Results 101 to 110 of about 44,389 (247)

Tomtit‐Raven Evolutionary Selector‐Reinforced Attention‐Driven: A High‐Performance and Computationally Efficient Cyber Threat Detection Framework for Smart Grids

Energy Science &Engineering, EarlyView.
Overview of the proposed work. ABSTRACT Identifying cyber threats maintains the security and operational stability of smart grid systems because they experience escalating attacks that endanger both operating data reliability and system stability and electricity grid performance.
Priya R. Karpaga, Praveen Kumar Balachandran, Umawathy Techanamurthy, Muhammad Ammirrul Atiqi Mohd Zainuri   +3 more
wiley   +1 more source

Predicting Parameters Affecting Building Energy Consumption Using Machine Learning Models

Energy Science &Engineering, EarlyView.
This framework integrates long‐term weather forecasting with building energy simulation to predict energy demand. The CNN–LSTM model achieved the highest accuracy (R2 ≈ 0.95), supporting smart HVAC control with ~ 15% energy savings. ABSTRACT The rapid growth of population and the construction industry have led to an increase in energy demand and an ...
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

Optimized Dual ANN Control Technique for Efficient Energy Management System (EMS) of Microgrid

Energy Science &Engineering, EarlyView.
Proposed methodology. ABSTRACT The escalating global energy demand necessitates a shift towards sustainable and environmentally friendly alternatives. While renewable energy sources like solar and wind energy offer promising solutions, their intermittent nature poses significant challenges for grid integration.
Bin Li, Bing Qi, Rashid Ali, Abubakar Siddique, Waseem Aslam, Hongfang Pan   +5 more
wiley   +1 more source

Examining Transnational Education in British Universities for Enhancing Internationalisation: The Impact of Constructivism on Alignment

Future in Educational Research, EarlyView.
ABSTRACT Transnational education (TNE) and the accelerating internationalisation of higher education demand pedagogical approaches that support deep learning across diverse contexts. Constructive alignment (CA) is widely adopted to align learning outcomes, teaching and assessment; however, its underlying constructivist rationale has weakened, creating ...
Samir Alamad
wiley   +1 more source

A Fuzzy Framework for Realized Volatility Prediction: Empirical Evidence From Equity Markets

Journal of Forecasting, EarlyView.
ABSTRACT This study introduces a realized volatility fuzzy time series (RV‐FTS) model that applies a fuzzy c‐means clustering algorithm to estimate time‐varying c$$ c $$ latent volatility states and their corresponding membership degrees. These memberships are used to construct a fuzzified volatility estimate as a weighted average of cluster centroids.
Shafqat Iqbal, Štefan Lyócsa
wiley   +1 more source

Hyperspectral Imaging Combined With Image Fusion Features and Machine Learning to Discriminate Different Origins, Grades, and Shelf‐Life of Oranges

Food Safety and Health, EarlyView.
This study verified that it is feasible to distinguish oranges of different origins, grades and shelf lives by using hyperspectral technology. It covers spectral, image and graph technologies, as well as machine learning and deep learning models. ABSTRACT This study reports the first application of hyperspectral feature fusion technology combined with ...
Honghui Xiao, Hao Hu, Hanyi Mei, Hao Deng, Yongzhi Zhang, Jing Nie, Hao Wu, Karyne M. Rogers, Yuwei Yuan, Chunlin Li   +9 more
wiley   +1 more source

Using Deep Learning Conditional Value‐at‐Risk Based Utility Function in Cryptocurrency Portfolio Optimisation

International Journal of Finance &Economics, EarlyView.
ABSTRACT One of the critical risks associated with cryptocurrency assets is the so‐called downside risk, or tail risk. Conditional Value‐at‐Risk (CVaR) is a measure of tail risks that is not normally considered in the construction of a cryptocurrency portfolio.
Xinran Huang, Linzhi Tan, Haozhe Su, Jeremy Eng‐Tuck Cheah   +3 more
wiley   +1 more source

Providing affective and supportive video feedback in a multidisciplinary unit during the pandemic

Journal of Learning Development in Higher Education, 2021
Abdul Razeed, Pat Norman, Kristna Gurney
doaj   +1 more source

Modeling human visuomotor adaptation with a disturbance observer framework. [PDF]

PLoS Comput Biol
Sharma G, 't Hart BM, Orban de Xivry JJ, Henriques DYP, Broucke ME.   +4 more
europepmc   +1 more source