Identifying and prioritization barriers to renewable energy diffusion in developing countries: a novel spherical fuzzy AHP approach and application

Energy Efficiency, Год журнала: 2024, Номер 17(5)

Опубликована: Апрель 24, 2024

Язык: Английский

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Optimizing decision-making in electric power system selection: A generalized approach based on Hamacher aggregation operators for q-rung orthopair fuzzy soft sets

Applied Energy, Год журнала: 2024, Номер 367, С. 123405 - 123405

Опубликована: Май 13, 2024

Язык: Английский

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Ensuring environment sustainability through natural resources, renewable energy consumption, and inflation dynamics

Resources Policy, Год журнала: 2024, Номер 90, С. 104676 - 104676

Опубликована: Фев. 8, 2024

Язык: Английский

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The nexus between resource depletion, price fluctuations, and sustainable development in expenditure on resources

Resources Policy, Год журнала: 2024, Номер 89, С. 104629 - 104629

Опубликована: Янв. 12, 2024

Язык: Английский

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Mineral resources, tourism, human capital, and carbon neutrality: A path towards balanced and sustainable development

Resources Policy, Год журнала: 2024, Номер 90, С. 104756 - 104756

Опубликована: Фев. 17, 2024

Язык: Английский

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Transitioning to sustainable energy: Multidimensional factors guiding solar power technology adoption

Energy, Год журнала: 2024, Номер unknown, С. 133468 - 133468

Опубликована: Окт. 1, 2024

Язык: Английский

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Mineral resource volatility and green growth: The role of technological development, environmental policy stringency, and trade openness

Resources Policy, Год журнала: 2024, Номер 89, С. 104630 - 104630

Опубликована: Янв. 12, 2024

While natural resources significantly contribute to global socio-economic development, the unresolved question of their volatility's role in decoupling economic growth and carbon emissions persists. Previous empirical studies have underscored both positive negative impacts resource exploration on environment. This study addresses knowledge gap by employing a linear non-linear panel ARDL framework investigate correlation between re source volatility sustainable development BRICS economies. Our key findings reveal that adversely green within model short long run. Conversely, model, an increase negatively influences growth, whereas decrease encourages albeit only Moreover, we found technological stringent environmental policies, trade openness are conducive growth. These results underscore necessity for managing foster particularly emerging

Язык: Английский

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Sustainable energy transition optimization through decentralized hybrid energy systems with various energy storage technologies under multi-criterion indices: A mid-career repowering scenarios

Journal of Energy Storage, Год журнала: 2024, Номер 94, С. 112490 - 112490

Опубликована: Июнь 14, 2024

Язык: Английский

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Ensuring environment sustainability through natural resources, renewable energy consumption, and inflation dynamics

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

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LTPNet Integration of Deep Learning and Environmental Decision Support Systems for Renewable Energy Demand Forecasting

Journal of Organizational and End User Computing, Год журнала: 2025, Номер 37(1), С. 1 - 29

Опубликована: Фев. 21, 2025

Against the backdrop of increasingly severe global environmental changes, accurately predicting and meeting renewable energy demands has become a key challenge for sustainable business development. Traditional demand forecasting methods often struggle with complex data processing low prediction accuracy. To address these issues, this paper introduces novel approach that combines deep learning techniques decision support systems. The model integrates advanced techniques, including LSTM Transformer, PSO algorithm parameter optimization, significantly enhancing predictive performance practical applicability. Results show our achieves substantial improvements across various metrics, 30% reduction in MAE, 20% decrease MAPE, 25% drop RMSE, 35% decline MSE. These results validate model's effectiveness reliability forecasting. This research provides valuable insights applying

Язык: Английский

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