Search Results - (( using function path algorithm ) OR ( evolution classification swarm algorithm ))
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1
Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation
Published 2011“…Ant Swarm Optimization refers to the hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms to enhance optimization performance. …”
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2
EMG Feature Selection And Classification Using A Pbest-Guide Binary Particle Swarm Optimization
Published 2019“…In order to measure the effectiveness of PBPSO, binary particle swarm optimization (BPSO), genetic algorithm (GA), modified binary tree growth algorithm (MBTGA), and binary differential evolution (BDE) were used for performance comparison. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…Hence, a new co-evolution binary particle swarm optimization with a multiple inertia weight strategy (CBPSO-MIWS) is proposed in this work. …”
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Artificial fish swarm optimization for multilayer network learning in classification problems
Published 2012“…Nature-Inspired Computing (NIC) has always been a promising tool to enhance neural network learning. Artificial Fish Swarm Algorithm (AFSA) as one of the NIC methods is widely used for optimizing the global searching of ANN.In this study, we applied the AFSA method to improve the Multilayer Perceptron (MLP) learning for promising accuracy in various classification problems.The parameters of AFSA: AFSA prey, AFSA swarm and AFSA follow are implemented on the MLP network for improving the accuracy of various classification datasets from UCI machine learning. …”
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Artificial Fish Swarm Optmization for Multilayernetwork Learning in Classification Problems
Published 2012“…The results are compared to other NIC methods, i.e., Particle Swarm Optimization (PSO) and Differential Evolution (DE), in which AFSA gives better accuracy with feasible performance for all datasets.…”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The third method is the hybridization of BPSO and Binary Differential Evolution, namely Binary Particle Swarm Optimization Differential Evolution (BPSODE). …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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10
A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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A-star (A*) algorithm implementation for robotics path planning navigation
Published 2018“…This thesis is about the implementation of Astar (A*) algorithm as path planning algorithm used in robotics navigation. …”
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Undergraduates Project Papers -
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Synthesis of transistor chaining algorithm for CMOS cell layout using euler path / Sukri Hanafiah
Published 1997“…The euler's path it using pseudo input and Heuristic algorithm to find the minimum interlace. …”
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Cognitive map approach for mobility path optimization using multiple objectives genetic algorithm
Published 2023Conference Paper -
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Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group
Published 2014“…Consequently, the gradient of the potential functions would be used by the searching algorithm to generate path from starting to goal location. …”
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Y-type Random 2-satisfiability In Discrete Hopfield Neural Network
Published 2024“…Additionally, the proposed Hybrid Differential Evolution Algorithm was implemented into the training phase to ensure that the cost function of the Discrete Hopfield Neural Network is minimized. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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False path identification algorithm framework for nonseparable controller-data path circuits
Published 2016“…This paper proposes an algorithm frame-work to deal with these false paths through identification for DFT test. …”
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Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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False path identification algorithm framework for nonseparable controller-data path circuits
Published 2017“…This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. …”
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The Development Of A Robust Algorithm For Uav Path Planning In 3d Environment
Published 2016“…Significant research has been conducted on Unmanned Aerial Vehicle (UAV) path planning using evolutionary algorithms, such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Differential Evolution (DE), and Biogeographic-Based Optimization (BBO). …”
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