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Sewage energy saving processing optimization control method based on improved firefly algorithm and least squares support vector machine

A technology of support vector machine and firefly algorithm, which is applied in the field of energy-saving optimization of sewage treatment, which can solve the problems of large changes in sewage concentration and inability to optimize the water quality and energy consumption of sewage treatment.

Pending Publication Date: 2017-08-22
HUNAN UNIV OF TECH
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Problems solved by technology

In actual operation, external factors affecting sewage treatment are changeable. The concentration of sewage varies greatly in different climates and time periods. This constant set value of dissolved oxygen concentration and nitrate nitrogen concentration cannot realize the water quality and quality of sewage treatment. To optimize energy consumption, the set value of the controller must be optimally designed

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  • Sewage energy saving processing optimization control method based on improved firefly algorithm and least squares support vector machine
  • Sewage energy saving processing optimization control method based on improved firefly algorithm and least squares support vector machine
  • Sewage energy saving processing optimization control method based on improved firefly algorithm and least squares support vector machine

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Embodiment Construction

[0083] Based on the improved firefly algorithm, the least squares support vector machine predicts the sewage energy-saving treatment control system, including the following two stages:

[0084] Phase 1: Establishment of a prediction model based on the improved firefly algorithm and the least squares support vector machine, including the following sequential steps:

[0085] Step A1: The sewage treatment process: the dissolved oxygen concentration, the set value of the nitrate nitrogen concentration, and the influent flow rate are used as the input of the model, and the energy consumption used in the sewage treatment process and the effluent water quality index are used as the model output. Collect the historical data and experimental data of the sewage treatment plant, eliminate the abnormal data, and perform normalized preprocessing on the original sample data.

[0086] Step A2: Use the multi-core least squares support vector machine to model, determine the kernel function and...

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Abstract

The invention discloses a sewage energy saving processing optimization control method based on an improved firefly algorithm and a least squares support vector machine, and belongs to the field of intelligent control. The method comprises steps of using a multicore least squares support vector machine to model energy consumption and water quality of discharged water of a sewage processing factory; using the improved firefly algorithm to optimize established model parameters; and using the improved firefly algorithm to optimize a set value of the controller. According to the invention, the least squares support vector machine is used for modeling energy consumption and water quality of discharged water of a sewage processing factory; a multi-core idea is introduced; the improved firefly algorithm is used for optimizing model parameters, so accuracy of an energy consumption model and a discharged water quality model is greatly improved; the improved firefly algorithm is used for carrying out online optimization on set values of dissolved oxygen concentration and nitrate nitrogen concentration of the controller, so under the premise of meeting the discharged water quality, the energy consumption of the sewage processing factor is reduced; an objective of saving energy and carrying out optimization in the sewage processing process is obtained; and compared with other algorithms, the method is characterized by simple algorithm, few used parameters and high convergence accuracy.

Description

technical field [0001] The invention proposes a method for energy-saving optimization control of a sewage treatment process. Specifically, it is a sewage energy-saving treatment control system based on improved firefly algorithm and support vector machine prediction model. The firefly algorithm based on adaptive inertia weight is used to optimize the least squares support vector machine's predicted energy consumption and effluent water quality model, which greatly improves the accuracy of the model; comprehensively considers the aeration and pumping when the effluent water quality is satisfied. The energy consumption is reduced as much as possible, and the energy-saving optimization control of sewage treatment is realized. The invention relates to the technical field of energy-saving optimization of sewage treatment. Background technique [0002] With the increase of population and the rapid development of economy and society, the problem of water pollution has become incre...

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 秦斌张俊杰王欣
Owner HUNAN UNIV OF TECH
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