Red tide early-warning method based on graph model construction

Abstract

The invention relates to a red tide early-warning method based on graph model construction. The method includes the following steps: step S1, data preprocessing is carried out; step S11, weight calculation is carried out; S12, environment factor dimensionality reduction is carried out; step S2, a DWFCM clustering algorithm is carried out; step S21, clustering center selection improvement is conducted; step S22, Euclidean distance weighting is conducted; step S23, objective function improvement is carried out; and S3, a red tide map data model is constructed. The method has the advantages thatred tide data can be classified according to generation stages and stored in a graph model according to the stages; red tide forecast personnel can quickly judge the stages of a red tide and take a control measure for the current stage in a targeted manner, so that the economic and ecological loss can be reduced; the red tide forecast personnel can conveniently check the needed data in an accurateand quick manner and rapid and accurate comprehensive data support can be provided for the red tide forecast personnel; and comparison control is carried out by using current data and historical data, and a generation stage of the red tide can be predicted.

Description

technical field [0001] The invention relates to the technical field of red tide data graph model construction, in particular to a red tide early warning method based on graph model construction. Background technique [0002] Red tide is one of the important factors affecting the marine environment. Red tide disasters occur frequently in the world, which is extremely harmful to ecological and economic systems. In 2003, a total of 119 red tides were found in my country's sea areas, with a cumulative area of ​​about 14,550 square kilometers, causing direct economic losses of up to 42.81 million yuan. In recent years, with the development of industry and agriculture near the coast and the increase of population, industrial wastewater and urban domestic sewage have been continuously discharged into the sea, resulting in an increase in the local nutrient level of seawater, which has led to a large increase in red tide organisms, resulting in frequent occurrence of red tides and in...

AI Technical Summary

Problems solved by technology

However, the use of relational databases to store red tide monitoring data has the following problems: First, the occurrence of a red tide is the result of the joint action of multiple influencing factors. Secondly, the continuous monitoring over the years has resulted in a huge amount of red tide monitoring data, and it will take a lot of time to find relevant data

However, regarding a method that can classify red tide data according to the stage of occurrence and store it in a graphical model by stage; red tide forecasters can quickly judge the stage of red tide, and put forward targeted prevention and control measures for the current stage, reducing economic and ecological costs. Loss; it is convenient for red tide forecasters to accurately and quickly query the required data, provide fast, accurate and comprehensive data support for red tide forecasters, use current data and historical data for comparison, and predict the occurrence of red tides. public

[0022] To sum up, there is a need for a method that can classify red tide data according to the stage of occurrence and store it in a graphical model by stage; red tide forecasters can quickly judge the stage of red tide, and put forward targeted prevention and control measures for the current stage. Reduce economic and ecological losses; facilitate red tide forecasters to accurately and quickly query the required data, provide fast, accurate and comprehensive data support for red tide forecasters, use current data and historical data for comparison, and predict the occurrence of red tide based on A red tide early warning method constructed by a graph model, but there is no report about this early warning method

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