Search Results - (( program implementation matching algorithm ) OR ( parallel classification system algorithm ))

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    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    “…This method resulted around 99% of classification rate. 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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    Thesis
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    Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

    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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    Evaluation of the effectiveness and efficiency of Wagner and Fischer algorithm in retrieving Hadith translated documents / Kamarul Arifin Muhamad by Muhamad, Kamarul Arifin

    Published 2002
    “…First experiment uses exact match, which is no method, is apply. Second experiment uses dynamic programmings apply with Wagner and Fischer algorithm.…”
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    Selection of prospective workers using profile matching algorithm on crowdsourcing platform by Cucus, Ahmad, Aji, Luhur Bayu, Al Fahim, Mubarak Ali, Aminuddin, Afrig, Farida, Lilis Dwi

    Published 2022
    “…These criteria become variables that are used in the profile matching algorithm to find workers who best match the profiles offered. …”
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    Design and analysis of management platform based on financial big data by Chen, Yuhua, Mustafa, Hasri, Zhang, Xuandong, Liu, Jing

    Published 2023
    “…In order to make financial big data generate business value and improve the information application level of financial management, aiming at the high error rate of current financial data classification system, this article adopts the fuzzy clustering algorithm to classify financial data automatically, and adopts the local outlier factor algorithm with neighborhood relation (NLOF) to detect abnormal data. …”
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    Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui by Muhammad Faisal , Siddiqui

    Published 2016
    “…Complex multiplier, complex matrix multiplier and pseudo-inverse modules are designed according to the algorithmic needs to increase the efficiency of the system. …”
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    An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players by Mohammad Zukuwwan, Zainol Abidin

    Published 2021
    “…The system can provide the team formation and players, and calculate the strength of the KFA team to justify its winning and loss of 2019 FA Cup and Malaysia Cup final matches respectively. This system can help coaches to solve problem regarding the strong team development with available players and motivate the use of decision technologies in sports able to match the results from the real world implementation.…”
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    Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System by Ali, Mohammed Hasan, Mohamed Fadli, Zolkipli

    Published 2019
    “…The approach was tested on the KDD Cup99 intrusion detection dataset and the results proved the proposed PSO-RKFLN as an accurate, reliable, and effective classification algorithm.…”
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    Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

    Published 2011
    “…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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