Method and system for judging aquaculture water regimen based on sensor risk interval model

Abstract

The invention discloses an aquaculture water regimen judgment method and system based on a sensor risk interval model. The method comprises the following steps: establishing an interval number representation model of aquaculture water regimen data, calculating the distance between water regimen measurement data [E] k obtained by a sensor and different water regimen level characteristic values represented by an interval number, and constructing a basic probability distribution function according to the distance; correcting the basic probability distribution function by using a pre-constructed negative-positive model based on a sensor risk interval value, and carrying out normalization processing on the corrected value; utilizing an interval evidence combination rule and integrating the normalized basic probability distribution function value to obtain a comprehensive interval evidence; and judging the water regimen level based on a predetermined decision criterion according to the comprehensive interval evidence. According to the method, interval number processing is carried out on the output of the sensor, the error coefficient is added into the output of the sensor, modeling is carried out on potential risks, the uncertainty of sensor measurement data is effectively eliminated, and the final precision of the system is improved.

Description

technical field [0001] The invention relates to the field of aquaculture water quality detection, in particular to a method and system for judging the aquaculture water regime based on multiple sensors. Background technique [0002] With the improvement of people's consumption demand for aquatic products, the requirements for the quality and output of aquaculture products are also getting higher and higher, and water quality parameters have a greater impact on the process of aquaculture, especially parameters such as temperature, dissolved oxygen, and PH value, and then It will also affect the quality and yield of farmed products. Therefore, monitoring changes in the fishery breeding environment and realizing automatic monitoring of water quality indicators is an indispensable guarantee for mastering the fishery environment and improving fishery production and fishery resource research. [0003] Most of the existing aquaculture water quality monitoring systems can only real...

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