Search Results - parallel selection ((learning algorithm) OR (means algorithm))
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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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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…To conclude, multi objective parallel genetic algorithm can automatically tune feed forward neural network to classify the dataset with a good classification rate.…”
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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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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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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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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Most of the currently existing intrusion detection systems (IDS) use machine learning algorithms to detect network intrusion. Machine learning algorithms have widely been adopted recently to enhance the performance of IDSs. …”
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Effective software fault localization based on complex network theory / Abubakar Zakari
Published 2019“…This has led researchers to adopt approaches such as one bug-at-a-time debugging approach (OBA) and parallel debugging approach. However, using OBA debugging approach increases software time-to-delivery and potentially leads to more faults during regression testing, while utilizing k-mean clustering algorithm with Euclidean distance metric to group failed tests based on their execution profile similarity in parallel debugging approach is claimed to be problematic and inappropriate. …”
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Small-scale helicopter system identification model using recurrent neural networks
Published 2010“…The identification process is conducted by using the well known Levenberg-Marquardt learning algorithm. The obtained dynamics model shows good fitness with the actual data. …”
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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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Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…Our results indicate that gene expression profiles combined with carefully chosen learning algorithms can predict patient survival for certain diseases.…”
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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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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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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An integrated priority-based cell attenuation model for dynamic cell sizing
Published 2012“…A new, robust integrated priority-based cell attenuation model for dynamic cell sizing is proposed and simulated using real mobile traffic data.The proposed model is an integration of two main components; the modified virtual community – parallel genetic algorithm (VC-PGA) cell priority selection module and the evolving fuzzy neural network (EFuNN) mobile traffic prediction module.The VC-PGA module controls the number of cell attenuations by ordering the priority for the attenuation of all cells based on the level of mobile level of mobile traffic within each cell.The EFuNN module predicts the traffic volume of a particular cell by extracting and inserting meaningful rules through incremental, supervised real-time learning.The EFuNN module is placed in each cell and the output, the predicted mobile traffic volume of the particular cell, is sent to local and virtual community servers in the VC-PGA module.The VC-PGA module then assigns priorities for the size attenuation of all cells within the network, based on the predicted mobile traffic levels from the EFuNN module at each cell.The performance of the proposed module was evaluated on five adjacent cells in Selangor, Malaysia. …”
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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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High-Speed Implementations Of Fractal Image Compression For Low And High Resolution Images
Published 2018“…Therefore, in this research new hardware implementations of FIC are proposed for accelerating the encoding process by means of parallelism and pipelining. Various approaches have been investigated for achieving high speed performance. …”
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