EJPAU 2006. Wiśniewski R. EVALUATION OF QUALITY AND GENERALIZATION PROCESSES IN NEURAL NETWORK SETS USED TO FORECAST THE VALUE OF SPACE

Electronic Journal of Polish Agricultural Universities (EJPAU) founded by all Polish Agriculture Universities presents original papers and review articles relevant to all aspects of agricultural sciences. It is target for persons working both in science and industry,regulatory agencies or teaching in agricultural sector. Covered by IFIS Publishing (Food Science and Technology Abstracts), ELSEVIER Science - Food Science and Technology Program, CAS USA (Chemical Abstracts), CABI Publishing UK and ALPSP (Association of Learned and Professional Society Publisher - full membership). Presented in the Master List of Thomson ISI.

2006
Volume 9
Issue 2

Topic:

Geodesy and Cartography

ELECTRONIC
JOURNAL OF
POLISH
AGRICULTURAL
UNIVERSITIES

Wiśniewski R. 2006. EVALUATION OF QUALITY AND GENERALIZATION PROCESSES IN NEURAL NETWORK SETS USED TO FORECAST THE VALUE OF SPACE, EJPAU 9(2), #33.
Available Online: http://www.ejpau.media.pl/volume9/issue2/abs-33.html

EVALUATION OF QUALITY AND GENERALIZATION PROCESSES IN NEURAL NETWORK SETS USED TO FORECAST THE VALUE OF SPACE

Radosław Wiśniewski
Department of Land Management and Regional Development, University of Warmia and Mazury in Olsztyn, Poland

ABSTRACT

Forecasting the value of real estate is an essential element that should be taken into account by the investor in the process of financing an investment. A similar situation can be observed in the process of land management. In such cases, the reliability of the model used for real estate value prediction becomes a key issue.

The geostatic model is designed to be used for diagnosing the land market system in the past and in the present (at the moment the forecast is generated). It then becomes a prognostic geostatic model used for forecasting. Geostatic models can be developed based on a set of artificial neural networks. A set of neural networks is a set of many trained monolithic neural networks, which are combined into one set to eliminate faults assigned to single network models, as well as to improve generalization capability and resistance.

The aim of the present study was to develop and test in practice a set of measures enabling to evaluate the quality of a forecasting model as well as its generalization capability.

Key words: .

Radosław Wiśniewski
Department of Land Management and Regional Development,
University of Warmia and Mazury in Olsztyn, Poland

email: danrad@uwm.edu.pl

Responses to this article, comments are invited and should be submitted within three months of the publication of the article. If accepted for publication, they will be published in the chapter headed 'Discussions' and hyperlinked to the article.