Search Results - (( parallel distribution model algorithm ) OR ( parameter optimization learning algorithm ))
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Existing literature relies on offline trained models or incremental learning models. The former suffers from partially or fully outdated knowledge after drift occurrence, and the latter suffers from the constraints of the pre-defined hyper-parameter of the model. …”
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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 distributed genetic algorithm development based on microcontrollers framework
Published 2023Subjects:Conference paper -
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Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems
Published 2017“…To implement the parallel algorithm a distributed parallel computing system using MATLAB Distributed Computing Server (MDCS) is configured. …”
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Discretization of crack propagation on parallel computing : complexity and parallel algorithms with source code
Published 2010“…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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Discretization of crack propagation on parallel computing: complexity and parallel algorithms with source code
Published 2010“…Parallel algorithm is used by Parallel Virtual Machine (PVM) software tool to capture the visualization of the overall extension and the stress distribution in a linearly tapered bar of circular section with an end load. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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The visualization of three dimensional brain tumors' growth on distributed parallel computer systems
Published 2009“…The main objective of this study is to visualize the brain tumors’ growth in three-dimensional and implement the algorithm on distributed parallel computer systems. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle
Published 2023“…This paper presents the application of a recent metaheuristic algorithm namely Evolutionary Mating Algorithm (EMA) for optimizing the Deep Learning (DL) parameters to estimate the state of charge (SOC) of a battery for an electric vehicle in the real environment. …”
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Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Geographically distributed heterogeneous resources can execute such workflows in parallel. …”
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Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm
Published 2018“…This paper proposes optimal parameters for an extreme learning machine-based interval type 2 fuzzy logic system to learn its best configuration. …”
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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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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Although this algorithm is optimal for the parameters which appear linearly in the consequent part of interval type-2 fuzzy logic systems, it is not optimal for the parameters of the antecedent part as it uses random parameters. …”
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The learning phase of wavelet neural network entails the task of finding the optimal set of parameter, which includes wavelet activation function, translation centers, dilation parameter, synaptic weight values, and bias terms. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms
Published 2021“…The proposed method combined the New Teaching-Learning-Based Optimization Algorithm (NTLBO), Support Vector Machine (SVM), Extreme Learning Machine (ELM), and Logistic Regression (LR) (feature selection and weighting) NTLBO algorithm with supervised machine learning techniques for Feature Subset Selection (FSS). …”
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Hybrid Harmony Search Algorithm with Grey Wolf Optimizer and Modified Opposition-based Learning
Published 2019“…Many variants have been developed to cope with this problem and improve algorithm performance. In this paper, a hybrid algorithm of HS with grey wolf optimizer (GWO) has been developed to solve the problem of HS parameter selection. …”
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Artificial bee colony optimization of interval type-2 fuzzy extreme learning system for chaotic data
Published 2016“…This paper propose a novel hybrid learning algorithm for the design of IT2FLS. The proposed hybrid learning algorithm utilizes the combination of extreme learning machine (ELM) and artificial bee colony optimization (ABC) to tune the parameters of the consequent and antecedent parts of the IT2FLS, respectively. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. …”
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