Enhancing carbon price point-interval multi-step-ahead prediction using a hybrid framework of autoformer and extreme learning machine with multi-factors

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126467 - 126467

Опубликована: Янв. 1, 2025

Язык: Английский

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Comparative Analysis of Influenza Modeling Using Novel Fractional Operators with Real Data

Symmetry, Год журнала: 2024, Номер 16(9), С. 1126 - 1126

Опубликована: Авг. 30, 2024

In this work, the efficacy of fractional models under Atangana–Baleanu–Caputo, Caputo–Fabrizio, and Caputo is compared to performance integer-order in forecasting weekly influenza cases using data from Kingdom Saudi Arabia. The suggested model was effectively verified calculus. Our investigation uncovered topic’s essential properties deepened our understanding disease progression. Furthermore, we analyzed numerical scheme’s positivity, limitations, symmetry. fractional-order demonstrated superior accuracy, producing smaller root mean square error (RMSE) absolute (MAE) than classical model. novelty work lies introducing Atangana–Baleanu–Caputo incorporate memory an epidemic, which leads higher accuracy traditional models. These captured peak drop cases. Based on these findings, it can be concluded that perform better typical when predicting dynamics. insights should illuminate importance calculus addressing epidemic threats.

Язык: Английский

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Breaking through the limitation of carbon price forecasting: A novel hybrid model based on secondary decomposition and nonlinear integration

Journal of Environmental Management, Год журнала: 2024, Номер 362, С. 121253 - 121253

Опубликована: Июнь 1, 2024

Язык: Английский

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Designing Home Automation Routines Using an LLM-Based Chatbot

Designs, Год журнала: 2024, Номер 8(3), С. 43 - 43

Опубликована: Май 13, 2024

Without any more delay, individuals are urged to adopt sustainable behaviors fight climate change. New digital systems mixed with engaging and gamification mechanisms could play an important role in achieving such objective. In particular, Conversational Agents, like Smart Home Assistants, a promising tool that encourage within household settings. recent years, large language models (LLMs) have shown great potential enhancing the capabilities of assistants, making them effective interacting users. We present design implementation GreenIFTTT, application empowered by GPT4 create control home automation routines. The agent helps users understand which energy consumption optimization routines be created applied make their appliances environmentally sustainable. performed exploratory study (Italy, December 2023) N = 13 participants test our application’s usability UX. results suggest GreenIFTTT is usable, engaging, easy, supportive tool, providing insight into new perspectives usage LLMs automation.

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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Using explainable deep learning to improve decision quality: Evidence from carbon trading market

Omega, Год журнала: 2025, Номер unknown, С. 103281 - 103281

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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Forecasting carbon price in Hubei Province using a mixed neural model based on mutual information and Multi-head Self-Attention

Journal of Cleaner Production, Год журнала: 2025, Номер unknown, С. 144960 - 144960

Опубликована: Фев. 1, 2025

Язык: Английский

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A novel probabilistic carbon price prediction model: Integrating the transformer framework with mixed-frequency modeling at different quartiles

Applied Energy, Год журнала: 2025, Номер 391, С. 125951 - 125951

Опубликована: Апрель 21, 2025

Язык: Английский

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Raw Material Stage Assessment of Seating Elements as Urban Furniture and Eco-Model Proposals

Sustainability, Год журнала: 2024, Номер 16(10), С. 4163 - 4163

Опубликована: Май 16, 2024

As cities strive to become sustainable, it is imperative consider even the smallest components of urban environment and prioritize sustainability. Ensuring sustainability furniture, especially numerous benches found in cities, crucial. This study proposes an alternative solution issue regarding furniture. because a review literature indicates that while efforts have been made evaluate amenities studies conducting life cycle analysis specifically for furniture are lacking. will contribute identified gap by analyzing 14 different seating elements recreational areas located city Rize, Turkey, using Ccalc program calculate their carbon footprints. In subsequent phase this study, eco-design process be conducted based on findings, aiming create eco-seating unit design. Based data obtained, materials with high environmental impact were identified, material replacement recommendations made, consequently, model proposal was presented. The potential reduction footprints use transformed discussed. findings revealed footprint values particularly units where concrete polypropylene used. Additionally, determined solvent paint, varnish, affects footprint, recommended would used its natural form, which eco-friendly. conclusion, developed coastal future humanity.

Язык: Английский

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