Simulation and optimization of genetic algorithm-artificial neural network based air quality estimator

Pandey, Shirish; Saeed, Syed Hasan; Kidwai, Naimur Rahman

doi:10.11591/ijeecs.v19.i2.pp775-783

Cited by 6 publications

(4 citation statements)

References 28 publications

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“…In this section, the optimization result of the M-SCA has been compared with those of the genetic algorithm (GA), which is considered as one of the most powerful and widely used evolutionary algorithms [26]- [28], and the original sine cosine algorithm (SCA). Using the same comparison analysis of the previous section, 10 runs were made for each algorithm and the average of these runs was taken.…”

Section: A Comparsion Study With Other Optimization Techniquesmentioning

confidence: 99%

Control of a servo-hydraulic system utilizing an extended wavelet functional link neural network based on sine cosine algorithms

Mahdi

Lutfy

2022

IJEECS

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Servo-hydraulic systems have been extensively employed in various industrial applications. However, these systems are characterized by their highly complex and nonlinear dynamics, which complicates the control design stage of such systems. In this paper, an extended wavelet functional link neural network (EWFLNN) is proposed to control the displacement response of the servo-hydraulic system. To optimize the controller's parameters, a recently developed optimization technique, which is called the modified sine cosine algorithm (M-SCA), is exploited as the training method. The proposed controller has achieved remarkable results in terms of tracking two different displacement signals and handling external disturbances. From a comparative study, the proposed EWFLNN controller has attained the best control precision compared with those of other controllers, namely, a proportional-integralderivative (PID) controller, an artificial neural network (ANN) controller, a wavelet neural network (WNN) controller, and the original wavelet functional link neural network (WFLNN) controller. Moreover, compared to the genetic algorithm (GA) and the original sine cosine algorithm (SCA), the M-SCA has shown better optimization results in finding the optimal values of the controller's parameters.

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Section: A Comparsion Study With Other Optimization Techniquesmentioning

confidence: 99%

Control of a servo-hydraulic system utilizing an extended wavelet functional link neural network based on sine cosine algorithms

Mahdi

Lutfy

2022

IJEECS

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“…Genetic algorithm and neural network [24] An optimized air quality estimation model was developed based on a genetic algorithm and an artificial neural network.…”

Section: Wsn Based Aqm [19]mentioning

confidence: 99%

Free Hardware based System for Air Quality and CO2 Monitoring

Alvarez-Mendoza¹,

Vilchez-Lucana²,

Sierra-Liñan³

et al. 2022

IJACSA

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Due to the increase in air pollution, especially in Latin American countries of low and middle income, great environmental and health risks have been generated, highlighting that there is more pollution in closed environments. Given this problem, it has been proposed to develop a system based on free hardware for monitoring air quality and CO2, in order to reduce the levels of air pollution in a closed environment, improving the quality of life of people and contributing to the awareness of the damage caused to the environment by the hand of man himself. The system is based on V-Model, complemented with a ventilation prototype implemented with sensors and an application for its respective monitoring. The sample collected in the present investigation was non-probabilistic, derived from the reports of air indicators during 15 days with specific schedules of 9am, 1pm and 6pm. The results obtained indicated that the air quality decreased to 670 ppm, as well as the collection time decreased to 5 seconds and finally the presence of CO2 was reduced to 650 ppm after the implementation of the system, achieving to be within the standards recommended by the World Health Organization.

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“…However, GA is computationally expensive and requires careful parameter configuration [6]. GA has demonstrated exemplary performance when implemented in real-world problems, including optimizing CNN architecture with a transfer-learning strategy from parent networks [2], shortest path problem [9],optimizing ANN parameters [10], cryptoanalysis [11], community structure in complex networks [12], multi-objective in packing [13], scheduling [9], combinatorial configuration optimization [5], feature selection Ramdhani 2023 [14], intrution detection suhaimi [15]. There are at least five variants of genetic algorithms, namely real and binary-coded, multiobjective, parallel, chaotic, and hybrid GAs [8].…”

Section: Introductionmentioning

confidence: 99%

Improve Coal Blending Optimization in CFPP by Cromosom and Fitness Function Redefinition of the Genetic Algorithm

Solihah,

Zuhdi,

Rochman

et al. 2024

JUITA

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Blending coal before it enters the power plant boiler unit is necessary to adjust the coal categories according to the boiler unit specifications. The power plant must also comply with the regulations regarding coal-biomass co-firing through blending. Applying a Genetic Algorithm that only considers the composition and fitness based on the blend's quality leads to accumulation issues, decreasing coal quality. This research proposes redefining chromosomes, fitness functions, mutation rules, population determination, and output as the best chromosome used in the Genetic Algorithm. Testing uses various compositions of coal inputs from the barge, coal yard, and biomass to simulate different conditions. The test results demonstrate that the developed algorithm can provide all possible alternative blends between the coal in the barge and at the coal yard. Under specific conditions, operators can choose a blend composition that involves coal stored in the coal yard for an extended period.

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Simulation and optimization of genetic algorithm-artificial neural network based air quality estimator

Cited by 6 publications

References 28 publications

Control of a servo-hydraulic system utilizing an extended wavelet functional link neural network based on sine cosine algorithms

Control of a servo-hydraulic system utilizing an extended wavelet functional link neural network based on sine cosine algorithms

Free Hardware based System for Air Quality and CO2 Monitoring

Improve Coal Blending Optimization in CFPP by Cromosom and Fitness Function Redefinition of the Genetic Algorithm

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