Search Results - (( parallel evaluation study algorithm ) OR ( parallel optimization learning algorithm ))*
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1
Online system identification development based on recursive weighted least square neural networks of nonlinear hammerstein and wiener models.
Published 2022“…This research introduces a developed method for online system identification based on the Hammerstein and Wiener nonlinear block-oriented structure with the artificial neural networks (NN) advantages and recursive weighted least squares algorithm for optimizing neural network learning in real-time. …”
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Thesis -
2
Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
3
Adaptive genetic algorithm to improve negotiation process by agents e-commerce
Published 2011“…The proposed negotiation algorithm employs Bayesian learning and similarity functions in order to predict opponent agent’s type and preferences. …”
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4
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. …”
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Student Project -
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…A genetic algorithm search heuristic was chosen to solve this multi-objective optimization problem. …”
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Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…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. …”
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7
PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Metaheuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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8
Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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A parallel ensemble learning model for fault detection and diagnosis of industrial machinery
Published 2023“…However, the gradient descent optimization method that is commonly used in deep learning suffers from several limitations, such as high computational cost and local sub-optimal solutions. …”
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10
PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…Meta-heuristic algorithms have shown promising performance in solving sophisticated real-world optimization problems. …”
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11
Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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12
Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
Published 2019“…In this paper, the particle swan optimization algorithm (PSO) was used to obtain an optimal set of initial parameters for Reduce Kernel FLN (RK-FLN), thus, creating an optimal RKFLN classifier named PSO-RKELM. …”
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Conference or Workshop Item -
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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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Conference or Workshop Item -
14
A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering
Published 2023“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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A parallel-model speech emotion recognition network based on feature clustering
Published 2023“…To address this issue, we proposed a novel algorithm called F-Emotion to select speech emotion features and established a parallel deep learning model to recognize different types of emotions. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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17
An Experimental Study on Relationship between Performance and Energy Consumption of Serial and Parallel Text Searching Algorithm.
Published 2013“…In this paper, text searching algorithm is using to study the relationship between performance of computer and amount of energy produced in serial and parallel text searching algorithm. …”
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Final Year Project -
18
Parallel CFD Simulations of Multiphase Systems: Jet into a Cylindrical Bath and Rotary Drum on a Rectangular Bath.
Published 2001“…In short, this research is intended to establish a strategic procedure to optimize a parallel version of a CFD package, FLUENT. …”
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Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…MR is an emerging parallel processing framework that hides the complex parallelization processes by employing the functional abstraction of "map and reduce" The Performance of the parallelized GA via MR and PSO via MR are evaluated using an analogous case study to find out the speedup and efficiency in order to measure the scalability of both proposed algorithms. …”
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20
Parallel Execution of Runge-Kutta Methods for Solving Ordinary Differential Equations
Published 2004“…The method used here is actually have been tailored made for the purpose of parallel machine where the subsequent functions evaluations do not depend on the previous function evaluations. …”
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