Results 51 to 60 of about 47,568 (277)
ACO for continuous function optimization: a performance analysis [PDF]
, 2014 The performance of the meta-heuristic algorithms often depends on their parameter settings. Appropriate tuning of the underlying parameters can drastically improve the performance of a meta-heuristic. The Ant Colony Optimization (ACO), a population based
Abraham, Ajith +2 more
core
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Physics based meta heuristics in manufacturing
Materials Today: Proceedings, 2021 Abstract Physics based algorithms are inspired from physical phenomenon in nature but not from biological organisms. They were created by mimicking certain laws of physics and chemistry. The disadvantages of these algorithms was taken care of by their improved versions some of which gives best result on one application and fails on the another ...
Seshadri Sridharan +2 more
openaire +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 +3 more
wiley +1 more source
IEEE Access, 2022 This paper proposes a new meta-heuristic optimization algorithm, namely Mud Ring Algorithm (MRA) that mimics the mud ring feeding behaviour of bottlenose dolphins in the Atlantic coast of Florida.
Abeer S. Desuky +4 more
doaj +1 more source
Time series predictive analysis based on hybridization of meta-heuristic algorithms [PDF]
, 2018 This paper presents a comparative study which involved five hybrid meta-heuristic methods to predict the weather five days in advance. The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial ...
Ernawan, Ferda +4 more
core
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
Solving a big-scaled hospital facility layout problem with meta-heuristics algorithms
Engineering Science and Technology, an International Journal, 2020 The main objective of the hospital facility layout problem is to place the polyclinics, laboratories and radiology units within the predefined boundaries in such way that minimize the movement cost of patients and healthcare staff.
Vahit Tongur +2 more
doaj +1 more source
Optimal FOC-PID Parameters of BLDC Motor System Control Using Parallel PM-PSO Optimization Technique
International Journal of Computational Intelligence Systems, 2021 This paper proposes a parallelization method for meta-heuristic particle swarm optimization algorithm to obtain a convincingly fast execution and stable global solution result.
Nguyen Tien Dat +2 more
doaj +1 more source
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 +4 more
wiley +1 more source