Search Results - (( java implementation learning algorithm ) OR ( network selection based algorithm ))

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  1. 1

    A malware analysis and detection system for mobile devices / Ali Feizollah by Ali, Feizollah

    Published 2017
    “…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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  2. 2

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
    “…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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  3. 3

    Static and self-scalable filter range selection algorithms for peer-to-peer networks by Kweh, Yeah Lun

    Published 2011
    “…For peer-to-peer networks, Loo (2005) selection algorithm has been selected as the benchmark as it is an established algorithm that claimed to be the best proposed for this network. …”
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  4. 4

    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm by Zeni, Saltihie

    Published 2012
    “…Meanwhile in LEACH, the cluster head selection was based on distributed algorithm. Both of these protocols was implemented in network simulator to compare the performance. …”
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  5. 5

    Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm by Vincent Chung, Hamzarul Alif Hamzah, Norah Tuah, Kit, Guan Lim, Min, Keng Tan, Kenneth Tze Kin Teo

    Published 2020
    “…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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    Article
  6. 6

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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  7. 7

    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

    Published 2022
    “…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  10. 10

    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…In the initial stage, the dynamic Bayesian networks models are constructed based on a set of lexical cues selected tentatively from the dialogue corpus. …”
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    An energy based cluster head selection unequal clustering algorithm with dual sink (ECH-DUAL) for continuous monitoring applications in wireless sensor networks by Alagirisamy, Mukil, Chow, Chee Onn

    Published 2018
    “…In our algorithm, tentative cluster head is selected based on energy based timer, residual energy, node IDs and trust value. …”
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    Article
  13. 13

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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    Article
  14. 14

    An adaptive routing algorithm: enhanced confidence-based Q routing algorithm in network traffic by Yap, Soon Teck, Othman, Mohamed

    Published 2004
    “…Confidence-based Q (CQ) Routing Algorithm is an adaptive network routing algorithm. …”
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    Adaptive resource allocation algorithms with QoS support based on network conditions using fuzzy logic system for IEEE 802.11n networks / Bakeel Hussein Naji Maqhat by Naji Maqhat, Bakeel Hussein

    Published 2016
    “…The DSMF is an intelligent based system approach to support selective retransmission process and to enhance the performance by means of sensing the network channel conditions and updating the transmission decision. …”
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  17. 17

    An enhanced cluster head selection algorithm for routing in mobile AD-HOC network by Abdulsaheb, Ghaida Muttasher

    Published 2017
    “…The performance of ECRP algorithms was compared with other cluster based algorithms. …”
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  18. 18

    Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

    Published 2004
    “…These two adaptive routing algorithms enhance the existing Confidence-based Q (CQ) and Confidence-based Dual Reinforcement Q (CDRQ) Routing Algorithms. …”
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    Hybrid LTE-Vanets Based Optimal Radio Access Selection by Harum, Norharyati, Abu, Nor Azman, Ali, Mohanad Faeq

    Published 2018
    “…The periodically broadcasted network information supports mobile users to make their selection decisions;mobiles consider their own individual preferences,cost and partial QoS information signaled by the network while making their decision.The switches algorithm between VANET and LTE based on the load value of network and quality of service requirements were proposed.The simulation results have shown that the proposed algorithm has better performance compared with LTE and VANETs separately in terms of packet delivery ratio,latency and application-level throughput. …”
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