RETRACTED: Effect of combined air cooling and nano enhanced phase change materials on thermal management of lithium-ion batteries

Journal of Energy Storage, Год журнала: 2022, Номер 52, С. 104906 - 104906

Опубликована: Июнь 10, 2022

Язык: Английский

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RETRACTED ARTICLE: Nickel oxide nanoparticles synthesis using plant extract and evaluation of their antibacterial effects on Streptococcus mutans

Bioprocess and Biosystems Engineering, Год журнала: 2022, Номер 45(7), С. 1201 - 1210

Опубликована: Июнь 15, 2022

Язык: Английский

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Predicting compressive strength of manufactured-sand concrete using conventional and metaheuristic-tuned artificial neural network

Measurement, Год журнала: 2022, Номер 194, С. 110993 - 110993

Опубликована: Март 8, 2022

Язык: Английский

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A temporal fusion transformer for short-term freeway traffic speed multistep prediction

Neurocomputing, Год журнала: 2022, Номер 500, С. 329 - 340

Опубликована: Май 26, 2022

Язык: Английский

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Seasonal peak load prediction of underground gas storage using a novel two-stage model combining improved complete ensemble empirical mode decomposition and long short-term memory with a sparrow search algorithm

Energy, Год журнала: 2023, Номер 274, С. 127376 - 127376

Опубликована: Март 30, 2023

Язык: Английский

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Natural gas consumption forecasting using a novel two-stage model based on improved sparrow search algorithm

Journal of Pipeline Science and Engineering, Год журнала: 2024, Номер 5(1), С. 100220 - 100220

Опубликована: Авг. 23, 2024

The foundation of natural gas intelligent scheduling is the accurate prediction consumption (NGC). However, because its volatility, this brings difficulties and challenges in accurately predicting NGC. To address problem, an improved model developed combining sparrow search algorithm (ISSA), long short-term memory (LSTM), wavelet transform (WT). First, performance ISSA tested. Second, NGC divided into several high- low-frequency components applying different layers Coilfets', Fejer-Korovkins', Symletss', Haars', Discretes' orders. In addition, LSTM applied to forecast decomposed view one- multi-step, hyper-parameters are optimized by ISSA. At last, final results reconstructed. research indicate that: (1) Comparing other machine algorithms (e.g. fuzzy neural network), convergence speed stability stronger standard deviation mean; (2) better than that forecasting models; (3) single-step superior two-, three-, four- step; (4) computational load proposed highest compared models, accuracy still excellent on extended time series.

Язык: Английский

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Exploring the Nexus of Renewable Energy, Ecological Footprint, and Economic Growth through Globalization and Human Capital in G7 Economics

Sustainability, Год журнала: 2022, Номер 14(19), С. 12227 - 12227

Опубликована: Сен. 27, 2022

This study used panel simultaneous equations models with a generalized method of moments (GMM) estimator to examine the three-way linkages between ecological footprint (EFP), renewable energy consumption (REC), and income in Group Seven (G7) countries over period 1990–2018. The outcomes this demonstrate two-way association gross domestic product (GDP) energy. findings confirm presence bidirectional link outcome footprint, as well EFP results that improving human capital positively significantly effects income, environmental quality, REC. Ecological is not impacted by economic social globalization, whereas impact financial globalization negative significant. Trade openness connected REC which could contribute reducing deterioration. In conclusion, we make policy recommendations are based on study.

Язык: Английский

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Short-term renewable energy consumption and generation forecasting: A case study of Western Australia

Heliyon, Год журнала: 2022, Номер 8(3), С. e09152 - e09152

Опубликована: Март 1, 2022

Peer-to-Peer (P2P) energy trading has gained much attention recently due to the advanced development of distributed resources. P2P enables prosumers trade their surplus electricity and allows consumers purchase affordable locally produced renewable energy. Therefore, it is significant develop solutions that are able forecast consumption generation toward better power management, thereby making more accessible empowering make an informed decision on management. In this paper, several models for forecasting short-term generating developed discussed. Real-time datasets were collected from smart meters installed in residential premises Western Australia. These August 2018 Apr 2019 at fine time resolution down 5 s comprise import grid, export rooftop PV, households, outdoor temperature. Several The empirical results demonstrate superiority optimised deep learning-based Long Term Short Memory (LSTM) model both outperforms baseline as well alternative classical machine learning methods by a substantial margin.

Язык: Английский

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Diagnose Parkinson’s disease and cleft lip and palate using deep convolutional neural networks evolved by IP-based chimp optimization algorithm

Biomedical Signal Processing and Control, Год журнала: 2022, Номер 77, С. 103688 - 103688

Опубликована: Апрель 29, 2022

Язык: Английский

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Thermal Management of the Melting Process in a Latent Heat Triplex Tube Storage System Using Different Configurations of Frustum Tubes

Journal of Nanomaterials, Год журнала: 2022, Номер 2022(1)

Опубликована: Янв. 1, 2022

In this study, the energy charging mechanism is mathematically modeled to determine impact of design modifications on thermofluidic behavior a phase change material (PCM) filled in triplex tube containment geometry. The surface area middle tube, where PCM placed, supported by single or multi‐internal frustum tubes vertical increase performance heating and cooling system. addition ordinary straight tubes, three more scenarios are considered: (1) changing (2) inner (3) both internal central tubes. adopting designs gap width were studied. outcomes reveal that heat storage rates increased for all systems compared According results, case 5 mm optimal one among studied cases terms melting time rate. Employing configuration with 5‐mm would save 25.6% rate 32.8% base

Язык: Английский

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