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General Information
    • ISSN: 1793-8244 (Print)
    • Abbreviated Title:  J. Adv. Comput. Netw.
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Professor Haklin Kimm
    • Executive Editor: Ms. Cherry Chan
    • Abstracting/ Indexing: EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
    • APC: 500USD
Professor Haklin Kimm
East Stroudsburg University, USA
I'm happy to take on the position of editor in chief of JACN. We encourage authors to submit papers on all aspects of computer networks.

JACN 2016 Vol.4(1): 19-23 ISSN: 1793-8244
DOI: 10.18178/JACN.2016.4.1.197

Radio Spectrum Valuation by Applying the Artificial Neural Network Model

S. Malisuwan, N. Suriyakrai, and N. Madan

Abstract—As radio spectrum is a key resource for many technology-based industries and most promising industries of the future including broadcasting, telecommunications, military defense, industrial, medical and even domestic applications. These radio spectrum licenses are inputs into these business sectors that provide services to the public. The radio spectrum management and its valuation have turned out to be of vital importance in recent years due to the rapid development of mobile broadband communication. As a result of such popular demand of spectrum in this past decade, spectrum value is absolutely critical to policy analysis, as well as to encouraging investment in the telecom industry. This paper presents and proposes the radio spectrum valuation method by applying Artificial Neural Network model (ANN). The contributions in this paper could assist telecom policy makers to gain more understanding in development of radio spectrum valuation.

Index Terms—Radio spectrum, valuation, neural network, model.

The authors are with the National Broadcasting and Telecommunications Commission Bangkok, Thailand (e-mail: settapong.m@nbtc.go.th, nattakit.s@nbtc.go.th, navneet.m@nbtc.go.th).


Cite:S. Malisuwan, N. Suriyakrai, and N. Madan, "Radio Spectrum Valuation by Applying the Artificial Neural Network Model," Journal of Advances in Computer Networks vol. 4, no. 1, pp. 19-23, 2016.

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