Results 171 to 180 of about 491,073 (352)

Enhancing Hybrid Microgrid Dynamics Using an Agent‐Based Reinforcement Learning (RL) Framework

open access: yesEnergy Science &Engineering, EarlyView.
Overview of (RL) framework ABSTRACT Hybrid microgrids, integrating renewable, and conventional energy sources are critical for sustainable and resilient power systems. Their dynamic performance is affected by uncertainties in load demand, generation variability, and control strategies.
Sudhakiran Ponnuru   +8 more
wiley   +1 more source

Introduction: frontiers of applied inverse problems in science and engineering. [PDF]

open access: yesPhilos Trans A Math Phys Eng Sci
Smyl D, Hauptmann A, Tallman T.
europepmc   +1 more source

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

open access: yesEnergy 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   +5 more
wiley   +1 more source

A Comprehensive Review of Biotechnological Innovations in Valorization of Food Waste: Enhancing Nutritional, Techno‐Functional Properties, and Process Optimization for Sustainable Product Development

open access: yesFood Frontiers, EarlyView.
This review highlights recent biotechnological innovations in the valorization of food waste through enzyme‐assisted processing and microbial fermentation to enhance nutritional, techno‐functional, and shelf‐stable properties for developing sustainable, plant‐based functional foods and nutraceuticals.
Md. Sakhawot Hossain   +6 more
wiley   +1 more source

Can Legal and Professional Personnel Selection Principles be Met With Machine Learning (Artificial Intelligence)?

open access: yesHuman Resource Management, EarlyView.
ABSTRACT The purpose of this article is primarily to evaluate whether machine learning (a form of artificial intelligence) can meet scientific, professional, and legal principles of personnel selection based on the rapidly accumulating research literature in Human Resource Management (HRM).
Michael A. Campion
wiley   +1 more source

Home - About - Disclaimer - Privacy