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Method for predicting membrane pollution tendency in membrane distilled water processing system on the basis of GA-LSSVM (Genetic Algorithm- Least Squares Support Vector Machine) model

A processing system and model prediction technology, applied in the direction of electrical digital data processing, special data processing applications, instruments, etc., can solve problems such as difficult to determine the network topology, achieve fast prediction speed, good adaptability and prediction performance, and optimize high precision effect

Inactive Publication Date: 2015-09-23
HOHAI UNIV
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Problems solved by technology

However, ANN has the following disadvantages: 1. The prediction result is only a local minimum, not a global minimum; 2. It is difficult to determine its network topology; 3. It is prone to overfitting problems

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  • Method for predicting membrane pollution tendency in membrane distilled water processing system on the basis of GA-LSSVM (Genetic Algorithm- Least Squares Support Vector Machine) model
  • Method for predicting membrane pollution tendency in membrane distilled water processing system on the basis of GA-LSSVM (Genetic Algorithm- Least Squares Support Vector Machine) model
  • Method for predicting membrane pollution tendency in membrane distilled water processing system on the basis of GA-LSSVM (Genetic Algorithm- Least Squares Support Vector Machine) model

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Embodiment Construction

[0036] The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0037] like figure 1 Shown basic flowchart of the present invention, the method for predicting membrane fouling trend in membrane distilled water treatment system based on GA-LSSVM model, comprises the following steps:

[0038] The first step: use the LSSVM algorithm to establish a prediction model for the membrane distillation sewage treatment process; the specific process is as follows:

[0039] First, the input data is denoted as X, and the output data is denoted as Y, these data are divided into training data and test data, and the set of the training data is denoted as A={(x 1 ,y 1 ),…,(x i ,y i ),…,(x N ,y N )}, where x i ∈X,y i ∈Y, 1≤i≤N, N is the size of the training data set, use the nonlinear mapping function to establish the regression model of the following formula (1), and map the input data X to the high-dimensional fe...

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Abstract

The invention discloses a method for predicting a membrane pollution tendency in a membrane distilled water processing system on the basis of a GA-LSSVM (Genetic Algorithm- Least Squares Support Vector Machine) model. The method comprises the following steps: firstly, utilizing an LSSVM algorithm to establish a prediction model in a membrane distilled sewage processing process; secondly, utilizing a GA to optimize the parameter of the prediction model independently under a quasi-steady state and an unsteady state; thirdly, utilizing the optimized prediction model to predict the change tendency of membrane flux and membrane pollution resistance independently under a quasi-steady state and an unsteady state, and analyzing an influence on the membrane flux and the membrane pollution resistance by the basic operation parameter of membrane distilling; and finally, carrying out sensitivity analysis and calculation on a prediction result, and determining a leading factor which affects the membrane flux and the membrane pollution resistance. The method utilizes GA-LSSVM to predict a change situation of the membrane flux and the membrane pollution resistance in real time, and the influence on membrane pollution by the basic operation parameter of the membrane distilling is clarified and quantized.

Description

technical field [0001] The invention belongs to the field of membrane distillation technology and sewage and wastewater treatment, and in particular relates to a method for predicting the membrane fouling trend in a membrane distillation water treatment system based on a GA-LSSVM model. Background technique [0002] In recent years, membrane separation technology has developed rapidly, including nanofiltration membranes, ultrafiltration membranes, reverse osmosis membranes, and membrane distillation. Their rapid development provides new ways for urban sewage treatment and industrial wastewater treatment. Membrane distillation is a heat-driven process based on the principle of gas-liquid equilibrium and heat and mass transfer. With a microporous hydrophobic membrane as the medium, under the action of the vapor pressure difference on both sides of the membrane, the volatile components in the feed water pass through in the form of steam. Membrane pores condense into a liquid st...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/00
Inventor 陈琳刘畅朱亮靳斌斌赵苇航王俊
Owner HOHAI UNIV
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