Results 31 to 40 of about 41,487 (244)
Proposal and Comparative Study of Evolutionary Algorithms for Optimum Design of a Gear System [PDF]
, 2019 This paper proposes a novel metaheuristic framework using a Differential Evolution (DE) algorithm with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II).
Frutos, Mariano +3 more
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FPGA Implementation of Metaheuristic Optimization Algorithm
e-Prime - Advances in Electrical Engineering, Electronics and Energy, 2023 Metaheuristic algorithms are gaining popularity amongst researchers due to their ability to solve nonlinear optimization problems as well as the ability to be adapted to solve a variety of problems. There is a surge of novel metaheuristics proposed recently, however it is uncertain whether they are suitable for FPGA implementation.
Nurul Hazlina Noordin +2 more
openaire +2 more sources
IET Networks, EarlyView., 2023 We utilise a metaheuristic optimisation method, inspired by nature, called the Lévy‐flight firefly algorithm (LFA), to tackle the power regulation and user grouping in the NOMA systems. Abstract The non‐orthogonal multiple access strategies have shown promise to boost fifth generation and sixth generation wireless networks' spectral efficiency and ...
Zaid Albataineh +4 more
wiley +1 more source
Multi-Objective Big Data Optimization with jMetal and Spark [PDF]
, 2017 Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi ...
A Cabanas-Abascal +11 more
core +1 more source
Optimizing EMG Classification through Metaheuristic Algorithms
Technologies, 2023 This work proposes a metaheuristic-based approach for hyperparameter selection in a multilayer perceptron to classify electromyographic signals. The main goal of the study is to improve the performance of the model by optimizing four important hyperparameters: the number of neurons, the learning rate, the epochs, and the training batches.
Marcos Aviles +2 more
openaire +2 more sources
Metaheuristic Algorithms for Optimization: A Brief Review
Engineering ProceedingsIn the area of optimization, metaheuristic algorithms have attracted a lot of interest. For many centuries, human beings have utilized metaheuristic algorithms as a problem-solving approach.
Vinita Tomar, Mamta Bansal, Pooja Singh
doaj +1 more source
Enhanced Metaheuristic Optimization: Wind-Driven Flower Pollination Algorithm
IEEE Access, 2019 The flower pollination algorithm is a new metaheuristic optimization technique that simulates the pollination behavior of flowers in nature. The global and local search processes of the algorithm are performed by simulating the self-pollination and cross-
Mengyi Lei, Yongquan Zhou, Qifang Luo
doaj +1 more source
A New Metaheuristic Bat-Inspired Algorithm
, 2010 Metaheuristic algorithms such as particle swarm optimization, firefly algorithm and harmony search are now becoming powerful methods for solving many tough optimization problems.
J. Kennedy +9 more
core +1 more source
Bat Algorithm for Multi-objective Optimisation [PDF]
, 2011 Engineering optimization is typically multiobjective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimization algorithms.
Yang, Xin-She
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Bio-inspired Optimization: metaheuristic algorithms for optimization
, 2020 In today's day and time solving real-world complex problems has become fundamentally vital and critical task. Many of these are combinatorial problems, where optimal solutions are sought rather than exact solutions. Traditional optimization methods are found to be effective for small scale problems.
Game, Pravin S, Vaze, Vinod, M, Emmanuel
openaire +2 more sources