Results 141 to 150 of about 108,415 (292)

Deep Q-Learning for Nash Equilibria: Nash-DQN

, 2019
Model-free learning for multi-agent stochastic games is an active area of research. Existing reinforcement learning algorithms, however, are often restricted to zero-sum games, and are applicable only in small state-action spaces or other simplified ...
Casgrain, Philippe, Jaimungal, Sebastian, Ning, Brian   +2 more
core  

AI‐based localization of the epileptogenic zone using intracranial EEG

Epilepsia Open, EarlyView.
Abstract Artificial intelligence (AI) is rapidly transforming our lives. Machine learning (ML) enables computers to learn from data and make decisions without explicit instructions. Deep learning (DL), a subset of ML, uses multiple layers of neural networks to recognize complex patterns in large datasets through end‐to‐end learning.
Atsuro Daida, Yipeng Zhang, Sotaro Kanai, Richard Staba, Vwani Roychowdhury, Hiroki Nariai   +5 more
wiley   +1 more source

Assessment of Voltage Unbalance and Power Losses in Distribution Network Integrated With PVs and EV Charging Stations

Energy Science &Engineering, EarlyView.
ABSTRACT Unequal load distribution in three‐phase power distribution networks leads to voltage unbalance and decreased network efficiency. Integration of photovoltaics (PVs) and electric vehicle charging stations (EVCSs) into such networks is a challenging task as their penetration affects the power quality of the system.
Maaz Ahmad, Aamir Nawaz, Rahmat Ullah, Ehtasham Mustafa, Abdelfatah Ali   +4 more
wiley   +1 more source

High‐Fidelity Simulation‐Driven Control Framework for Robust Grid Integration of Renewable Energy Systems

Energy Science &Engineering, EarlyView.
This work proposes a high‐fidelity, simulation‐driven control framework for robust grid integration of hybrid PV–wind systems using a modular, hierarchical multi‐loop architecture with adaptive decision logic. The framework coordinates power, DC‐link voltage, and grid currents under fast load and generation changes, enabling safe exploration of extreme
Wulfran Fendzi Mbasso, Ambe Harrison, Idriss Dagal, Pradeep Jangir, Zhe Liu, Aseel Smerat   +5 more
wiley   +1 more source

Bi‐Level Coordination of Demand Response and Multiple Virtual Power Plants in a Distribution Network for Flexibility Assessment

Energy Science &Engineering, EarlyView.
This study presents a hierarchical coordination framework where multiple VPPs interact with the DSO to optimize energy trades and flexibility offers. Each VPP aggregates DERs and DR, performing internal optimization, day‐ahead bidding, and assessing flexibility to reduce excess renewable generation and pollution.
Alireza Zare, Mohammad Agha Shafiyi, Mehrdad Setayesh Nazar, Miadreza Shafie‐khah, Pierluigi Siano   +4 more
wiley   +1 more source

On the maxmin value of stochastic games with imperfect monitoring [PDF]

We study zero-sum stochastic games in which players do not observe the actions of the opponent. Rather, they observe a stochastic signal that may depend on the state, and on the pair of actions chosen by the players.
ROSENBERG, Dinah, SOLAN, Eilon, VIEILLE, Nicolas   +2 more
core  

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

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

Material ESG Performance and Bid Premium in Merger and Acquisition Deals

International Journal of Finance &Economics, EarlyView.
ABSTRACT This study examines the firm‐level and country‐level environmental, social, and governance (ESG) performance on bid premiums in cross‐border mergers and acquisitions (M&A) transactions. We document considerable variations in bid premiums. Higher carbon emissions are associated with higher bid premiums, suggesting that acquirers may perceive ...
Ndubuisi Ezenwa, Ibrahim Ayoade Adekunle, Robin Maialeh   +2 more
wiley   +1 more source

Interplay Between Green Investment and Market Price Premia in Global Shipping

International Journal of Finance &Economics, EarlyView.
ABSTRACT Existing research emphasises that the driver of green investment is its future profitability. This paper shows that other investors' decisions also influence green investment. We take the example of scrubber installation in shipping, which is optional by regulation but has an established market for trading its underlying asset.
Yao Shi, Nikos C. Papapostolou, Malvina Marchese, Ioannis C. Moutzouris, Angelos Efstathiou   +4 more
wiley   +1 more source