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  1. 1
    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
    “…Hence, this study suggests improvement on the algorithm development for future research.…”
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  2. 2
    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan

    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

    Published 2018
    “…Apart from that, sizing algorithm with DEA was also discovered to outperform sizing algorithms with selected computational intelligence, i.e. …”
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  3. 3
    Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman

    Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

    Published 2017
    “…Selecting a successor is an important part within an organization to finding a replacement based on the position. …”
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  4. 4
    Statistical fixed range multiple selection algorithm for peer-to-peer system

    Statistical fixed range multiple selection algorithm for peer-to-peer system by Kweh, Yeah Lun, Othman, Mohamed, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2010
    “…In this research, a new multiple selection algorithm, which is known as "statistical fixed range multiple selection algorithm" is proposed. …”
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  5. 5
    Static range multiple selection algorithm for peer-to-peer system

    Static range multiple selection algorithm for peer-to-peer system by Othman, Mohamed, Kweh, Yeah Lun, Ahmad, Fatimah, Ibrahim, Hamidah

    Published 2011
    “…In this research, a new multiple selection algorithm, which is known as "static range statistical multiple selection algorithm" is proposed. …”
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  6. 6
    SURE-Autometrics algorithm for model selection in multiple equations

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

    Published 2016
    “…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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  7. 7
    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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  8. 8
    Route Optimization System

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…This algorithm is an exact algorithm that is specifically for finding the shortest route in a network. …”
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  9. 9
    Algorithmic approaches in model selection of the air passengers flows data

    Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

    Published 2015
    “…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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  10. 10
    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection

    Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection by Almazini, Hussein

    Published 2022
    “…Experimental results of the EBGWO algorithm on the NSL-KDD dataset in terms of number of selected features and classification accuracy are superior to other benchmark optimisation algorithms. …”
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  11. 11
    Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm

    Web-Based Route Optimization System For Logistic Using Agglomerative Clustering And Genetic Algorithm by Tan, Chee Kuan

    Published 2020
    “…Thus, a web-based route optimization is proposed with the objectives of developing a system that is able to find the shortest route to deliver. …”
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  12. 12
    Some metaheuristic algorithms for solving multiple cross-functional team selection problems

    Some metaheuristic algorithms for solving multiple cross-functional team selection problems by Ngo, S.T., Jaafar, J., Izzatdin, A.A., Tong, G.T., Bui, A.N.

    Published 2022
    “…We can find solutions to the team selection problem in many different areas. …”
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  13. 13
    An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation

    An Evolutionary Algorithm: An Enhancement of Binary Tournament Selection for Fish Feed Formulation by Soong, Cai Juan, Abd Rahman, Rosshairy, Ramli, Razamin, Abd Manaf, Mohammed Suhaimee, Chek-Choon, Ting

    Published 2022
    “…*e novelty of the proposed SD tournament selection is compared with BT selection in terms of searching for an efficient but not myopic algorithm. …”
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  14. 14
    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…Beside that, this research also has to fulfill the objective of find the comparison of the three types of selection methods which roulette wheel selection, tournament selection and rank selection. …”
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  15. 15
    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. Third, using a modified k-Nearest Neighbor method as well as an improved method of backpropagation neural networks, the classification process was advanced based on optimum arrays of the features selected by genetic algorithms. …”
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  16. 16
    Development of low power viterbi decoder on complex programmable logic device platform

    Development of low power viterbi decoder on complex programmable logic device platform by Abu, Mohd Azlan

    Published 2018
    “…For the path metric updater unit (PMU), the traditional method of Viterbi algorithm is to store the selected minimum value of branch metric in the memory unit. …”
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  17. 17
    Development Of Fall Risk Clustering Algorithm In Older People

    Development Of Fall Risk Clustering Algorithm In Older People by Wong, Kam Kang

    Published 2020
    “…Therefore, the aim of this study is to develop a clustering-based fall risk algorithm which can provide assistances for clinician in management of falls. …”
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  18. 18
    Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm

    Bio-inspired computation: Recent development on the modifications of the cuckoo search algorithm by Haruna, Chiroma, Herawan, Tutut, Iztok, Fister Jr, Iztok, Fister, Abdulkareem, Sameem, Shuib, Liyana, Mukhtar, Fatihu Hamza, Younes, Saadi, Abubakar, Adamu

    Published 2017
    “…The purpose of this study is to assist potential developers in selecting the most suitable cuckoo search variant, provide proper guidance in future modifications and ease the selection of the optimal cuckoo search parameters. …”
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  19. 19
    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers

    Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

    Published 2016
    “…We develop Robust Forward Selection algorithm based on RFCH correlation coefficient (RFS.RFCH) because FS.Winso is not robust to multivariate outliers. …”
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  20. 20
    Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification

    Swarm intelligence-based feature selection for amphetamine-type stimulants (ATS) drug 3D molecular structure classification by Draman @ Muda, Azah Kamilah, Mohd Yusof, Norfadzlia, Pratama, Satrya Fajri

    Published 2021
    “…For this purpose, the binary version of swarm algorithms facilitated with the S-shaped or sigmoid transfer function known as binary whale optimization algorithm (BWOA), binary particle swarm optimiza-tion algorithm (BPSO), and new binary manta-ray foraging opti-mization algorithm (BMRFO) are developed for feature selection. …”
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