Modeling and multi-objective optimization for ANAMMOX process under COD disturbance using hybrid intelligent algorithm.

Environmental Science and Pollution Research International
Bin XieZe-Yu Guan

Abstract

Anaerobic ammonium oxidation (ANAMMOX) has been regarded as an efficient process to treat nitrogen-containing wastewater. However, the treatment process is not fully understood in terms of reaction mechanisms, process simulation, and control. In this paper, a multi-objective control strategy mixed soft-sensing model (MCSSM) is developed to systematically design the operating variations for multi-objective control by integrating the developed model, a least square support vector machine optimized with principal component analysis (PCA-LSSVM) and non-dominated sorting genetic algorithm-II (NSGA-II). The results revealed that the PCA-LSSVM model is a feasible and efficient tool for predicting the effluent ammonia nitrogen concentration ([Formula: see text]) and the total nitrogen removal concentration (CTN, rem) with determination coefficients (R2) were 0.997 for [Formula: see text] and 0.989 for CTN, rem, and gives us the reasonable solutions in influent by using NSGA-II. To achieve a better removal effect, the influent pH should be kept between 7.50 and 7.52, the COD/TN ratio is suggested to maintain at 0.15 and the NH4+-N/NO2--N ratio is suggested to maintain at 0.61. The developed MCSSM approach and its general modeling framew...Continue Reading

References

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May 26, 2017·Environmental Science and Pollution Research International·Xiaoliang JiMinghua Zhang

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