Presentation	2012/1/11 Ray-tracing Propagation Prediction System Applying Machine Learning Algorithms Atsushi KUNIKATA, Tetsuro IMAI,
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Abstract(in English)	In order to improve the precision and calculation efficiency of the ray-tracing system which we developed earlier, we additionally implemented machine learning algorithms of a neural network and a genetic algorithm. As for the neural network, we trained the neural network to compensate errors in our ray-tracing system and examined the error compensation effect of parameters inputted into the neural network. As for the genetic algorithm (GA), we evaluated the performance of GA ray-tracing method in urban macro cellular environment, from the viewpoint of processing time and an estimation error.
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Keyword(in English)	Ray-tracing / Neural network / Genetic algorithm
Paper #	A・P2011-162
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Conference Information
Committee	AP
Conference Date	2012/1/11(1days)
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Paper Information
Registration To	Antennas and Propagation (A・P)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Ray-tracing Propagation Prediction System Applying Machine Learning Algorithms
Sub Title (in English)
Keyword(1)	Ray-tracing
Keyword(2)	Neural network
Keyword(3)	Genetic algorithm
1st Author's Name	Atsushi KUNIKATA
1st Author's Affiliation	NTT DoCoMo, Inc.()
2nd Author's Name	Tetsuro IMAI
2nd Author's Affiliation	NTT DoCoMo, Inc.
Date	2012/1/11
Paper #	A・P2011-162
Volume (vol)	vol.111
Number (no)	376
Page	pp.pp.-
#Pages	6
Date of Issue