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Effluent total phosphorus prediction method based on fuzzy neural network, electronic equipment and medium

A fuzzy neural network and effluent total phosphorus technology, applied in the field of water treatment, can solve the problems of long detection time of total phosphorus, inability to meet real-time detection, etc., and achieve the effect of solving low prediction accuracy

Pending Publication Date: 2021-06-15
XIAOHONGMEN SEWAGE TREATMENT PLANT BEIJING DRAINAGE GRP +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since sewage treatment is a long-term technological process, and the total phosphorus detection time is long, it cannot meet the requirements of real-time detection
It is problematic to carry out phosphorus removal operation when the total phosphorus is found to exceed the standard

Method used

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  • Effluent total phosphorus prediction method based on fuzzy neural network, electronic equipment and medium
  • Effluent total phosphorus prediction method based on fuzzy neural network, electronic equipment and medium
  • Effluent total phosphorus prediction method based on fuzzy neural network, electronic equipment and medium

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Experimental program
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Effect test

Embodiment 1

[0111] figure 1 A flowchart showing the steps of the fuzzy neural network-based method for predicting effluent total phosphorus according to an embodiment of the present invention.

[0112] Such as figure 1 As shown, the fuzzy neural network-based effluent total phosphorus prediction method includes: step 101, determining the characteristic variable of effluent total phosphorus as an input variable; step 102, constructing an initial prediction model based on fuzzy neural network; step 103, obtaining training samples and Input to the initial prediction model, and determine the final prediction model through the multi-objective particle swarm optimization algorithm; Step 104, input the input variables into the final prediction model, and calculate the total phosphorus in water.

[0113] According to the actual data of a sewage treatment plant in 2020, the influent water flow, redox potential in the middle of the anaerobic zone, redox potential in the front end of the anoxic zon...

Embodiment 2

[0145] The present disclosure provides an electronic device comprising: a memory storing executable instructions; a processor running the executable instructions in the memory to implement the fuzzy neural network-based effluent total phosphorus prediction method.

[0146] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0147] The memory is used to store non-transitory computer readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache). The non-volatile memory may include, for example, a read-only memory (ROM), a hard disk, a flash memory, and the like.

[0148] The processor may be a central processing unit (CPU) or other form of processing unit having dat...

Embodiment 3

[0152] An embodiment of the present disclosure provides a computer-readable storage medium, where a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the fuzzy neural network-based effluent total phosphorus prediction method is realized.

[0153] A computer-readable storage medium according to an embodiment of the present disclosure has non-transitory computer-readable instructions stored thereon. When the non-transitory computer-readable instructions are executed by the processor, all or part of the steps of the aforementioned methods in the various embodiments of the present disclosure are executed.

[0154] The above-mentioned computer-readable storage media include but are not limited to: optical storage media (for example: CD-ROM and DVD), magneto-optical storage media (for example: MO), magnetic storage media (for example: magnetic tape or mobile hard disk), Media that rewrites nonvolatile memory...

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Abstract

The invention discloses an effluent total phosphorus prediction method based on a fuzzy neural network, electronic equipment and a medium. The method comprises the following steps: determining a characteristic variable of effluent total phosphorus as an input variable; constructing an initial prediction model based on a fuzzy neural network; obtaining a training sample, inputting the training sample into the initial prediction model, and determining a final prediction model through a multi-target particle swarm optimization algorithm; and inputting the input variable into the final prediction model, and calculating the total phosphorus in the effluent. According to the method, a prediction model based on the fuzzy neural network is established to predict the effluent total phosphorus, an asymmetric membership function is adopted to describe the distribution characteristics of variable data, a multi-target particle swarm optimization algorithm is utilized to dynamically adjust the structure and parameters of the fuzzy neural network at the same time, and real-time prediction of the effluent total phosphorus concentration of sewage treatment is achieved.

Description

technical field [0001] The invention relates to the field of water treatment, more specifically, to a fuzzy neural network-based prediction method for effluent total phosphorus, electronic equipment and media. Background technique [0002] In the past 100 years, the global water consumption has increased by 6 times, and due to factors such as population and economy, the water consumption is still growing at a rate of about 1% per year, which exacerbates the current water shortage situation and makes the use of water resources face serious challenges. more severe pressure. With the increasing demand for water resources and the increasing amount of sewage generated, the treatment and reuse of sewage has become the focus in recent years; at the same time, doing a good job in sewage treatment is an important step to improve environmental quality and promote green development. Therefore, it is of great significance to study the process of urban sewage treatment to provide scient...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G16C20/20G16C20/70G06N3/04G06N3/08
CPCG16C20/20G16C20/70G06N3/086G06N3/043G06N3/045
Inventor 郑江顾剑阜葳韩红桂何政王欢欢赵楠孙晨暄乔俊飞
Owner XIAOHONGMEN SEWAGE TREATMENT PLANT BEIJING DRAINAGE GRP
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