Search Results - (( data distributed learning algorithm ) OR ( based optimization based algorithm ))
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Supervised deep learning algorithms for process fault detection and diagnosis under different temporal subsequence length of process data
Published 2025“…Deep learning algorithms were widely used among all the data-driven algorithms. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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An improved optimization algorithm-based prediction approach for the weekly trend of COVID-19 considering the total vaccination in Malaysia: A novel hybrid machine learning approach
Published 2023“…This study concludes, based on its experimental findings, that hybrid IBMOLSSVM outperforms cross validations, original BMO, ANN and few other hybrid approaches with optimally optimized parameters.…”
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An enhanced version of black hole algorithm via levy flight for optimization and data lustering problems
Published 2019“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…The main keys of the new classifier are based on the new kernel method, new learning metric and a new optimization algorithm in order to optimize the SVM decision function. …”
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Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…An alternative method is proposed, utilizing machine learning algorithms. Therefore, this thesis explores the comparative analysis for BOTDA data processing using the six most suited machine learning algorithms. …”
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Thus, using neural network-based semi-supervised stream data learning is inadequate due to capture the changes in the distribution and characteristics of various classes of data while avoiding the effect of the outdated stored knowledge in neural networks (NN). …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Classification of imbalanced datasets remained a significant issue in data mining and machine learning (ML) fields. This research work proposed a new idea based on the optimization for handling the imbalanced datasets. …”
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An enhanced version of black hole algorithm via levy flight for optimization and data clustering problems
Published 2019“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems, in which it is a population-based metaheuristic that emulates the phenomenon of the black holes in the universe. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems
Published 2021“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Distributed learning based energy-efficient operations in small cell networks
Published 2023“…Simulation results demonstrate improved performance in power consumption, load, sum rate, utility, learning rate, convergence, and energy efficiency for small base stations (SBSs) and user equipment (UEs) compared to four benchmarked algorithms, including WMMSE, game theory, Q-learning, and DRL. …”
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Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The proposed framework and models that are are considered to be the specific research contributions of this thesis are: 1) a comparison framework of classification models for software defect prediction known as CF-SDP, 2) a hybrid genetic algorithm based feature selection and bagging technique for software defect prediction known as GAFS+B, 3) a hybrid particle swarm optimization based feature selection and bagging technique for software defect prediction known as PSOFS+B, and 4) a hybrid genetic algorithm based neural network parameter optimization and bagging technique for software defect prediction, known as NN-GAPO+B. …”
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Predicting Customer Buying Decisions for Online Shopping with Unbalanced Data Set
Published 2022“…Weka, a data mining tool, provides the facility to classify the data set with different machine learning algorithms. …”
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Final Year Project / Dissertation / Thesis -
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering
Published 2020“…Existing stream data learning models with limited labeling have many limitations, most importantly, algorithms that suffer from a limited capability to adapt to the evolving nature of data, which is called concept drift. …”
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Route Optimization based on Clustering and Travelling Salesman Problem
Published 2022“…In this paper, comparison results between the original route taken by the driver and the proposed route based on optimization are conducted and reported. …”
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Hybrid performance measures and mixed evaluation method for data classification problems
Published 2012“…In the second evaluation stage, almost all selected algorithms that optimized by OAERP2 measure are able to produce better generalization ability against its original measure and other selected performance measures. …”
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Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Next, an advanced machine learning based on is utilized to predict islanding and none islanding states. …”
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