Search Results - parallel feature selection algorithm
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1
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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3
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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4
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…ITLBO with supervised machine learning (ML) technique was used for feature subset selection (FSS). The selection of the least number of features without causing an effect on the result accuracy in FSS is a multiobjective optimisation problem. …”
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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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6
Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…This paper presents two intelligent algorithms that hybridized between ant colony optimization (ACO) and SVM for tuning SVM parameters and selecting feature subset without having to discretize the continuous values. …”
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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 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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9
Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…The performance of our work also been compared with several state-of-the-art of features for selection algorithms.…”
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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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11
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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12
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 -
13
A new approach in solving illumination and facial expression problems for face recognition
Published 2009“…In this paper, a novel dual optimal multiband features (DOMF) method is presented to increase the robustness of face recognition system to illumination and facial expression variations.The wavelet packet transform first decomposes image into low-, mid- and high-frequency subbands and the multiband feature fusion technique is incorporated to select the subbands that are invariant to illumination and expression variation separately.These subbands form the optimal feature sets.Parallel radial basis function neural networks are employed to classify these feature sets.The scores generated by the neural networks are combined by an adaptive fusion mechanism where the level of illumination variations of the testing image is estimated and the weights are assigned to the scores accordingly.The experimental results show that DOMF outperforms other algorithms and also achieves promising performance on illumination and facial expression variation conditions.…”
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Conference or Workshop Item -
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An evolutionary-based term reduction approach to bilingual clustering of Malay-English corpora
Published 2017“…The objective in this study is to study the effects of reducing terms considered in clustering bilingual corpus in parallel for English and Malay documents. In this study, a genetic algorithm (GA) is used in order to reduce the number of feature selected. …”
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Conference or Workshop Item -
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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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16
A Simulated Annealing-Based Hyper-Heuristic For The Flexible Job Shop Scheduling Problem
Published 2023“…SA-HH based on the HS with problem state features (SA-HHPSF) and without problem state features (SA-HHNO-PSF).…”
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Three phase induction motor coupled to DC motor in hybrid electric vehicle application
Published 2011“…The developed algorithm for the three phase induction motor couple to dc motor provides fast convergence of parameters, rapid response characteristics of the drive, and accurate tracking of the control command for the three phase induction motor drive.These performance features are highly desirable for the propulsion motor in HEVs and EVs.…”
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19
On line fault detection for transmission line using power system stabilizer signals
Published 2007“…Hence, this study will show that not only the PSS able to compensate the damping due to the disturbance but also by using the developed algorithm it succeeds to detect and classify the fault conditions on the parallel transmission lines.…”
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A new visual simulation tool for performance evaluation of MANET routing protocols
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Proceeding Paper