Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

Galdo, María Isabel Lamas; Miranda, Javier Telmo; Lorenzo, José Manuel Rebollido; Caccia, Claudio Giovanni

doi:10.3390/ijerph182312823

Cited by 3 publications

(2 citation statements)

References 37 publications

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“…There is no exact rule to define the number of hidden layers and hidden nodes, and several methods to determine them can be found in the literature. Generally, a single hidden layer is recommended for most problems, and the multi-layered structure is only recommended for complex problems [35][36][37][38] since adding hidden layers may cause memorizing instead of generalizing [39]. Each input node has an assigned weight and transfer functions related to the nodes.…”

Section: Ann Analysismentioning

confidence: 99%

Optimization of a Nature-Inspired Shape for a Vertical Axis Wind Turbine through a Numerical Model and an Artificial Neural Network

et al. 2022

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The present work proposes an artificial neural network (ANN) to analyze vertical axis wind turbines of the Savonius type. These turbines are appropriate for low wind velocities due to their low starting torque. Nevertheless, their efficiency is too low. In order to improve the efficiency, several modifications are analyzed. First of all, an innovative blade profile biologically inspired is proposed. After that, the influence of several parameters such as the aspect ratio, overlap, and twist angle was analyzed through a CFD (computational fluid dynamics) model. In order to characterize the most appropriate combination of aspect ratio, overlap, and twist angle, an artificial neural network is proposed. A data set containing 125 data points was obtained through CFD. This data set was used to develop the artificial neural network. Once established, the artificial neural network was employed to analyze 793,881 combinations of different aspect ratios, overlaps, and twist angles. It was found that the maximum power coefficient, 0.3263, corresponds to aspect ratio 7.5, overlap/chord length ratio 0.1125, and twist angle 112°. This corresponds to a 32.4% increment in comparison to the original case analyzed with aspect ratio 1, overlap 0, and twist angle 0.

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Section: Ann Analysismentioning

confidence: 99%

Optimization of a Nature-Inspired Shape for a Vertical Axis Wind Turbine through a Numerical Model and an Artificial Neural Network

et al. 2022

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“…The evaluation of complex system schemes often involves many indicators, and the relationship between indicators is also complex. Conventional scheme decision-making methods mainly adopt the combination of qualitative and quantitative methods, and the fusion of objective information and subjective information, such as fuzzy optimization method (Xu and Zhao, 2008;Ignatius et al, 2018;Sitorus and Brito-Parada, 2022), grey relational analysis (GRA) (Xia et al, 2016;Tian et al, 2018;Cai et al, 2021), TOPSIS method (Liu and Zhang, 2014;Imam and Gurol, 2018), projection pursuit (PP) (Lan and Huang, 2018;Lee, 2018;Cho and Lee, 2021), analytic hierarchy process (AHP) (Wang et al, 2021;Yu et al, 2021;Ye and Chen, 2022) and artificial neural network (Galdo et al, 2021;Yuan et al, 2021;Leng and Huang, 2022). In the decision-making field of reservoir operation schemes, Zhu et al (2017b) used TOPSIS method, fuzzy optimization method and fuzzy matter-element method to rank all feasible flood control alternatives of multi-reservoir system, and the optimization scheme provides support for decision-making.…”

Section: Introductionmentioning

confidence: 99%

A decision-making method for reservoir operation schemes based on deep learning and whale optimization algorithm

Lin

et al. 2023

Front. Plant Sci.

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Reservoir operation is an important part of basin water resources management. The rational use of reservoir operation scheme can not only enhance the capacity of flood control and disaster reduction in the basin, but also improve the efficiency of water use and give full play to the comprehensive role the reservoir. The conventional decision-making method of reservoir operation scheme is computationally large, subjectivity and difficult to capture the nonlinear relationship. To solve these problems, this paper proposes a reservoir operation scheme decision-making model IWGAN-IWOA-CNN based on artificial intelligence and deep learning technology. In view of the lack of data in the original reservoir operation scheme and the limited improvement of data characteristics by the traditional data augmentation algorithm, an improved generative adversarial network algorithm (IWGAN) is proposed. IWGAN uses the loss function which integrates Wasserstein distance, gradient penalty and difference item, and dynamically adds random noise in the process of model training. The whale optimization algorithm is improved by introducing Logistic chaotic mapping to initialize population, non-linear convergence factor and adaptive weights, and Levy flight perturbation strategy. The improved whale optimization algorithm (IWOA) is used to optimize hyperparameters of convolutional neural networks (CNN), so as to obtain the best parameters for model prediction. The experimental results show that the data generated by IWGAN has certain representation ability and high quality; IWOA has faster convergence speed, higher convergence accuracy and better stability; IWGAN-IWOA-CNN model has higher prediction accuracy and reliability of scheme selection.

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Prediction of IC engine performance and emission parameters using machine learning: A review

Karunamurthy

Janvekar

Palaniappan

et al. 2023

J Therm Anal Calorim

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Internal Modifications to Optimize Pollution and Emissions of Internal Combustion Engines through Multiple-Criteria Decision-Making and Artificial Neural Networks

Cited by 3 publications

References 37 publications

Optimization of a Nature-Inspired Shape for a Vertical Axis Wind Turbine through a Numerical Model and an Artificial Neural Network

Optimization of a Nature-Inspired Shape for a Vertical Axis Wind Turbine through a Numerical Model and an Artificial Neural Network

A decision-making method for reservoir operation schemes based on deep learning and whale optimization algorithm

Prediction of IC engine performance and emission parameters using machine learning: A review

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