Method and system for optimizing and predicting dissolved oxygen based on hybrid QPSO-DE optimization

Abstract

The invention discloses a method and a system for optimizing and predicting dissolved oxygen based on hybrid QPSO-DE, and the method comprises the steps: carrying out the optimization design of parameters of a support vector machine through employing a QPSO-DE algorithm, setting the support vector machine obtained through optimization design as an optimization prediction dissolved oxygen model, and obtaining dissolved oxygen prediction data. Compared with a standard differential evolution algorithm, the invention has the advantages that the search capability is stronger, the performance is better, individuals entering the next generation in each iteration have better fitness values, the premature phenomenon of the algorithm can be effectively avoided, that is, the algorithm falls into local optimum and cannot jump out, and the global search capability of the algorithm is improved.

Description

technical field [0001] The present disclosure relates to the technical field of artificial intelligence, in particular to a method and system for optimizing and predicting water quality dissolved oxygen based on hybrid QPSO-DE. Background technique [0002] my country is a country with a large aquaculture industry. As a kind of aquaculture production activities, aquaculture plays a decisive role in the aquaculture industry. In aquaculture, water quality has an important impact on the growth of aquatic animals and plants. The quality of water greatly affects the health of aquatic organisms. Poor water quality may make fish become intermediate hosts, which in turn transmit parasites. To human beings, thereby bringing great harm to human health. With the improvement of the intensive culture of aquaculture, water quality management has become one of the most concerned issues in the aquaculture industry. If the future water quality changes can be predicted more accurately, it c...

AI Technical Summary

Problems solved by technology

[0005] (1) In terms of water quality research, it is very difficult to obtain basic data. Due to the influence of various environmental and economic factors, it is difficult for us to obtain long-term, continuous and complete monitoring data. The factors affecting water quality are complex and multifaceted. It is obviously of great practical significance to further do a good job in the research of dissolved oxygen prediction, how to effectively obtain long-term and stable data

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