Search Results - parallel selection ((((machine algorithm) OR (learning algorithm))) OR (bees algorithm))
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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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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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources
Published 2022“…This paper solved the unrelated parallel machine scheduling with additional resources (UPMR) problem. …”
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Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…For example, cancer prognosis using machine learning techniques is now a promising area of research. …”
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Proceeding Paper -
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Parallel algorithms on some numerical techniques using PVM platform on a cluster of workstations
Published 2002“…In this paper, a few parallel algorithms are explained in solving one dimensional heat model problem using Parallel Virtual Machine (PVM). …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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10
Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Performing feature subset and tuning support vector machine (SVM) parameter processes in parallel with the aim to increase the classification accuracy is the current research direction in SVM. …”
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ROA-CONS: raccoon optimization job scheduling
Published 2021“…An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. …”
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…This research algorithm demonstrated a very promising result with Support Vector Machines, this algorithm produces a 90% of accuracies whereas the decision tree algorithm gets 100% accuracies. …”
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Final Year Project / Dissertation / Thesis -
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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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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Addressing these OBL limitations, this research proposes a new general OBL technique inspired by a natural phenomenon of parallel mirrors systems called the Parallel Mirrors Technique (PMT). …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…Addressing these issues, this research proposes a new general opposition-based learning (OBL) technique inspired by a natural phenomenon of parallel mirrors systems called the parallel mirrors technique (PMT). …”
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Parallel processing in Compute Unified Device Architecture (CUDA) for energy saving glass
Published 2014“…In order to develop a complex coating structure, genetic algorithm technique is used in this research. However, genetic algorithm require a fast processing speed in order to cope with the process of creating new chromosome from the population and undergoes the selection, crossover and mutation operation processes. …”
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Three phase induction motor coupled to DC motor in hybrid electric vehicle application
Published 2011“…An advanced electric drive controller for a high power starter-generator subsystem based on a series DC machine is presented. The machine is belt-coupled to a diesel engine in a series-parallel 2×2 HEV. …”
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A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA)
Published 2024“…The optimization result was compared with well-established algorithms, the Pareto Envelope-based Selection Algorithm II (PESA2), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), and new algorithms, Multi-Objective Grasshopper Optimization Algorithm (MOGOA) and Multi-Objective Ant Lion Optimizer (MOALO). …”
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Conference or Workshop Item -
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A Simulated Annealing-Based Hyper-Heuristic For The Flexible Job Shop Scheduling Problem
Published 2023“…Flexible job shop scheduling problem (FJSP) is a common optimisation problem in the industry. The use of parallel machines allows an operation to be executed on a machine assigned from a set of alternative machines, raising a combination of machine assignment and job sequencing sub-problems. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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