scholarly journals Water Quality Indicator Interval Prediction in Wastewater Treatment Process Based on the Improved BES-LSSVM Algorithm

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 422
Author(s):  
Meng Zhou ◽  
Yinyue Zhang ◽  
Jing Wang ◽  
Yuntao Shi ◽  
Vicenç Puig
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Estimation Method ◽  
Bald Eagle ◽  
Computational Time ◽  
Support Vector ◽  
Effluent Water ◽  
Interval Prediction

This paper proposes a novel interval prediction method for effluent water quality indicators (including biochemical oxygen demand (BOD) and ammonia nitrogen (NH3-N)), which are key performance indices in the water quality monitoring and control of a wastewater treatment plant. Firstly, the effluent data regarding BOD/NH3-N and their necessary auxiliary variables are collected. After some basic data pre-processing techniques, the key indicators with high correlation degrees of BOD and NH3-N are analyzed and selected based on a gray correlation analysis algorithm. Next, an improved IBES-LSSVM algorithm is designed to predict the BOD/NH3-N effluent data of a wastewater treatment plant. This algorithm relies on an improved bald eagle search (IBES) optimization algorithm that is used to find the optimal parameters of least squares support vector machine (LSSVM). Then, an interval estimation method is used to analyze the uncertainty of the optimized LSSVM model. Finally, the experimental results demonstrate that the proposed approach can obtain high prediction accuracy, with reduced computational time and an easy calculation process, in predicting effluent water quality parameters compared with other existing algorithms.

The Application of Support Vector Regression Models which Based on MATLAB on the Simulation of Wastewater Treatment Plant

2013 ◽  
Vol 664 ◽  
pp. 197-201 ◽  
Author(s):  
Fu Guang Gu ◽  
Zhao Bo Chen ◽  
Hong Cheng Wang ◽  
Shun Li Zhang ◽  
Shu Kai Nie
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plant ◽  
Treatment Plant ◽  
Pso Algorithm ◽  
Parameters Optimization ◽  
Support Vector ◽  
Model Parameters ◽  
Feed Water ◽  
Water Quality Prediction

Mathematical modeling and simulation technology is a very important wastewater treatment plant data processing analysis tools. To analysis the wastewater treatment plant operation process, this study was realized on MATLAB and LIB-SVM tools. Determine the five feed water quality indexes (water inflow, pH, temperature, COD, MLSS) as input variables and the effluent COD concentration as output variable. Within the SVM modeling, through the GA algorithm, PSO algorithm and the grid search method to separately carried on the model parameters optimization. Through the verification results show that SVM model predicted the COD concentration average relative error is 0.0165, which has higher accuracy, which can meet the actual requirements of water quality prediction.

Simulation of wastewater treatment plant within integrated urban wastewater models

2010 ◽  
Vol 61 (10) ◽  
pp. 2645-2652 ◽  
Author(s):  
S. Heusch ◽  
B. Kamradt ◽  
M. Ostrowski
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Activated Sludge ◽  
Wastewater Treatment Plant ◽  
Planning Process ◽  
Treatment Plant ◽  
Federal State ◽  
Quality Model ◽  
Modelling Framework ◽  
Software Modelling

In the federal state of Hesse in Germany the application of an integrated software modelling framework is becoming part of the planning process to attain legal approval for the operation of combined sewer systems. The software allows for parallel simulation of flow and water quality routing in the sewer system and in receiving rivers. It combines existing pollution load model approaches with a simplified version of the River Water Quality Model No. 1 (RWQM1). Comprehensive simulation of the wastewater treatment plant (WWTP) is not considered yet. The paper analyses alternatives for the implementation of a WWTP module to model activated sludge plants. For both primary and secondary clarifiers as well as for the activated sludge process concepts for the integration into the existing software framework were developed. The activated sludge concept which uses a linearized version of the well known ASM1 model is presented in detail.

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