Search Results - parallel selection ((((learning algorithm) OR (matching algorithm))) OR (based algorithm))
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PMT : opposition based learning technique for enhancing metaheuristic algorithms performance
Published 2020“…Like existing OBL-based approaches, the PMT generates new potential solutions based on the currently selected candidate. …”
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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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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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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…The aim of this work is to develop an improved optimization method for IDS that can be efficient and effective in subset feature selection and parameters optimization. To achieve this goal, an improved Teaching Learning-Based Optimization (ITLBO) algorithm was proposed in dealing with subset feature selection. …”
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The development of semantic meta-database: an ontology based semantic integration of biological databases
Published 2007“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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Monograph -
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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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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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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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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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Job Matching Mobile Application using Fuzzy Analytic Hierarchy Process (FAHP) / Mohammad Ashraf Jefrizin
Published 2017“…Findings of this project is portrayed as conceptual framework that consists the structure of job matching mobile application using FAHP algorithm. Evaluation is conducted using accuracy test where the result of this application is compared to the manual method using a survey. …”
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New CFAR algorithm and circuit development for radar receiver
Published 2020“…Therefore, the MSS-CA-CFAR is chosen to implement by practical digital circuit and there is another important feature in the MSS-CFAR algorithm that is parallel processing since the spike selection process is done at the same time with summing of samples process that makes this algorithm much less in processing time from any other algorithm using the same environment. …”
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Authenticating sensitive diacritical texts using residual, data representation and pattern matching methods / Saqib Iqbal Hakak
Published 2018“…The searching of halves is achieved through two different algorithms based on the split approach and the parallel approach respectively. …”
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Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources
Published 2022“…Results show that the GGA outperforms the simple genetic algorithm (SGA), but it still didn't match the results in the literature. …”
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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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A review of genetic algorithms and parallel genetic algorithms on Graphics Processing Unit (GPU)
Published 2013“…GAs is one of the optimization tools used widely in solving problems based on natural selection and genetics. This paper is intended to cover the study of GA and parallel GA and analyses its usage in CPU and GPU. …”
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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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Parallel computation of maass cusp forms using mathematica
Published 2013“…Our parallel programme comprises of two important parts namely the pullback algorithm and also the Maass cusp form algorithm. …”
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