Search Results - (( parallel validation using algorithm ) OR ( pattern classification parallel algorithm ))
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EMG motion pattern classification through design and optimization of neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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Proceeding Paper -
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EMG motion pattern classification through design and optimization of Neural Network
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Working Paper -
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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Article -
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Robust tweets classification using arithmetic optimization with deep learning for sustainable urban living
Published 2024“…In this view, this research develops an arithmetic optimization algorithm with deep learning based tweets classification (AOADL-TC) approach for sustainable living. …”
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Parallel block backward differentiation formulas for solving large systems of ordinary differential equations.
Published 2010“…Parallelism is obtained by using Message Passing Interface (MPI).Numerical results are given to validate the efficiency of the PBBDF implementation as compared to the sequential implementation.…”
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Harmonic reduction in three-phase parallel connected inverter
Published 2009“…High frequency third harmonic injection PWM (THIPWM) employed to reduce the total harmonic distortion and to make maximum use of the voltage source. DSP was used to generate the THIPWM and the control algorithm for the converter. …”
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Article -
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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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Thesis -
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The Parallel Fuzzy C-Median Clustering Algorithm Using Spark for the Big Data
Published 2024“…Therefore, we develop a Parallel Fuzzy C-Median Clustering Algorithm Using Spark for Big Data that can handle large datasets while maintaining high accuracy and scalability. …”
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Fpga-Based Accelerator For The Identification Of Finger Vein Pattern Via K-Nearest Centroid Neighbors
Published 2016“…In recent years, finger vein recognition has emerged as a promising biometric technology due to the fact that each person in this world has unique finger vein pattern. Over the past few years, various finger vein recognition algorithms and techniques have been proposed by researchers and scholars. …”
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Distributed generation with parallel connected inverter
Published 2009“…Third harmonic injection PWM (THIPWM) reduces the total harmonic distortion and to make maximum use of the voltage source. DSP was used to generate the THIPWM and the control algorithm for the converter. …”
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Conference or Workshop Item -
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Parallel connected inverter for fuel cell system
Published 2008“…Third harmonic injection PWM (THIPWM) reduces the total harmonic distortion and to make maximum use of the voltage source. DSP was used to create the THIPWM and the control algorithm for the converter. …”
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Development of an automatics parallel parking system for nonholonomic mobile robot
Published 2011“…Experimental results are presented to demonstrate and validate effectiveness of the technique used.…”
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Accelerating DNA sequence alignment based on smith waterman algorithm using recursive variable expansion / Muhamad Faiz Ismail
Published 2014“…We generalize the approach by proposing a framework such that the technique can be applied to a large range of DP problems. Finally, we validate the proposed DP framework using the Smith-Waterman (SW) algorithm, which is a widely used, computation and data intensive application in bioinformatics. …”
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Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN)
Published 2011“…ANNs are particularly useful for complex pattern recognition and classification tasks. The capability of learning from examples, the ability to reproduce arbitrary non-linear functions of input, and the highly parallel and regular structure of ANNs make them especially suitable for pattern recognition tasks. …”
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Proceeding Paper -
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Flexible job shop scheduling using priority heuristics and genetic algorithm
Published 2010“…Then, the validation of proposed genetic algorithm with reinforced initial population (GA2) has been checked with random keys genetic algorithm (RKGA). …”
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Distributed generation system using parallel inverters supplied by unstable DC source
Published 2009“…High frequency third harmonic injection PWM (THIPWM) was employed to reduce the total harmonic distortion and to make maximum use of the DC bus voltage. The generation of control algorithm for three-phase inverter is implemented in Digital Signal Processing (DSP) boards. …”
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Partitioning techniques and their parallelization for stiff system of ordinary differential equations
Published 2007“…Parallelizing the right algorithm in the partitioning code will give a better perfonnance with shorter execution times. …”
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…This is believed to be due to the different approaches of both classifiers in capturing data pattern for classification. In terms of computational time, compared to GS-tuned models and the respective HS hybrids, the proposed hybrid MHS-SVM and MHS-RF have reported time improvement of more than 50%, while the parallel computation have saved up approximately 80% of the computational time. …”
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Development of a heuristic procedure for balancing mixed-model parallel assembly line type II
Published 2010“…To solve these problems, two heuristic algorithms were developed and coded in MATLAB®. The first one allocates each model to only one parallel assembly line and achieves the initial arrangement of tasks with the minimum number of workstations for each line. …”
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