2020
DOI: 10.1186/s13638-020-01703-7
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A survey of fuzzy logic in wireless localization

Abstract: Positioning and location estimation of targets either for mobile or stationary nodes is very important, especially after the astonishing developments of the wired and/or wireless communications, as well as the popularity of handheld devices. To assist in accessing services or managing resources, numerous users, application developers, and service providers require accurate position information. Owing to the boom of multisensory systems, wireless technology, and autonomous systems, many positioning systems have… Show more

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Cited by 27 publications
(12 citation statements)
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“…Because linguistic values can be defined by classical sets per set or with some granular computing technique [182]. Therefore, a fuzzy system can be classified as a granular computation technique, where membership functions define linguistic values, i.e., by fuzzy sets.…”
Section: ) Fuzzy Logicmentioning
confidence: 99%
“…Because linguistic values can be defined by classical sets per set or with some granular computing technique [182]. Therefore, a fuzzy system can be classified as a granular computation technique, where membership functions define linguistic values, i.e., by fuzzy sets.…”
Section: ) Fuzzy Logicmentioning
confidence: 99%
“…In this method, a study on Fuzzy logic has been conducted for solving the wireless positioning problems in wireless sensor network (WSN). The intension of the study is to include the parameters such as Fuzzy logic, its sets and interference in wireless sensor network (WSN) (Alakhras et al , 2020). However, it focuses on the positioning system in wireless sensor network (WSN) using the Fuzzy logic method.…”
Section: Related Workmentioning
confidence: 99%
“…Fuzzy Logic is the type of AI algorithms that aims to achieve intelligence by creating fuzzy logic of parameters involved in the application [73], [89]. One of the key advantages of fuzzy logic-based methods is the high interpretability as the outcome of these methods is understandable by a human.…”
Section: B Fuzzy Logicmentioning
confidence: 99%