2020•Journal of Coastal ResearchRequires access

Marine Disaster Prediction Based on Mathematical Model

Guo'an Wang

Open publisher page 4 citations

Abstract

Wang, G.-A., 2020. Marine disaster prediction based on mathematical model. In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 230-233 . Coconut Creek (Florida), ISSN 0749-0208.China is a large marine country with a long coastline, which is 18000 kilometers long. Therefore, marine disasters occur frequently in China's coastal areas. Since 1989 to 2017, marine disasters have caused serious economic losses to China, totaling about 346.8 billion yuan, and the number of deaths and missing persons has reached 7054. At the same time, with the aggravation of global warming, green tide, red tide, typhoon and other natural disasters gradually increase. With the increasing frequency of marine disasters, great economic losses have been caused in coastal areas of China. Marine disasters have many characteristics, which are open and dynamic. By analyzing and solving the causes of marine disasters, we can better predict disasters. Therefore, we need to predict marine disasters, which will better plan and use marine resources and reduce the loss of marine disasters. Firstly, this paper analyzes the basic characteristics of marine disasters. Then, this paper introduces the data model of SVM. Then, the paper forecasts the green tide disaster. Finally, some suggestions are put forward.

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What this paper is about

Wang, G.-A., 2020. Marine disaster prediction based on mathematical model. In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 230-233 . Coconut Creek (Florida), ISSN 0749-0208.China is a large marine country with a long coastline, which is 18000 kilometers long. Therefore, marine disasters occur frequently in China's coastal areas. Since 1989 to 2017, marine disasters have caused serious economic losses to China, totaling about 346.8 billion yuan, and the number of deaths and missing persons has reached 7054. At the same time, with the aggravation of global warming, green tide, red tide, typhoon and other natural disasters gradually increase. With the increasing frequency of marine disasters, great economic losses have been caused in coastal areas of China. Marine disasters have many characteristics, which are open and dynamic. By analyzing and solving the causes of marine disasters, we can better predict disasters. Therefore, we need to predict marine disasters, which will better plan and use marine resources and reduce the loss of marine disasters. Firstly, this paper analyzes the basic characteristics of marine disasters. Then, this paper introduces the data model of SVM. Then, the paper forecasts the green tide disaster. Finally, some suggestions are put forward.

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Available abstract

Wang, G.-A., 2020. Marine disaster prediction based on mathematical model. In: Qiu, Y.; Zhu, H., and Fang, X. (eds.), Current Advancements in Marine and Coastal Research for Technological and Sociological Applications. Journal of Coastal Research, Special Issue No. 107, pp. 230-233 . Coconut Creek (Florida), ISSN 0749-0208.China is a large marine country with a long coastline, which is 18000 kilometers long. Therefore, marine disasters occur frequently in China's coastal areas. Since 1989 to 2017, marine disasters have caused serious economic losses to China, totaling about 346.8 billion yuan, and the number of deaths and missing persons has reached 7054. At the same time, with the aggravation of global warming, green tide, red tide, typhoon and other natural disasters gradually increase. With the increasing frequency of marine disasters, great economic losses have been caused in coastal areas of China. Marine disasters have many characteristics, which are open and dynamic. By analyzing and solving the causes of marine disasters, we can better predict disasters. Therefore, we need to predict marine disasters, which will better plan and use marine resources and reduce the loss of marine disasters. Firstly, this paper analyzes the basic characteristics of marine disasters. Then, this paper introduces the data model of SVM. Then, the paper forecasts the green tide disaster. Finally, some suggestions are put forward.

Key concepts: Geology, Oceanography, Computer science

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