Results 181 to 190 of about 51,613 (264)

A Hybrid Fuzzy–Support Vector Machine Framework for Real‐Time Dust Detection and Thermal Mapping in Photovoltaic Panels

Energy Science &Engineering, EarlyView.
A hybrid Fuzzy–SVM framework for real‐time dust detection and thermal mapping in PV panels. ABSTRACT Dust accumulation significantly degrades the energy output of photovoltaic (PV) panels, particularly in arid and semi‐arid regions. While existing studies have separately explored image‐based dust detection, environmental modeling, and machine learning (
Debasish Sarker, S. M. Rezaul Karim, MD. Shouquat Hossain, Md. Moshaddek Hossain, Md. Monirul Kabir   +4 more
wiley   +1 more source

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

Energy Science &Engineering, EarlyView.
Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga, Subhasish Deb, Kshetrimayum Robert Singh, Subir Datta, Ahmet Onen, Taha Selim Ustun, Jaesung Jung   +6 more
wiley   +1 more source

QoE collaborative evaluation method based on fuzzy clustering heuristic algorithm. [PDF]

Springerplus, 2016
Bao Y, Lei W, Zhang W, Zhan Y.
europepmc   +1 more source

Intelligent Control Framework of District Heating Systems Considering Waste Heat Utilization in Data Centers

Energy Science &Engineering, EarlyView.
A deep reinforcement learning–based control architecture is proposed to coordinate heat pumps, thermal storage, renewable energy, and demand response in data center waste heat recovery systems. The agent learns optimal control actions from system states and reward feedback to achieve electrical–thermal co‐optimization under realistic operational ...
Rendong Shen, Ruifan Zheng, Shengyuan Zhong, Lei Gu, Dongfang Yang, Jun Zhao   +5 more
wiley   +1 more source

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors

Energy Science &Engineering, EarlyView.
Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen, Linming Dou, Atao Li, Wu Cai, Lei Zhang   +4 more
wiley   +1 more source

Multifactorial Screening for Fine‐Scale Selection of CCS Industrial Clusters and Hubs in Brazil

Greenhouse Gases: Science and Technology, EarlyView.
ABSTRACT As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as a key pathway for large‐scale CO2 abatement in hard‐to‐abate sectors. This paper presents a multifactorial, data‐driven framework to screen and prioritize potential CCS industrial clusters and hubs across Brazilian regions,
Gustavo P. Oliveira, Beatriz R. Almeida, Thiago R. C. Justino, Carlos A. S. Santos, Alex A. Santos, Fabiana Philipi   +5 more
wiley   +1 more source

Technological Evolution in Fintech: A Decadal Scientometric and Systematic Review of Developments and Criticisms

International Journal of Finance &Economics, EarlyView.
ABSTRACT This study aims to classify pivotal fintech innovations and explore the prospects and pitfalls associated with emerging fintech services extensively discussed in the literature. We conducted a multistage systematic review of research published on fintech over the past decade from a technological perspective. Using the Preferred Reporting Items
Muhammad Imran Qureshi, Nohman Khan
wiley   +1 more source

Recent advances in data‐driven and artificial intelligence‐integrated perovskite solar cells: From design to self‐driving laboratories

InfoMat, EarlyView.
To address the limitations of conventional trial‐and‐error approaches, perovskite solar cell research is shifting toward a new paradigm that utilizes datasets and AI. This review examines the fundamental elements of data‐driven and AI‐integrated research: data platforms, AI methodologies, and self‐driving laboratories, demonstrating how their ...
Jaehee Lee, Juhwan Noh, Hyunjun Lee, Yea‐Lee Lee, Jino Im, Jangwon Seo   +5 more
wiley   +1 more source

Count Data Models With Heterogeneous Peer Effects Under Rational Expectations

Journal of Applied Econometrics, EarlyView.
ABSTRACT This paper develops a peer effect model for count responses under rational expectations. The model accounts for heterogeneity in peer effects across groups based on observed characteristics. Identification is based on the linear model condition that requires the presence of friends of friends who are not direct friends.
Aristide Houndetoungan
wiley   +1 more source

Toward an idiographic understanding of the role of sleep‐mood dynamics in adolescents' internalizing symptoms

JCPP Advances, EarlyView.
Abstract Background Adolescence is marked by increased vulnerability to sleep disturbances and mood disorders. Understanding how day‐to‐day changes in sleep and mood are linked within the same individual is crucial for clarifying sleep's role in emerging internalizing disorders. However, the extent to which an adolescent's fluctuations in sleep predict
Konstantin Drexl, Setareh Ranjbar, Sébastien Urben, Kerstin Jessica Plessen, Jennifer Glaus   +4 more
wiley   +1 more source