Cyprus's needs for an up-dated tax base for equitabileness and for an assessment system capable of performing an effective revaluation at a certain date, with minimum acceptable mean error,
minimum data and minimum cost.
Investigation within Cyprus and world-wide indicated that this research project is a unique study in relation to Cyprus's property taxation and the development of a computer assisted mass appraisal system based on modular artificial neural networks. An empirical study was carried out, including prototyping and testing.
The system results satisfy IAAO criteria for mass appraisal techniques, compare favourably with other studies and established a framework upon which future research into computer assisted mass appraisal for taxation purposes can be developed.
In conclusion, the project has contributed significantly to the available literature on the immovable property taxation in Cyprus and the development of a computer assisted mass appraisal system for houses and apartments based on modular artificial neural network method. The proposed approach is novel not only in the context of Cyprus but also world-wide."],"dc:identifier":["oai:pure.atira.dk:studenttheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a","https://pure.southwales.ac.uk/en/studentTheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a"],"dc:identifier.uri":["https://pure.southwales.ac.uk/files/2069080/P._A._Panayiotou_1999_2059389.pdf"],"dc:language":["eng"],"dc:relation.isreferencedby":["https://pure.southwales.ac.uk/en/studentTheses/3ec3bd33-0820-4e21-97f0-a3ea0e303a9a"],"dc:subject":["Artificial Neural Networks","ANNs","Valuation System","Immovable property taxation","Cyprus","mass appraisal techniques"],"dc:title":["Immovable property taxation and the development of an artificial neural network valuation system for residential properties for tax purposes in Cyprus"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["Student thesis"],"dc:type.qualificationname":["Doctoral Thesis"]},"updated_at":"2026-07-24T04:38:53Z"}