Generalized models based on neural networks and multiple linear regression

Authors:
Pero Radonja;Srdjan Stankovic;Dragana Drazic;Bratislav Matovic
Affiliations:
Institute of Forestry, Belgrade, Serbia;Faculty of Electrical Engineering, University of Belgrade, Belgrade, Serbia;Institute of Forestry, Belgrade, Serbia;Institute of Forestry, Belgrade, Serbia
Venue:
CSECS'06 Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing
Year:
2006

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Abstract

Developed generalized models are based on neural networks, linear and multiple linear regression. Applications of the generalized (regional) models in estimation of the most important general (common) characteristic of the whole region is done. Testing of the regional models with real, referent data is performed by regression analyses, also. The obtained correlation coefficients between referent data and corresponding data computed using the regional models based on linear and multiple linear regression are very height, 0.9971 and 0.9955 respectively. In the case of application of neural networks correlation coefficients is the largest, 0.9985.