Efficiency assessment and scenario simulation of the water-energy-food system in the Yellow river basin, China

Energy, Год журнала: 2024, Номер 305, С. 132279 - 132279

Опубликована: Июль 2, 2024

Язык: Английский

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Group dynamic game under bounded rationality in agreed transfer of China’s carbon trading secondary market

Computers & Industrial Engineering, Год журнала: 2025, Номер unknown, С. 110857 - 110857

Опубликована: Янв. 1, 2025

Язык: Английский

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Incorporating key features from structured and unstructured data for enhanced carbon trading price forecasting with interpretability analysis

Applied Energy, Год журнала: 2025, Номер 382, С. 125301 - 125301

Опубликована: Янв. 8, 2025

Язык: Английский

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Assessment and enhancement pathways of the Water-Energy-Food-Economy-Ecosystem Nexus in China's Yellow River Basin

Energy, Год журнала: 2025, Номер unknown, С. 134492 - 134492

Опубликована: Янв. 1, 2025

Язык: Английский

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A hybrid model for carbon price forecasting based on SSA-NSTransformer: Considering the role of multi-stage carbon reduction targets

Journal of Environmental Management, Год журнала: 2025, Номер 375, С. 124237 - 124237

Опубликована: Янв. 29, 2025

Язык: Английский

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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods

Mathematics, Год журнала: 2025, Номер 13(3), С. 464 - 464

Опубликована: Янв. 30, 2025

Carbon price forecasting and pricing are critical for stabilizing carbon markets, mitigating investment risks, fostering economic development. This paper presents an advanced decomposition-integration framework which seamlessly integrates econometric models with machine learning techniques to enhance forecasting. First, the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN) method is employed decompose data into distinct modal components, each defined by specific frequency characteristics. Then, Lempel–Ziv complexity dispersion entropy algorithms applied analyze these facilitating identification of their unique attributes. The subsequently employs GARCH predicting high-frequency components a gated recurrent unit (GRU) neural network optimized grey wolf algorithm low-frequency components. Finally, GRU model utilized integrate predictive outcomes nonlinearly, ensuring comprehensive precise forecast. Empirical evidence demonstrates that this not only accurately captures diverse characteristics different but also significantly outperforms traditional benchmark in accuracy. By optimizing optimizer (GWO) algorithm, enhances both prediction stability adaptability, while nonlinear integration approach effectively mitigates error accumulation. innovative offers scientifically rigorous efficient tool forecasting, providing valuable insights policymakers market participants trading.

Язык: Английский

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Enhanced accuracy and interpretability of nitrous oxide emission prediction of wastewater treatment plants through machine learning of univariate time series: A novel approach of learning feature reconstruction

Journal of Water Process Engineering, Год журнала: 2025, Номер 71, С. 107263 - 107263

Опубликована: Фев. 15, 2025

Язык: Английский

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Using the TSA-LSTM two-stage model to predict cancer incidence and mortality

PLoS ONE, Год журнала: 2025, Номер 20(2), С. e0317148 - e0317148

Опубликована: Фев. 20, 2025

Cancer, the second-leading cause of mortality, kills 16% people worldwide. Unhealthy lifestyles, smoking, alcohol abuse, obesity, and a lack exercise have been linked to cancer incidence mortality. However, it is hard. Cancer lifestyle correlation analysis mortality prediction in next several years are used guide people's healthy lives target medical financial resources. Two key research areas this paper Data preprocessing sample expansion design Using experimental comparison, study chooses best cubic spline interpolation technology on original data from 32 entry points 420 converts annual into monthly solve problem insufficient prediction. Factor possible because sources indicate changing factors. TSA-LSTM Two-stage attention popular tool with advanced visualization functions, Tableau, simplifies paper's study. Tableau's testing findings cannot analyze predict time series data. LSTM utilized by optimization model. By commencing input feature attention, model technique guarantees that encoder converges subset sequence features during output features. As result, model's natural learning trend quality enhanced. The second step, performance maintains We can choose network improve forecasts based real-time performance. Validating source factor using Most cancers overlapping risk factors, excessive drinking, exercise, obesity breast, colorectal, colon cancer. A poor directly promotes lung, laryngeal, oral cancers, according visual tests. expected climb 18-21% between 2020 2025, 2021. Long-term projection accuracy 98.96 percent, smoking may be main causes.

Язык: Английский

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How supply chain enterprises achieve coordination between green transition and profitability under the carbon trading framework

Journal of Environmental Management, Год журнала: 2025, Номер 377, С. 124588 - 124588

Опубликована: Фев. 21, 2025

Язык: Английский

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Deconstructing customer satisfaction recipes: A dynamic configurational framework leveraging the power of online reviews in tourism contexts

Tourism Management, Год журнала: 2025, Номер 110, С. 105181 - 105181

Опубликована: Март 17, 2025

Язык: Английский

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