LAIK: Location-Specific Analysis to Infer Key Performance Indicators

Enami, Rita; Gupta, Sabyasachi; Rajan, Dinesh; Camp, Joseph

doi:10.1109/tvt.2021.3067880

Cited by 3 publications

(2 citation statements)

References 33 publications

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“…e experimental results show that the proposed effluent COD prediction model has high accuracy [8]. In addition, Enami and others designed an effluent quality prediction model based on an activated sludge mathematical model to obtain the correlation between effluent organic matter concentration, solid residence time, and internal circulation [9]. e results show that the proposed effluent quality model can accurately obtain the effluent quality characteristics of the urban sewage treatment process.…”

Section: Literature Reviewmentioning

confidence: 90%

“…In formula (9), g te k (x) is the Chebyshev value of the k-th subproblem, g te (x new ) is the Chebyshev value of the new solution, N is the number of subproblems decomposed, and i * is the sequence number of the most appropriate subproblem for the new solution. After finding this subproblem, the new solution and the old solution are replaced by comparing the Chebyshev values of all solutions and new solutions in the neighborhood; at the same time, for the subproblem that generates the new solution, the solutions in its neighborhood are not necessarily better than the new solution, so the optimal solution and the inferior solution are also replaced in the neighborhood of the original subproblem, so as to increase the utilization of the new solution and make the population converge more quickly.…”

Section: Ss-moea/d Algorithmmentioning

confidence: 99%

See 1 more Smart Citation

Intelligent Optimal Control of Sewage Treatment Based on Multiobjective Evolutionary Algorithm

Jia¹,

Xiang²,

Wang³

et al. 2022

Journal of Control Science and Engineering

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In order to solve the problem of optimal control of the sewage treatment process based on a multiobjective evolutionary algorithm, an intelligent optimal control of sewage treatment based on a multiobjective evolutionary algorithm is proposed in this paper. In this paper, the decomposition based multiobjective evolutionary algorithm (MOEA/D) is improved, and it is expected that the uniformly distributed approximate Pareto frontier can be obtained with fewer evolution times. For each new solution generated by the MOEA/D algorithm, the improved algorithm in this paper finds the most suitable subproblem for the new solution from all subproblems and replaces the population in its neighborhood. On the basis of the original subproblem, it carries out secondary optimization to improve the utilization rate of the children and then finds the approximate Pareto frontier in the optimization problem with fewer iterations. The experimental results show that AE, PE, and EC Based on SS–MOEA/D optimal control method are reduced by 6.91%, 1.54%, and 5.58%, respectively. Conclusion. The algorithm significantly reduces the number of steps to find the Pareto frontier, significantly improves the performance of the MOEA/D algorithm, and achieves the optimization goal in the optimization of the sewage treatment process.

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Section: Literature Reviewmentioning

confidence: 90%

Section: Ss-moea/d Algorithmmentioning

confidence: 99%