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  1. 1
    Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals

    Feature Selection using Binary Simulated Kalman Filter for Peak Classification of EEG Signals by Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Mohd Ibrahim, Shapiai, Asrul, Adam, Zulkifli, Md. Yusof, Kamil Zakwan, Mohd Azmi, Nor Hidayati, Abdul Aziz, Zuwairie, Ibrahim, Norrima, Mokhtar

    Published 2018
    “…Previously, an angle modulated simulated Kalman filter (AMSKF) algorithm has been implemented for feature selection in peak classification of electroencephalogram (EEG) signals. …”
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  2. 2
    Assessing the simulation performances of multiple model selection algorithm

    Assessing the simulation performances of multiple model selection algorithm by Yusof, Norhayati, Ismail, Suzilah, Tuan Muda, Tuan Zalizam

    Published 2015
    “…The Autometrics is an algorithm for single equation model selection.It is a hybrid method which combines expanding and contracting search techniques.In this study, the algorithm is extended for multiple equations modelling known as SURE-Autometrics.The aim of this paper is to assess the performance of the extended algorithm using various simulation experiment conditions. …”
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  3. 3
    Ant colony optimization for rule induction with simulated annealing for terms selection

    Ant colony optimization for rule induction with simulated annealing for terms selection by Saian, Rizauddin, Ku-Mahamud, Ku Ruhana

    Published 2012
    “…This paper proposes a sequential covering based algorithm that uses an ant colony optimization algorithm to directly extract classification rules from the data set.The proposed algorithm uses a Simulated Annealing algorithm to optimize terms selection, while growing a rule.The proposed algorithm minimizes the problem of a low quality discovered rule by an ant in a colony, where the rule discovered by an ant is not the best quality rule, by optimizing the terms selection in rule construction. …”
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  4. 4
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

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

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. © 2017, UK Simulation Society. …”
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  5. 5
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  6. 6
    Revisit of statistical selection algorithm for peer-to-peer system

    Revisit of statistical selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun

    Published 2008
    “…Over the years, the distributed computing environment has been developed so fast that there’s a need to develop an effective selection algorithm for it. Loo [9] has proposed a statistical selection algorithm with the same objective and run in the multicast / broadcast environment that has been proved that it is the best among others algorithm in the same platform in terms of the number of messages and the number of rounds needed to complete the searching process. …”
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  7. 7
    Improving on the network lifetime of clustered-based wireless sensor network using modified leach algorithm

    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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  8. 8
    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm

    Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

    Published 2019
    “…In conclusion, SURE(IFGLS)-Autometrics and SURE(EM)-Autometrics can be used as models selection algorithms. Additionally, both algorithms are suitable in improving performance of automated models selection procedures. …”
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  9. 9
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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  10. 10
    Encryption selection for WLAN IEEE802.11G

    Encryption selection for WLAN IEEE802.11G by Ahmad, Zahrol Azam

    Published 2013
    “…As for the solution, it proposes a mechanism of selecting encryption algorithms, which is able to help users to select the suitable encryption algorithm and encryption protocols for their secured communication in IEEE 802.11g WLAN. …”
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  11. 11
    Multiple equations model selection algorithm with iterative estimation method

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…This estimation method is equivalent to maximum likelihood estimation at convergence. Therefore, the algorithm is known as SUREIFGLS-Autometrics.Simulation and real data analyses were conducted to assess the performance of the algorithm.The simulation results reveal that the algorithm shows almost similar performances for all conditions involved. …”
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  12. 12
    The effect of GA parameters on the performance of GA-based QoS routing algorithm

    The effect of GA parameters on the performance of GA-based QoS routing algorithm by Yussof S., See O.H.

    Published 2023
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  13. 13
    A fault syndromes simulator for random access memories

    A fault syndromes simulator for random access memories by Wan Hasan, Wan Zuha, Abdul Halim, Izhal, Mohd Sidek, Roslina, Othman, Masuri

    Published 2008
    “…The simulator allows a user through a GUI to select a March based test algorithm depending on the desired fault coverage and diagnostic resolution. …”
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  14. 14
    A Simulation Framework For Performance Evaluation Of Network Selection Algorithms In Heterogeneous Wireless Networks.

    A Simulation Framework For Performance Evaluation Of Network Selection Algorithms In Heterogeneous Wireless Networks. by Hasib, Abdul, O. Fapojuwo, Abraham

    Published 2010
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  15. 15
    Improvement and performance analysis on statistical selection algorithms

    Improvement and performance analysis on statistical selection algorithms by Kweh, Yeah Lun, Othman, Mohamed

    Published 2006
    “…This new algorithm is developed based on the simulation of the real multicast environment. …”
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  16. 16
    Pressure vessel design simulation using hybrid harmony search algorithm

    Pressure vessel design simulation using hybrid harmony search algorithm by Alaa A., Alomoush, Mohammed I., Younis, Khalid S., Aloufi, Alsewari, Abdulrahman A., Kamal Z., Zamli

    Published 2019
    “…This paper presents successful hybrid algorithms with high performance to solve the pressure vessel design simulation. …”
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  17. 17
    Static and self-scalable filter range selection algorithms for peer-to-peer networks

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

    Published 2011
    “…Two multiple selection algorithm, which are known as “static filter range selection algorithm” and “self-scalable selection algorithm” are proposed. …”
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  18. 18
    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure

    Deterministic Mutation Algorithm As A Winner Over Forward Selection Procedure by Md Fahmi, Abd Samad

    Published 2016
    “…Two methods of model structure selection are closely looked into and these are deterministic mutation algorithm (DMA) and forward selection procedure (FSP). …”
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  19. 19
    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem

    Simulated Kalman Filter with modified measurement, substitution mutation and hamming distance calculation for solving traveling salesman problem by Suhazri Amrin, Rahmad, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

    Published 2022
    “…As a multi-agent algorithm, every agent in the population acts as a Kalman filter by using a standard Kalman filter framework, which includes a simulated measurement process and a best-so-far solution as a reference. …”
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  20. 20
    Automated surveillance in distributed, visual networks: an empirical comparison of recent algorithms

    Automated surveillance in distributed, visual networks: an empirical comparison of recent algorithms by Ahmed, Tarem, Ahmed, Supriyo, Pathan, Al-Sakib Khan

    Published 2014
    “…The selected algorithms were then applied in a distributed fashion at each node. …”
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