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Issue title: Special Section: Fuzzy theoretical model analysis for signal processing
Guest editors: Valentina E. Balas, Jer Lang Hong, Jason Gu and Tsung-Chih Lin
Article type: Research Article
Authors: Zhou, Weifenga | Hou, Juanb | Fan, Weic; * | Dai, Yangc
Affiliations: [a] East China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China | [b] Shanghai Ocean University, Shanghai, China | [c] Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture, Shanghai, China
Correspondence: [*] Corresponding author. Wei Fan, Key Laboratory of Oceanic and Polar Fisheries, Ministry of Agriculture, Shanghai, China, 200090. E-mail: fanwee@126.com.
Abstract: In this study, we develop a kind of location-based marine fishery information service method. The method is to use position and communication function of BeiDou navigation satellite system and shipborne marine environment monitoring sensors to obtain the location information, production data and marine environment data measured in situ, and then to extract the grid data around the target fishing vessel and transform these data into environment data in the form of vector. Then information service center takes the production data and environment data measured in situ as training sample to optimize the set fishing ground forecast model in accuracy and generalization. The model is used to calculate the fishing ground probability around the target fishing vessel. Finally, the information service center encodes the result of the forecast and related environment information together and send them to the target vessel. The method providing a location-based, vessel-oriented, customized and high-precision service, data generated from which is far less than those from some traditional methods, is cost-effective and easy to be popularized and applied by fishery operation departments.
Keywords: Marine fishery, information service, satellite navigation communication system, fishing ground forecasting
DOI: 10.3233/JIFS-179285
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 4, pp. 4523-4530, 2019
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