Results 41 to 50 of about 52,700 (290)
Scalable grid resource allocation for scientific workflows using hybrid metaheuristics [PDF]
, 2008 Grid infrastructure is a valuable tool for scientific users, but it is characterized by a high level of complexity which makes it difficult for them to quantify their requirements and allocate resources.
Buss, G, Lee, K, Veit, D
core +1 more source
Advanced Electronic Materials, EarlyView.Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
Energy Reports, 2022 The management of renewable-powered smart grids deals with nonlinear optimization problems featuring a variety of linear or nonlinear constraints, discrete or continuous optimization variables, involving high dimensionality of the solution space, and ...
Cristina Bianca Pop +6 more
doaj +1 more source
Discrete Particle Swarm Optimization for the minimum labelling Steiner tree problem [PDF]
, 2008 Particle Swarm Optimization is an evolutionary method inspired by the social behaviour of individuals inside swarms in nature. Solutions of the problem are modelled as members of the swarm which fly in the solution space.
AS Tanenbaum +19 more
core +2 more sources
Advanced Intelligent Discovery, EarlyView.A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker +3 more
wiley +1 more source
Combinatorial optimization and metaheuristics [PDF]
, 2006 Today, combinatorial optimization is one of the youngest and most active areas of discrete mathematics. It is a branch of optimization in applied mathematics and computer science, related to operational research, algorithm theory and computational ...
Consoli, S, Darby-Dowman, K
core
Advanced Intelligent Systems, EarlyView.Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source
Mathematics, 2021 Combinatorial optimization problems are often considered NP-hard problems in the field of decision science and the industrial revolution. As a successful transformation to tackle complex dimensional problems, metaheuristic algorithms have been ...
Md Ashikur Rahman +5 more
doaj +1 more source
Metaheuristics in applied geophysics
Pamukkale University Journal of Engineering Sciences, 2016 In this study, four metaheuristic algorithms including particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE) and simulated annealing (SA) were used for one-, two-and threedimensional (1D, 2D and 3D) geophysical inverse problems.
BALKAYA, ÇAĞLAYAN +3 more
openaire +4 more sources
An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification
Advanced Intelligent Systems, EarlyView.An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li +6 more
wiley +1 more source