Results 121 to 130 of about 65,008 (228)
Energy Science &Engineering, EarlyView.ABSTRACT Traditional air conditioners suffer from low energy efficiency and exacerbate grid peak loads. While ice storage offers energy‐saving potential, the systematic regulation of ice packing fraction (IPF) on cooling consumption and its synergy with dynamic carbon emissions remains unexplored.
Di Yang, Wenpeng Hong, Xu Jin
wiley +1 more source
Feasibility Study and Optimal Placement of Solar Power Plants Using Binary Genetic Algorithm
Energy Science &Engineering, EarlyView.This study introduces an integrated optimization framework using a binary genetic algorithm (BGA) for optimal siting and sizing of two solar plants (865 and 739 kWp) in Karaj, Iran. The BGA outperformed conventional methods, achieving a 24.3% reduction in power losses and enhanced voltage stability.
Mehrab Shahbazi, Reza Eslami
wiley +1 more source
InfoMat, EarlyView.Two‐dimensional MA2Z4 such as MoSi2N4 offer a new path to extend transistor scaling beyond the limits of silicon. Due to their exceptional properties, these 2D semiconductors are promising candidates for future Ångström‐scale CMOS technology. This review outlines the computational design and roadmap bridging materials discovery, device design and ...
Che Chen Tho +11 more
wiley +1 more source
Beyond the Metrics: Context‐Aware Calibration for Better Drain Flow Modelling
Irrigation and Drainage, EarlyView.ABSTRACT Robust hydrological and water quality modelling is essential for advancing the understanding and management of engineered agricultural subsurface drainage systems. Achieving credible model output hinges on calibration strategies that are both rigorous and context sensitive. At the field scale, accurately capturing the dynamics of nutrient load
R. Caleb Bruhn +3 more
wiley +1 more source
MetalMat, EarlyView.This review explores current strategies for shaping two‐dimensional transition metal dichalcogenides (TMDs) beyond their planar form. It highlights how strain engineering, nanopatterning, and growth on complex substrates modulate their mechanical, optical, and electronic properties.
C. Grazianetti +6 more
wiley +1 more source
On the Mean‐Field Limit of Consensus‐Based Methods
Mathematical Methods in the Applied Sciences, EarlyView.ABSTRACT Consensus‐based optimization (CBO) employs a swarm of particles evolving as a system of stochastic differential equations (SDEs). Recently, it has been adapted to yield a derivative free sampling method referred to as consensus‐based sampling (CBS). In this paper, we investigate the “mean‐field limit” of a class of consensus methods, including
Marvin Koß, Simon Weissmann, Jakob Zech
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Networks, EarlyView.ABSTRACT The minimum s$$ s $$‐t$$ t $$‐cut problem is one of the most‐studied problems in discrete optimization and has a unique complexity status in multi‐objective optimization. Even though the single‐objective version of the problem can be solved in polynomial time, it has been shown in the seminal work of Papadimitriou and Yannakakis (2000) that ...
Jan Boeckmann +4 more
wiley +1 more source
Sustainable Development, EarlyView.ABSTRACT Chemical engineering faces an increasing imperative to integrate sustainability principles beyond traditional economic and environmental considerations. The social dimension—encompassing impacts on human well‐being, equity, community health, labor practices, and ethical governance—represents a critical yet often underdeveloped pillar within ...
José M. R. C. A. Santos
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TecnoLógicas, 2010 A linear controller is calculated by the use of a multiobjective optimization technique, and is applied over the induction machine; which is modeled in the oriented coordinate rotor flux system.
Santiago Sánchez +2 more
doaj
Multi‐Objective Optimisation Framework for Heterogeneous Federated Learning
CAAI Transactions on Intelligence Technology, EarlyView.ABSTRACT Federated learning is a distributed framework that trains a centralised model using data from multiple clients without transferring that data to a central server. Despite rapid progress, federated learning still faces several unsolved challenges. Specifically, communication costs and system heterogeneity, such as nonidentical data distribution,
Jamshid Tursunboev +4 more
wiley +1 more source