Search Results - (( frequency classification mining algorithm ) OR ( parallel optimization method algorithm ))
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1
Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm
Published 2023“…Classification (of information); Data mining; Digital forensics; Forestry; Learning algorithms; Loudspeakers; Motion compensation; Nearest neighbor search; Speech recognition; Trees (mathematics); K-near neighbor; Logistic model tree; Logistics model; Mel frequency cepstral co-efficient; Mel frequency cepstral coefficient; Mel-frequency cepstral coefficients; Mining classification; Model trees; Nearest-neighbour; Speaker identification systems; Authentication…”
Conference Paper -
2
An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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3
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Citation Index Journal -
4
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
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5
Rough set discretization: equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system
Published 2017“…Discretization of real value attributes is a vital task in data mining, particularly in the classification problem. …”
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Article -
6
Rough set discretization: Equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system
Published 2016“…Discretization of real value attributes is a vital task in data mining, particularly in the classification problem. …”
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Conference or Workshop Item -
7
Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System
Published 2016“…Discretization of real value attributes is a vital task in data mining, particularly in the classification problem. …”
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Book Chapter -
8
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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9
Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…The crosssubject and subject-based experiments were conducted to evaluate the classifers’ performance. The top 10 association rules generated by the RCAR classifer will be examined to determine the possible relationship between the EEG signal’s frequency changes and game-induced emotions. …”
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Article -
10
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Any optimization algorithm is suitable for only a specific domain of optimization problems. …”
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11
Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms
Published 2015“…This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. …”
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Article -
12
Investigation on the dynamic of computation of semi autonomous evolutionary computation for syntactic optimization of a set of programming codes
Published 2007“…Genetic Algorithm as one of the Evolutionary Computation method improve the execution of parallel programming codes by optimizing the number of processors and the distribution of data. …”
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Research Report -
13
Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design
Published 2024“…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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Article -
14
Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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15
Classification of metamorphic virus using n-grams signatures
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16
Analysis of evolutionary computing performance via mapreduce parallel processing architecture / Ahmad Firdaus Ahmad Fadzil
Published 2014“…Examples of EC such as Genetic Algorithm (GA) and PSO (Particle Swarm Optimization) are prevalent due to their efficiency and effectiveness. …”
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17
Distributed parallel deep learning with a hybrid backpropagation-particle swarm optimization for community detection in large complex networks
Published 2022“…Next, the method is integrated with two optimization algorithms: (1) backpropagation (BP), which optimizes deep learning locally within each local chunk of the CN; (2) particle swarm optimization (PSO), which is used to improve the BP optimization involving all CN chunks. …”
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Article -
18
PID Parameters Improvement for AGC in Three Parallel-Connected Power Systems
Published 2016“…The AGC loop is used to minimize the frequency deviation and control the power exchange in order to maintain them at their scheduled values due to the changes of the step-load disturbance. The optimal parameters of the PID scheme optimized by the proposed MS algorithm are compared with that one’s obtained by GA algorithm, and the proposed method has proven that its performance is more efficient and improved as well. …”
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Conference or Workshop Item -
19
Design and analysis of high performance matrix filling for DNA sequence alignment accelerator using asic design flow: article / Nurzaima Mahmod
“…The scope of this paper is to optimize the DNA sequences alignment on the matrix rilling module by implementing a parallel method of the Smith-Waterman algorithm. …”
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Article -
20
Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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