2023
DOI: 10.1038/s41598-023-30099-9
|View full text |Cite
|
Sign up to set email alerts
|

Modified Whale Optimization Algorithm based ANN: a novel predictive model for RO desalination plant

Abstract: In recent decades, nature-inspired optimization methods have played a critical role in helping industrial plant designers to find superior solutions for process parameters. According to the literature, such methods are simple, quick, and indispensable for saving time, money, and energy. In this regard, the Modified Whale Optimization Algorithm (MWOA) hybridized with Artificial Neural Networks (ANN) has been employed in the Reverse Osmosis (RO) desalination plant performance to estimate the permeate flux (0.118… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
19
0

Year Published

2023
2023
2025
2025

Publication Types

Select...
8
1

Relationship

0
9

Authors

Journals

citations
Cited by 24 publications
(19 citation statements)
references
References 52 publications
0
19
0
Order By: Relevance
“…High metrics were also obtained by the other algorithms implemented in the following two top models. Even though modified particle swarm optimization (modified PSO), modified genetic algorithm (modified GA) and modified grew wolf optimization (modified GWO) [82][83][84][85][86][87][88] can be found as the latest optimization algorithms for minimizing errors in desalination systems, the high accuracy and precision of the developed in the paper AID system is also reported. According to Table 3, the best turned out to be the Gradient Boosted Tree Classifier.…”
Section: Resultsmentioning
confidence: 99%
“…High metrics were also obtained by the other algorithms implemented in the following two top models. Even though modified particle swarm optimization (modified PSO), modified genetic algorithm (modified GA) and modified grew wolf optimization (modified GWO) [82][83][84][85][86][87][88] can be found as the latest optimization algorithms for minimizing errors in desalination systems, the high accuracy and precision of the developed in the paper AID system is also reported. According to Table 3, the best turned out to be the Gradient Boosted Tree Classifier.…”
Section: Resultsmentioning
confidence: 99%
“…The WOA algorithm is efficient, has fast convergence and high accuracy in handling the process of finding the optimal solution. It has the ability to jump out of the local optimum with fewer adjustment parameters [38]. Therefore, the WOA algorithm is proposed to optimize the temperature compensation method of the BP neural network, and its specific process is given as follows:…”
Section: Woa Optimizes Bp Neural Networkmentioning
confidence: 99%
“…The number of nodes in the input layer was 5, which were respectively the concentration of five elements measured by the instrument. According to equation (3) [27], the number of nodes in the hidden layer was determined to be 11 after enumeration [28]. And the number of nodes in the output layer was 1, which was the concentration of elements after calibration.…”
Section: Bp-ann Modelmentioning
confidence: 99%