Search Results - (( simulation optimization protocol algorithm ) OR ( variable classification modeling algorithm ))

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  1. 1

    QTCP: an optimized and improved congestion control algorithm of high-speed TCP networks by Qureshi, Barkatullah, Othman, Mohamed, K. Subramaniam, Shamala, Abdul Hamid, Nor Asilah Wati

    Published 2011
    “…To overcome these problems Quick Transport Control Protocol (QTCP) algorithm based on optimizations of HS-TCP slow start algorithm and Additive Increase and Multiplicative Decrease (AIMD) algorithm have been proposed. …”
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    Conference or Workshop Item
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    An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

    Published 2016
    “…The marking probability mechanism was also studied to check how parameters in the traffic rate affect fairness. Extensive simulations were carried out to implement the algorithm using the NS2 simulator and compare the proposed marker algorithm with several other algorithms. …”
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    Article
  3. 3

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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    Thesis
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    OPTIMIZATION OF MOBILE TRANSPORT NETWORK USING INTERNET PROTOCOL/MULTI-PROTOCOL LABEL SWITCHING (IP/MPLS) APPROACH by Ngo, Lip Chee

    Published 2014
    “…This report focuses on a research-based project of the title ‘Optimization of Mobile Transport Network using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Approach’. …”
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    Final Year Project
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    A new particle swarm optimization for wireless mesh routing protocol by Abd. Rahman, Tharek

    Published 2008
    “…We test the propose algorithm in network simulator 2 (ns2). Based on the results, we proven that PSO-SIIW algorithm can be applied to MPR calculation in OLSR.…”
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    Monograph
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    An improved energy-efficient clustering protocol to prolong the wireless sensor network lifetime by Alhmood, Ali Abdul-Hussian Hassan

    Published 2021
    “…The simulation results prove that the IEECP prolongs the network lifetime better than Energy efficient clustering protocol based on K-means (EECPK-means)-midpoint algorithm (EECPK-means), Traffic-Aware Channel Access Algorithm (TACAA), and an optimal clustering mechanism based on Fuzzy C-means (OCM–FCM) protocols based on the First node die and Weighted first node die. …”
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    Thesis
  7. 7

    Performance Analysis of Routing Protocols in Wireless Sensor Networks by Htet, Kyaw Min

    Published 2014
    “…Stable Election Protocol (SEP) routing protocol is also simulated using MATLAB in this project and the evaluation of the performance of the protocol will be discussed.…”
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    Final Year Project
  8. 8

    Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication by JAM'AAH, SUUD

    Published 2021
    “…This algorithm only applies the optimization scaling factor at the bit node processing of the variable node operation. …”
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    Thesis
  9. 9

    OPTIMIZATION OF MOBILE TRANSPORT NETWORK USING INTERNET PROTOCOL/MULTI-PROTOCOL LABEL SWITCHING (IP/MPLS) APPROACH by Ngo, Lip Chee

    Published 2014
    “…This report focuses on a research-based project of the title ‘Optimization of Mobile Transport Network using Internet Protocol/Multi-Protocol Label Switching (IP/MPLS) Approach’. …”
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    Final Year Project
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    Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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    Article
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    Performance evaluation of mobile ad hoc network in wireless LAN / Norfadhilah Hasan by Hasan, Norfadhilah

    Published 2005
    “…The work presented in this paper evaluates the performance of two MANET routing protocol known as Dynamic Source Routing (DSR) and Temporally Ordered Routing Algorithm (TORA). …”
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    Thesis
  16. 16

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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    Article
  17. 17

    A green clustering protocol for mobile sensor network using particle swarm optimization by Latiff, N.M.A., NikAbdMalik, N., Latiff, A.H.A.

    Published 2016
    “…In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm. …”
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    Article
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    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
    “…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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    Article
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