Results 161 to 170 of about 118,488 (274)

Bayesian neural network-based policy effect prediction for green transformation of power business environment. [PDF]

Sci Rep
Shen Y, Chen J, Wang W, Wu Q, Jiang D, Xia S.   +5 more
europepmc   +1 more source

AI‐Driven Optimization of a Hybrid PV–Wind–BESS Microgrid for a Rural Educational Institution in Developing Countries

Energy Science &Engineering, EarlyView.
An AI‐driven CNN–LSTM forecasting framework is integrated with HOMER Pro to optimally design a grid‐connected PV–wind–BESS microgrid for a rural school in Bangladesh, achieving 91.7% renewable penetration, low energy cost (0.0397 USD/kWh), and an 81.5% reduction in CO2 emissions. ABSTRACT Hybrid renewable microgrid planning in HOMER Pro often relies on
Robiul Khan, Md. Wajed Ali, Md. Feroz Ali, Md. Shafiul Alam, Mohammad Ali, Imil Hamda Imran   +5 more
wiley   +1 more source

UncerTrans: uncertainty-aware temporal transformer for early action prediction. [PDF]

Sci Rep
Zhai X, Liu Y.
europepmc   +1 more source

Feasibility of Wind‐Powered Green Hydrogen Production via a Hybrid Graph Neural Network‐Transformer Forecasting Model

Energy Science &Engineering, EarlyView.
ABSTRACT Accurate long‐term wind speed forecasting is pivotal for the strategic planning of renewable energy infrastructure, particularly for assessing the techno‐economic feasibility of wind‐powered green hydrogen facilities. However, capturing the complex spatiotemporal dependencies in climate data remains a significant challenge. This study proposes
Iman Baghaei, Mojtaba Mirhosseini, Alireza Zahedi   +2 more
wiley   +1 more source

Graph Neural Networks Model Based on Atomic Hybridization for Predicting Drug Targets. [PDF]

J Chem Inf Model
Mohamed A, Galal N, Brooks BR, Amin M.
europepmc   +1 more source

Environmental Control for Edible Fungi Cultivation Based on Temporal Information and Deep Learning

Food Bioengineering, EarlyView.
ABSTRACT Currently, there are still prevalent issues in greenhouse environmental regulation, such as response lag, low control accuracy, and difficulty in coping with sudden environmental disturbances. To achieve high‐precision and dynamic control of the edible fungi cultivation environment, this study proposes an edible fungi environmental control ...
Xiangyan Wang, Shuangcheng Huang, Qingbo Lu, Xinyi Guo   +3 more
wiley   +1 more source

A novel intrusion detection framework using hybrid deep learning to detect IIoT cloud environments attacks. [PDF]

Sci Rep
Chen S, Feng X.
europepmc   +1 more source

High‐performance heat‐resistant tactile sensor for intelligent sensing and safe operation

FlexMat, EarlyView.
Abstract Tactile sensing in high‐temperature environments remains a critical challenge for robotic systems operating in industrial manufacturing, food processing, and other high‐temperature assembly operations. Herein, we report a heat‐resistant flexible tactile sensor with comprehensive high performance, featuring a hierarchical architecture ...
Yugang Chen, Shasha Wang, Haopeng Wang, Xun Fu, Qifei Lv, Shuting Xie, Yan Li, Jiangtian Tan, Linghai Xie   +8 more
wiley   +1 more source

ConvCGP: A convolutional neural network to predict genetic values of agronomic traits from compressed genome-wide polymorphisms. [PDF]

Plant Genome
Raihan T, Kim CH, Shimono H, Kimura A, Iwata H.   +4 more
europepmc   +1 more source

A Deep Learning Framework for Forecasting Medium‐Term Covariance in Multiasset Portfolios

Journal of Forecasting, EarlyView.
ABSTRACT Forecasting the covariance matrix of asset returns is central to portfolio construction, risk management, and asset pricing. However, most existing models struggle at medium‐term horizons, several weeks to months, where shifting market regimes and slower dynamics prevail.
Pedro Reis, Ana Paula Serra, João Gama
wiley   +1 more source