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  1. 1
    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. …”
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  2. 2
    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm

    Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

    Published 2008
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  3. 3
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…GT-Power is one of the CAE tools available in GT-SUITE offers the only true "virtual engine/power train" tool, capable of integrated simulations of the total engine and power train system. …”
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    Proceeding Paper
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  4. 4
    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments

    Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

    Published 2006
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  5. 5
    An Educational Tool Aimed at Learning Metaheuristics

    An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

    Published 2020
    “…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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    Conference or Workshop Item
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  6. 6
    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment

    A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

    Published 2013
    “…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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  7. 7
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
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  8. 8
    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
    “…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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  9. 9
    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…As for the implementation of MPCA in feature extraction for BOD and COD, there were only 4 inputs required to explain at least 99.999% variability for both analyses. Altogether, for BOD, the BR algorithm with 60% training and 12 hidden nodes gives R=0.7825 whereas for COD, the BR algorithm with 70% training and 10 hidden nodes gives R=0.6716. …”
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    Monograph
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  10. 10
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
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    Monograph
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  11. 11
    DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS

    DESIGN AND IMPLEMENTATION OF INTELLIGENT MONITORING SYSTEMS FOR THERMAL POWER PLANT BOILER TRIPS by FIRAS BASIM, ISMAIL ALNAIMI

    Published 2011
    “…An integrated plant data preparation framework for seven boiler trips with related operational variables, has been proposed for the training and validation of the proposed artificial intelligent systems. …”
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  12. 12
    AI powered asthma prediction towards treatment formulation: an android app approach

    AI powered asthma prediction towards treatment formulation: an android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Md Muzahid, Abu Jafar, Sarker, Md Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md

    Published 2022
    “…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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  13. 13
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…The firefly algorithm remains a feasible alternative for shallow architectural network models, while metaheuristic algorithms such as the Particle swarm algorithm and Bat algorithm are better options for deeper architectural network models. …”
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  14. 14
    Daily rainfall runoff modeling using artificial neural network for sungai Sarawak Kanan upper catchment

    Daily rainfall runoff modeling using artificial neural network for sungai Sarawak Kanan upper catchment by Ong, Khin Kiat.

    Published 2005
    “…Judging on coefficient of correlation R, one layered training algorithm trainoss (R = 0.839) with 150 hidden neurons and 5 days backdated performed the best for the simulations. …”
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    Final Year Project Report / IMRAD
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  15. 15
    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…Results showed that GA was able to select the variables correctly, while also being an easy-to-use variable selection tool. …”
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  16. 16
    Soil Pore Water Pressure and River Suspended Sediment Modelling using Artificial Neural Networks

    Soil Pore Water Pressure and River Suspended Sediment Modelling using Artificial Neural Networks by Ul Mustafa, Muhammad Raza

    Published 2012
    “…ANN models are mostly preferred as a predictive tool because of their ability to map nonlinear patterns between the dependent and independent variables without a mathematical description of the physical process involved. …”
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  17. 17
    Modeling and forecasting of injected fuel flow using neural network

    Modeling and forecasting of injected fuel flow using neural network by Z., Saad, M. K., Osman, S., Omar, Mohd Yusoff, Mashor, Prof. Dr.

    Published 2011
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    Working Paper
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  18. 18
    AI powered asthma prediction towards treatment formulation : An android app approach

    AI powered asthma prediction towards treatment formulation : An android app approach by Murad, Saydul Akbar, Adhikary, Apurba, Muzahid, Abu Jafar Md, Sarker, Md. Murad Hossain, Khan, Md. Ashikur Rahman, Hossain, Md. Bipul, Bairagi, Anupam Kumar, Masud, Mehedi, Kowsher, Md.

    Published 2022
    “…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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  19. 19
    An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration

    An optimum drill bit selection technique using artificial neural networks and genetic algorithms to increase the rate of penetration by Momeni, M., Hosseini, S.J., Ridha, S., Laruccia, M.B., Liu, X.

    Published 2018
    “…This paper discusses bit selection by employing a method of combining Artificial Neural Network (ANN) and the computation of Genetic Algorithm (GA). In this method, offset well drilling records are used for training the ANN model and International Association Drilling Contractors (IADC) bit codes are used to name each bit. …”
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  20. 20
    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications

    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

    Published 2025
    “…The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”
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