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학술지 Optimized Fuzzy Adaptive Filtering for Ubiquitous Sensor Networks
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저자
이해영, 조대호
발행일
201106
출처
IEICE Transactions on Communications, v.E94.B no.6, pp.1648-1656
ISSN
0916-8516
출판사
일본, 전자정보통신학회 (IEICE)
DOI
https://dx.doi.org/10.1587/transcom.E94.B.1648
협약과제
10MS2700, 정보 산업기기용 임베디드SW 공통 플랫폼 개발, 임채덕
초록
In ubiquitous sensor networks, extra energy savings can be achieved by selecting the filtering solution to counter the attack. This adaptive selection process employs a fuzzy rule-based system for selecting the best solution, as there is uncertainty in the reasoning processes as well as imprecision in the data. In order to maximize the performance of the fuzzy system the membership functions should be optimized. However, the efforts required to perform this optimization manually can be impractical for commonly used applications. This paper presents a GA-based membership function optimizer for fuzzy adaptive filtering (GAOFF) in ubiquitous sensor networks, in which the efficiency of the membership functions is measured based on simulation results and optimized by GA. The proposed optimization consists of three units; the first performs a simulation using a set of membership functions, the second evaluates the performance of the membership functions based on the simulation results, and the third constructs a population representing the membership functions by GA. The proposed method can optimize the membership functions automatically while utilizing minimal human expertise. Copyright © 2011 The Institute of Electronics, Information and Communication Engineers.
키워드
False data filtering, Fuzzy logic, Genetic algorithms, Network security, Optimization, Ubiquitous sensor networks
KSP 제안 키워드
Adaptive filtering, Energy saving, False data, Fuzzy Rule-based System(FRBS), Fuzzy adaptive, Genetic Algorithm, Human expertise, Information and communication, Membership Functions, Selection process, adaptive selection