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  1. 1
    Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm

    Wireless sensor nodes deployment using multi-robot based on improved spanning tree algorithm by Arezoumand, Reza

    Published 2015
    “…Developing an exploration algorithm based on spanning tree is the main contribution. …”
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  2. 2
    Predictive models for hotspots occurrence using decision tree algorithms and logistic regression.

    Predictive models for hotspots occurrence using decision tree algorithms and logistic regression. by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…Furthermore, the logistic regression model outperforms the decision tree algorithms with the accuracy of 68.63%. …”
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  3. 3
    Comparison of path planning in simulated robot

    Comparison of path planning in simulated robot by Ch’ng, Chee Yu’ng

    Published 2020
    “…There are 4 path planning algorithms will be compared, which are Dijkstra’s algorithm, A* algorithm, RapidExploring Random Tree (RRT) algorithm, and the last one is an algorithm modified from A*. …”
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  4. 4
    An optimized attack tree model for security test case planning and generation

    An optimized attack tree model for security test case planning and generation by Omotunde, Habeeb, Ibrahim, Rosziati, Ahmed, Maryam

    Published 2018
    “…This paper presents an attack tree modeling algorithm for deriving a minimal set of effective attack vectors required to test a web application for SQL injection vulnerabilities. …”
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  5. 5
    Optimized tree-classification algorithm for classification of protein sequences

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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  6. 6
    Optimized tree-classification algorithm for classification of protein sequences

    Optimized tree-classification algorithm for classification of protein sequences by Iqbal, M.J., Faye, I., Said, A.M., Belhaouari Samir, B.

    Published 2016
    “…The existing classification methods are performing well on a very limited data; however the rapid increase in the genomic data leads to the development of improved computational methods. In this work, we have proposed an optimized tree-classification technique which uses cluster k nearest neighbor classification algorithm to classify protein sequences into superfamilies. …”
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  7. 7
    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking

    Improving performance of automated coronary arterial tree center-line extraction, stent localization and tracking by Boroujeni, Farsad Zamani

    Published 2012
    “…Over the last decade, many algorithms have been developed to address this problem. …”
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  8. 8
    Priority and dynamic quantum time algorithms for central processing unit scheduling

    Priority and dynamic quantum time algorithms for central processing unit scheduling by Mohammed, Maysoon A.

    Published 2018
    “…Central Processing Unit is scheduled using different types of scheduling algorithms. One of the most widely algorithm used in scheduling with sharing and batch operating systems is Round Robin. …”
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  9. 9
    The effectiveness of bottom up technique with probabilistic approach for a Malay parser

    The effectiveness of bottom up technique with probabilistic approach for a Malay parser by Muhammad Azhar Fairuzz Hiloh, Mohd Juzaiddin Ab Aziz, Lailatul Qadri Zakaria

    Published 2018
    “…Parsing is a process of analyzing the input string in a sentence to define the syntax structures according to rules of grammar. This task is performed by a parser which will produce a parse tree as output. …”
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  10. 10
    Waste management using machine learning and deep learning algorithms

    Waste management using machine learning and deep learning algorithms by Sami, Khan Nasik, Amin, Zian Md Afique, Hassan, Raini

    Published 2020
    “…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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  11. 11
    A Model for Evaluation of Cryptography Algorithm on UUM Portal

    A Model for Evaluation of Cryptography Algorithm on UUM Portal by Norliana, Abdul Majid

    Published 2004
    “…The simulation model was developed using Active Server Page, JavaScript and SQL 7.0 as database. …”
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  12. 12
    Knowledge-based system developement for the game congkak / Syah Ali Reza Yaacob

    Knowledge-based system developement for the game congkak / Syah Ali Reza Yaacob by Yaacob, Syah Ali Reza

    Published 2006
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  13. 13
    Fraud detection in shipping industry based on location using machine learning comparison techniques

    Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

    Published 2023
    “…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”
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  14. 14
    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem

    A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

    Published 2016
    “…The SVGPM performance is compared against current methods in developing a prediction model for IDS. In the third experiment, SVGPM is evaluated on wilt disease data set from remote sensing study, to identify wilt diseased trees in high-resolution image. …”
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  15. 15
    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation

    Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

    Published 2020
    “…Among them, a prediction task is widely applied in many real applications such as in manufacturing, medical, business and mainly for developing prediction model. …”
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  16. 16
    Prevention And Detection Mechanism For Security In Passive Rfid System

    Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

    Published 2013
    “…In addition, the randomness of the session key generated from the MLCG is verified using NIST test suite. Besides that, the security of the proposed protocol is validated using the formal analysis tool, AVISPA. …”
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  17. 17
    Complex word identification model for lexical simplification in the Malay language for non-native speakers

    Complex word identification model for lexical simplification in the Malay language for non-native speakers by Salehah, Omar

    Published 2023
    “…This study consists of three modules, i) A Malay CWI dataset, ii) Malay CWI features with the new enhanced stemmer rules, and iii) A CWI model based on the Gradient Boosted Tree (GB) algorithm. The model is evaluated based on a state-of-the-art Malay corpus. …”
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  18. 18
    Random forest algorithm for co2 water alternating gas incremental recovery factor prediction

    Random forest algorithm for co2 water alternating gas incremental recovery factor prediction by Belazreg, L., Mahmood, S.M., Aulia, A.

    Published 2020
    “…A Random Forest prediction model that predicts the WAG incremental recovery factor as a function of the eight input vectors was developed. The optimum developed model consists of 60 decision trees with a maximum depth of seven (7). …”
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  19. 19
    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…Ten knowledge and domain experts provided positive feedback on the framework's verification, affirming the framework's robustness. Validation was conducted through three experiments involving four Java programs. …”
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  20. 20
    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms

    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

    Published 2022
    “…The development of Management Information Systems (MIS) is impossible without the use of machine learning (ML). …”
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