Abstract
Similarity-based search has been a hot research topic for a long history, which is widely used in many applications. The large scale Restricted Floating Sensor (RFS) network is an important mod-el in offshore data collection [1]. Due to the mobility and the large number of sensors, improved techniques are needed to deal with uncertainty and mass queries. As a theoretical basis, this paper constructs a new fuzzy similarity measure based on distance. With examples we illustrate that many common similarity functions can be constructed from these measures. From [2] we know our work over distance and similarity is a reasonable generalization and extension of other Fuzzy Sets. This work provides a theoretical guidance for constructing a fuzzy query processing strategy for our RFS networks.
Highlights
There are significant interests in analyzing the siltation of the estuary and harbor
Similarity-based technologies are important in Restricted Floating Sensor (RFS) networks: firstly, RFSs are deployed on the sea collecting data of silt
Distinguished from traditional stat-ionary or mobile sensor networks, nodes in the RFS network will generally not be stationary at their original places, but float in a restricted area on the sea [1]
Summary
There are significant interests in analyzing the siltation of the estuary and harbor. Similarity-based technologies are important in RFS networks: firstly, RFSs are deployed on the sea collecting data of silt. Distinguished from traditional stat-ionary or mobile sensor networks, nodes in the RFS network will generally not be stationary at their original places, but float in a restricted area on the sea [1]. Our work is a reasonable extension of those on Fuzzy Set (FS), Intuitionistic Fuzzy Set (IFS) and Interval-Valued Intuitionistic Fuzzy Set (IVIFS) It is guidable on constructing similarity-based technologies for RFS networks.
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