DocumentCode
3244438
Title
Probabilistic neural network and Polynomial Fitting Approach used to determine radio field strength under power lines in radial network
Author
Ou, Ting-Chia ; Huang, Cong-Hui ; Chen, Chiung-Hsing ; Hong, Chih-Ming ; Lu, Kai-Hung
Author_Institution
Nat. Sun Yat-Sen Univ., Kaohsiung, Taiwan
fYear
2009
fDate
14-17 July 2009
Firstpage
1653
Lastpage
1658
Abstract
A new model based on Probabilistic neural network (PNN) and Polynomial Fitting Approaches (PFA) for radio field strength prediction has been developed. This paper researches the radio field strength, related to the service of a radio system for the operation of set points in the radial networks. The service uses radio propagation to dispatch messages to set points. In order to estimate the radio field strength, we performed some realistic measurements related to set points. Then, the data was analyzed using a combination of Probabilistic Neural Network and Polynomial approximations to estimate the radio field strength, and to create a new optimal model specific to the needs of radial networks.
Keywords
electrical engineering computing; neural nets; polynomial approximation; power cables; radiowave propagation; polynomial approximations; polynomial fitting approaches; power lines; probabilistic neural network; radial network; radial networks; radio field strength prediction; radio propagation; radio system service; Artificial neural networks; Data analysis; Flowcharts; Intelligent networks; Mechatronics; Neural networks; Performance evaluation; Polynomials; Predictive models; Radio propagation;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Intelligent Mechatronics, 2009. AIM 2009. IEEE/ASME International Conference on
Conference_Location
Singapore
Print_ISBN
978-1-4244-2852-6
Type
conf
DOI
10.1109/AIM.2009.5229826
Filename
5229826
Link To Document