Search Results - (( parallel optimization based algorithm ) OR ( wolf classification problems algorithm ))
Search alternatives:
- parallel optimization »
- wolf classification »
- problems »
-
1
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…—Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
Get full text
Get full text
Article -
2
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO) are well-perform metaheuristic algorithms used by various researchers in solving feature selection problems. …”
Get full text
Get full text
Article -
3
Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification
Published 2020“…In addition, to examine the efficiency of the proposed method, two recent algorithms namely: Whale Optimization algorithm (WAO) and Dragonfly Algorithm (DA) are implemented for comparison. …”
Get full text
Get full text
Conference or Workshop Item -
4
A New Competitive Binary Grey Wolf Optimizer To Solve The Feature Selection Problem In EMG Signals Classification
Published 2018“…Therefore, this article proposes a new competitive binary grey wolf optimizer (CBGWO) to solve the feature selection problem in EMG signals classification. …”
Get full text
Get full text
Get full text
Article -
5
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…This paper proposes a competitive grey wolf optimizer (CGWO) to solve the feature selection problem in electromyography (EMG) pattern recognition. …”
Get full text
Get full text
Get full text
Article -
6
Binary Multi-Objective Grey Wolf Optimizer for Feature Selection in Classification
Published 2020“…Recently, Multi-objective Grey Wolf optimizer (MOGWO) was proposed to solve multi-objective optimization problem. …”
Get full text
Get full text
Article -
7
An Improved Grey Wolf Optimization-based Learning of Artificial Neural Network for Medical Data Classification
Published 2021“…Like other metaheuristic algorithms, GWO also suffers from local optima and slow convergence problems, resulted in degraded performance. …”
Get full text
Get full text
Get full text
Get full text
Article -
8
Enhanced Multi-Objective Grey Wolf Optimizer with Lévy Flight and Mutation Operators for Feature Selection
Published 2023“…This paper presents enhanced multi-objective grey wolf optimizer with Lévy flight and mutation phase (LMuMOGWO) for tackling feature selection problems. …”
Get full text
Get full text
Article -
9
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic algorithm which is appealing to researcher owing to its demonstrated performance as cited in the scientific literature. …”
Get full text
Get full text
Thesis -
10
-
11
Improved swarm intelligence algorithms with time-varying modified Sigmoid transfer function for Amphetamine-type stimulants drug classification
Published 2022“…The new binary algorithms, BPSO, BGWOA, BWOA, BHHO, and BMRFO algorithms are utilized for solving the descriptors selection problem in supervised Amphetamine-type Stimulants (ATS) drug classification task. …”
Get full text
Get full text
Get full text
Article -
12
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…For these reasons, to improve the time and accuracy of the coverage in population-based meta-heuristics and their utilization in HPAs, this thesis presents a novel optimization algorithm called the Raccoon Optimization Algorithm (ROA). …”
Get full text
Get full text
Thesis -
13
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
Get full text
Get full text
Get full text
Thesis -
14
Performance Comparison of Parallel Bees Algorithm on Rosenbrock Function
Published 2012“…This thesis presents the parallel Bees Algorithm as a new approach for optimizing the last results for the Bees Algorithm. …”
Get full text
Get full text
Get full text
Thesis -
15
Parallel distributed computational microcontroller system for adaptive antenna downlink transmitter power optimization
Published 2023Subjects:Article -
16
Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
Published 2016“…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
Get full text
Get full text
Student Project -
17
A novel nonlinear time‑varying sigmoid transfer function in binary whale optimization algorithm for descriptors selection in drug classifcation
Published 2022“…The comparative optimization algorithms include two BWOA variants, binary bat algorithm (BBA), binary gray wolf algorithm (BGWOA), and binary manta-ray foraging algorithm (BMRFO). …”
Get full text
Get full text
Get full text
Article -
18
Short Text Classification Using An Enhanced Term Weighting Scheme And Filter-Wrapper Feature Selection
Published 2018“…In the second stage, grey wolf optimization (GWO) algorithm, a new heuristic search algorithm, uses the SVM accuracy as a fitness function to find the optimal subset feature.…”
Get full text
Get full text
Thesis -
19
A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)
Published 2013“…Genetic Algorithms (GAs) is proven to be effective in solving many optimization tasks. …”
Get full text
Conference or Workshop Item -
20
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
Get full text
Get full text
Thesis
