Results 31 to 40 of about 9,789 (258)

A Virtual Machine Consolidation Algorithm Based on Ant Colony System and Extreme Learning Machine for Cloud Data Center

IEEE Access, 2020
The energy consumption issue of large-scale data centers is attracting more and more attention. Virtual machine consolidation can significantly reduce energy consumption by migrating virtual machines from one physical machine to another.
Fagui Liu, Zhenjiang Ma, Bin Wang, Weiwei Lin   +3 more
doaj   +1 more source

Flood susceptibility mapping using meta-heuristic algorithms

Geomatics, Natural Hazards & Risk, 2022
Flood is a common global natural hazard, and detailed flood susceptibility maps for specific watersheds are important for flood management measures. We compute the flood susceptibility map for the Kaiser watershed in Iran using machine learning models ...
Alireza Arabameri, Amir Seyed Danesh, M. Santosh, Artemi Cerda, Subodh Chandra Pal, Omid Ghorbanzadeh, Paramita Roy, Indrajit Chowdhuri   +7 more
doaj   +1 more source

The Survey of Algorithms for k-center Problem [PDF]

Zhengzhou Daxue xuebao. Gongxue ban
The k-center problem is fundamental in facility siting, and is also an NP-hard problem with practical applications in the fields of distribution, emergency services, etc. However, with the expansion of the problem scale, the original algorithms were no
WANG Xiaofeng, HUA Yingying, WANG Junxia, PENG Qingyuan, HE Fei   +4 more
doaj   +1 more source

A Search-Based Test Data Generation Method for Concurrent Programs

International Journal of Computational Intelligence Systems, 2020
Concurrent programs are being widely adopted in development of multi-core and many-core processors. However, these types of programs present some features such as concurrency, communication and synchronization which make their testing more challenging ...
Seyed Mohsen Mirhosseini, Hassan Haghighi   +1 more
doaj   +1 more source

A Hybrid Meta-Heuristic Algorithm based on Imperialist Competition Algorithm

Journal of Artificial Intelligence and Data Mining, 2016
The human has always been to find the best in all things. This Perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables and find the best acceptable answer Due to the limitations of the problem, So that the objective function is minimum or maximum.
Roustaei, R., Yousefi Fakhr, F.
openaire   +2 more sources

Advancing the Design of High‐Efficiency Printable Hole‐Conductor‐Free Mesoscopic Perovskite Solar Cells Through Machine Learning

Advanced Science, EarlyView.
Based on the largest printable mesoscopic perovskite solar cells database we established, stacking model achieved precise PCE prediction (R2 = 0.73, MAE = 2.18%). Multiple experiments verified the accuracy of the model, which guided the fabrication of high‐PCE devices with an efficiency of 19.36%.
Hao Meng, Jingzi Zhang, Xu Zhu, Yuelin Wang, Antai Yang, Kailong Hu, Chengquan Zhong, Jiakai Liu, Menghan Dun, Xi Lin   +9 more
wiley   +1 more source

Application of predator-prey optimization for task scheduling in cloud computing [PDF]

Journal of Mahani Mathematical Research
Cloud computing environments require scheduling to allocate resources efficiently and ensure optimal performance. It is possible to maximize resource utilization and minimize execution time by scheduling cloud systems effectively.
Zahra Jalali Khalil Abadi, Behnam Mohammad Hasani zade, Najme Mansouri, Mohammad Masoud Javidi   +3 more
doaj   +1 more source

Advanced Experiment Design Strategies for Drug Development

Advanced Intelligent Discovery, EarlyView.
Wang et al. analyze 592 drug development studies published between 2020 and 2024 that applied design of experiments methodologies. The review surveys both classical and emerging approaches—including Bayesian optimization and active learning—and identifies a critical gap between advanced experimental strategies and their practical adoption in ...
Fanjin Wang, Anthony Harker, Mohan Edirisinghe, Maryam Parhizkar   +3 more
wiley   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

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, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source