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  1. 1
    Features selection for intrusion detection system using hybridize PSO-SVM

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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  2. 2
    Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde

    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 support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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  3. 3
    Developing Bus Tracking System that predicts the arrival times of public buses at Universiti Teknologi PETRONAS (UTP) bus stops.

    Developing Bus Tracking System that predicts the arrival times of public buses at Universiti Teknologi PETRONAS (UTP) bus stops. by Mohd Akhir, Norhasiah

    Published 2004
    “…The scope of the project includes developing an algorithm, the research and analysis of GPS and the use of SMS. …”
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    Final Year Project
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  4. 4
    Computing the autopilot control algorithm using predictive functional control for unstable model

    Computing the autopilot control algorithm using predictive functional control for unstable model by H. A., Kasdirin, J. A., Rossiter

    Published 2009
    “…One basic Ballistic Missile model (10) is used as an unstable model to formulate the control law algorithm using PFC. …”
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  5. 5
    Voting algorithms for large scale fault-tolerant systems

    Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

    Published 2011
    “…Using a proper test-bed, after 10000 run times, we compared our newly proposed algorithm with the basic algorithm in terms of reliability and availability. …”
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  6. 6
    System identification using Extended Kalman Filter

    System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

    Published 2017
    “…Many algorithm have been proposed to do an estimation process such as Lavemberg-Marquardt (LM), Orthogonal Least Square (OLS), Recursive Prediction Error (RPE) and Modified Recursive Prediction Error (MRPE). …”
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  7. 7
    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier

    Predicting hearing loss symptoms from Audiometry data using FP-Growth Algorithm and Bayesian Classifier by G. Noma, Nasir, Mohd Khanapi, Abd Ghani, Mohamad Khir , Abdullah, Noorizan , Yahya

    Published 2013
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  8. 8
    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak

    Mining The Basic Reproduction Number (R0) Forecast For The Covid Outbreak by Rajogoval, Illayakantthan

    Published 2022
    “…All the classification accuracies obtained were above the baseline accuracy. The COVID-19 Basic Reproduction Number, R0 a predictive model is developed using a linear regression classification algorithm to predict the COVID-19 Basic Reproduction Number, Robased on the actual COVID-19 Basic Reproduction Number, R0. …”
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    Monograph
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  9. 9
    Communication and computational cost on parallel algorithm of PDE elliptic type

    Communication and computational cost on parallel algorithm of PDE elliptic type by Alias, Norma

    Published 2009
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    Book Section
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  10. 10
    Predicting Flow Rate of V-Shape Customm Tank Using Derivative Free Recursive Algorithm

    Predicting Flow Rate of V-Shape Customm Tank Using Derivative Free Recursive Algorithm by Tawfeiig, Huzzaifa, Asirvadam , Vijanth Sagayan, Saad , Nordin

    Published 2011
    “…This prediction can be used in controlling the custom tank (predictive control). …”
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    Citation Index Journal
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  11. 11
    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller

    Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

    Published 2010
    “…The design schemes of modeling adaptive and predictive FLC (APFLC) is described as follow: Basic FLC, Predictive FLC (PFLC) and APFLC. …”
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  12. 12
    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction

    Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

    Published 2023
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  13. 13
    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique

    Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique by Abulifa, Abdulhadi Abdulsalam

    Published 2022
    “…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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  14. 14
    Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive

    Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive by Al-Bared, M.A.M., Mustaffa, Z., Armaghani, D.J., Marto, A., Yunus, N.Z.M., Hasanipanah, M.

    Published 2021
    “…Then, these basic properties were selected as input variables to predict the UCS values through the use of two hybrid intelligent systems i.e., the neuro-swarm and the neuro-imperialism. …”
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  15. 15
    Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive

    Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive by Al-Bared, M.A.M., Mustaffa, Z., Armaghani, D.J., Marto, A., Yunus, N.Z.M., Hasanipanah, M.

    Published 2021
    “…Then, these basic properties were selected as input variables to predict the UCS values through the use of two hybrid intelligent systems i.e., the neuro-swarm and the neuro-imperialism. …”
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  16. 16
    PREDICTING FLOW RATE AND LEVEL OF CUSTOM TANK USING PARTICLE FILTER

    PREDICTING FLOW RATE AND LEVEL OF CUSTOM TANK USING PARTICLE FILTER by TAWFEIG AHMED IZZELDIN, HUZAIFA

    Published 2009
    “…This prediction can be used in controlling the custom tank (predictive control). …”
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    Final Year Project
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  17. 17
    Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms

    Landslide susceptibility mapping at VAZ watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF)... by Pradhan, Biswajeet, Mohammad Zare, Pourghasemi, Hamid Reza, Vafakhah, Mahdi

    Published 2013
    “…In this study, both MLP and RBF algorithms were used in artificial neural network model. …”
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  18. 18
    Machine learning as new approach for predicting of maxillary sinus volume, a sexual dimorphic study

    Machine learning as new approach for predicting of maxillary sinus volume, a sexual dimorphic study by Hamd, Zuhal Y., Aljuaid, Hanan, Alorainy, Amal I., Osman, Eyas G., Abuzaid, Mohamed, Elshami, Wiam, Elhussein, Nagwan, Gareeballah, Awadia, Pathan, Refat Khan, Naseer, K.A., Khandaker, Mayeen Uddin *, Ahmed, Wegdan

    Published 2023
    “…In this retrospective study, we used data from 150 patients with normal maxillary sinuses to train and evaluate a Python ML algorithm for its ability to predict MSV from basic patient demographics (age, gender) and sinus length measurements in three directions (anteroposterior, mediolateral, and superoinferior). …”
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  19. 19
    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization

    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

    Published 2018
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  20. 20
    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization

    A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization by Ee, L.K., Aziz, I.A.

    Published 2018
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