Results 61 to 70 of about 46,625 (244)

A study on gender detection using multiple classifiers on voice data

Alexandria Engineering Journal
Researchers have frequently used metaheuristic algorithms for various problems due to their success. In data mining studies, feature selection (FS) is an essential preprocessing step for large-scale problems.
Gülnur Yildizdan, Emine Baş
doaj   +1 more source

An Investigation into the Merger of Stochastic Diffusion Search and Particle Swarm Optimisation [PDF]

, 2011
This study reports early research aimed at applying the powerful resource allocation mechanism deployed in Stochastic Diffusion Search (SDS) to the Particle Swarm Optimiser (PSO) metaheuristic, effectively merging the two swarm intelligence algorithms ...
al-Rifaie, Mohammad Majid, Bishop, Mark (J. M.), Blackwell, Tim M.   +2 more
core   +2 more sources

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

Energy Science &Engineering, EarlyView.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan, Suresh Panchanathan, Chan Choon Kit, Elumalai Perumal Venkatesan, Nasim Hasan   +4 more
wiley   +1 more source

MTS-PRO2SAT: Hybrid Mutation Tabu Search Algorithm in Optimizing Probabilistic 2 Satisfiability in Discrete Hopfield Neural Network

Mathematics
The primary objective of introducing metaheuristic algorithms into traditional systematic logic is to minimize the cost function. However, there is a lack of research on the impact of introducing metaheuristic algorithms on the cost function under ...
Ju Chen, Yuan Gao, Mohd Shareduwan Mohd Kasihmuddin, Chengfeng Zheng, Nurul Atiqah Romli, Mohd. Asyraf Mansor, Nur Ezlin Zamri, Chuanbiao When   +7 more
doaj   +1 more source

Metaheuristics for pharmacometrics

CPT: Pharmacometrics & Systems Pharmacology, 2021
Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature‐inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be ...
Seongho Kim, Andrew C. Hooker, Yu Shi, Grace Hyun J. Kim, Weng Kee Wong   +4 more
doaj   +1 more source

Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems

Applied Sciences, 2021
Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. For an optimization problem, population initialization plays a significant role in metaheuristic algorithms. These algorithms can influence the convergence to
Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat   +5 more
doaj   +1 more source

A comparison of general-purpose optimization algorithms forfinding optimal approximate experimental designs [PDF]

, 2019
Several common general purpose optimization algorithms are compared for findingA- and D-optimal designs for different types of statistical models of varying complexity,including high dimensional models with five and more factors.
Garcia-Garcia, Jose Carlos, Garcia-Rodenas, Ricardo, Lopez-Fidalgo, Jesus, Martin-Baos, Jose Angel, Wong, Weng Kee   +4 more
core  

POWER: Performance Optimization With Evaluated Results for HEV Battery Selection via MCDM‐TOPSIS

Energy Science &Engineering, EarlyView.
ABSTRACT The increasing transportation demands and environmental concerns in India necessitate the selection of optimal battery technologies for hybrid electric vehicles (HEVs). As the fifth‐largest car market globally, India faces rising vehicle demand, while the transportation sector remains a major contributor to air pollution.
Rinku Kumar Roy, Harpreet Kaur Channi, Sita Rani, Aman Kataria, Parveen Bajaj, George Uwadiegwu Alaneme   +5 more
wiley   +1 more source

An improved African vultures optimization algorithm based on tent chaotic mapping and time-varying mechanism.

PLoS ONE, 2021
Metaheuristic optimization algorithms are one of the most effective methods for solving complex engineering problems. However, the performance of a metaheuristic algorithm is related to its exploration ability and exploitation ability.
Jiahao Fan, Ying Li, Tan Wang
doaj   +1 more source

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

Energy Science &Engineering, EarlyView.
Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga, Subhasish Deb, Kshetrimayum Robert Singh, Subir Datta, Ahmet Onen, Taha Selim Ustun, Jaesung Jung   +6 more
wiley   +1 more source