Results 101 to 110 of about 9,608,205 (238)

Scalarizing cost-effective multi-objective optimization algorithms made possible with kriging

, 2008
Purpose – The purpose of this paper is threefold: to make explicitly clear the range of efficient multi-objective optimization algorithms which are available with kriging; to demonstrate a previously uninvestigated algorithm on an electromagnetic design ...
Hawe, G., Sykulski, J.K.
core  

Hybrid metaheuristics for multi-objective optimization

, 2015
International audienceOver the last two decades, interest on hybrid metaheuristics has risen considerably in the field of multi-objective optimization (MOP).
Talbi, El-Ghazali
core   +1 more source

A solution method for the traveling salesman problem based on multi-scale features and dynamic optimization

Discover Computing
As a classic NP-hard problem, the Traveling Salesman Problem (TSP) exhibits exponentially increasing complexity with node quantity, making optimal solutions difficult for large-scale instances. Traditional exact and heuristic algorithms still struggle to
Yuting Xie, Qianqian Duan
doaj   +1 more source

Optimizing crop planting structures for water savings and grain revenue in China considering different spatial scales

Resources, Environment and Sustainability
Balancing agricultural production to ensure food security and poverty alleviation with natural resource conservation, e.g., water, is the current focus of China's sustainable agricultural development policy.
Wen Liu, Yuchuan Fan, T. Edward Yu
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Scheduling Jamming Resources in Complex Terrain: A Multi-Objective Air—Ground Collaborative Optimization Approach

Future Internet
Addressing the high-dimensional, strongly constrained multi-objective optimization problem of air–ground collaborative jamming scheduling in complex terrain, existing methods are often limited by incomplete modeling and low optimization efficiency in ...
Haiyang You, Zhenhua Wei, Wenpeng Wu, Chenxi Li, Jianwei Zhan, Zhaoguang Zhang   +5 more
doaj   +1 more source

Spatially Adaptive Multi-Scale Optimization for Local Parameter Estimation in Cardiac Electrophysiology. [PDF]

IEEE Trans Med Imaging, 2017
Dhamala J, Arevalo HJ, Sapp J, Horacek M, Wu KC, Trayanova NA, Wang L.   +6 more
europepmc   +1 more source

Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source

Intermediate Resistive State in Wafer‐Scale Vertical MoS2 Memristors Through Lateral Silver Filament Growth for Artificial Synapse Applications

Advanced Functional Materials, EarlyView.
In MOCVD MoS2 memristors, a current compliance‐regulated Ag filament mechanism is revealed. The filament ruptures spontaneously during volatile switching, while subsequent growth proceeds vertically through the MoS2 layers and then laterally along the van der Waals gaps during nonvolatile switching.
Yuan Fa, Milan Buttberg, Ke Ran, Rana Walied Ahmad, Dennis Braun, Lukas Völkel, Jimin Lee, Sofía Cruces, Bart Macco, Bárbara Canto, Holger Lerch, Thorsten Wahlbrink, Holger Kalisch, Michael Heuken, Andrei Vescan, Joachim Mayer, Zhenxing Wang, Ilia Valov, Stephan Menzel, Max C. Lemme   +19 more
wiley   +1 more source

A Bidding Strategy for Power Suppliers Based on Multi-Agent Reinforcement Learning in Carbon–Electricity–Coal Coupling Market

Energies
The deepening operation of the carbon emission trading market has reshaped the cost–benefit structure of the power generation side. In the process of participating in the market quotation, power suppliers not only need to calculate the conventional power
Zhiwei Liao, Chengjin Li, Xiang Zhang, Qiyun Hu, Bowen Wang   +4 more
doaj   +1 more source