Search Results - parallel selection ((based algorithm) OR (search algorithm))
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1
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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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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Thesis -
3
PMT: opposition-based learning technique for enhancing meta-heuristic performance
Published 2019“…Like existing OBL-based approaches, the PMT generates new potential solutions based on the currently selected candidate. …”
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Article -
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). In parallel, a feature selection technique based on the combination of mutual information (MI) and neural network (NN) is developed in this study to select the input variables subsets, which have substantial impact on forecasting of electricity price. …”
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Improved hybrid teaching learning based optimization-jaya and support vector machine for intrusion detection systems
Published 2022“…Meanwhile, an improved parallel Jaya (IPJAYA) algorithm was proposed for searching the best parameters (C, Gama) values of SVM. …”
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6
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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7
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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8
Hybrid metaheuristics for QOS-aware service composition / Hadi Naghavipour
Published 2022“…An absolute majority of base algorithms for this problem were nature-inspired and population-based metaheuristics extended to complementary methods in hybrid solutions. …”
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9
Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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10
Development of a multi-objective optimization model for transport and environment in a closed-loop automotive supply chain
Published 2014“…In the last stage, an extended Gravitational Search Algorithm (GSA) as a parallel search algorithm and high convergence rate into high quality final solutions is used to solve the proposed mathematical model and to achieve the Pareto set of solution. …”
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11
High-Speed Implementations Of Fractal Image Compression For Low And High Resolution Images
Published 2018“…The major drawback of FIC is that it is a time consuming algorithm, especially when a full search is attempted. …”
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12
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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13
Guided genetic algorithm for solving unrelated parallel machine scheduling problem with additional resources
Published 2022“…Additionally, an appropriate selection of GA operators was also experimented. The guide genetic algorithm (GGA) is not used to solve the unspecified dynamic UPMR. …”
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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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Conference or Workshop Item -
15
Authenticating sensitive diacritical texts using residual, data representation and pattern matching methods / Saqib Iqbal Hakak
Published 2018“…The proposed method works by splitting the given pattern into two halves and searching for the respective halves. The searching of halves is achieved through two different algorithms based on the split approach and the parallel approach respectively. …”
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16
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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17
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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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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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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