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  1. 1
    Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems

    Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems by Ismail, Zuhaimy, Loh, Ser Lee

    Published 2009
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  2. 2
    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement

    Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement by Karami, Mahdi

    Published 2011
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  3. 3
    Ant colony optimization for solving solid waste collection scheduling problems

    Ant colony optimization for solving solid waste collection scheduling problems by Ismail, Zuhaimy, Loh, S. L.

    Published 2009
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  4. 4
    Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz

    Predicting mortality of Malaysian patients with acute coronary syndrome (ACS) subtypes using machine learning and deep learning approaches / Muhammad Firdaus Aziz by Muhammad Firdaus , Aziz

    Published 2022
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  5. 5
    Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application

    Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

    Published 2023
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  6. 6
    Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging

    Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging by Norhasmira, Mohammad, Anuar Mikdad, Muad, Rohana, Ahmad, Mohd Yusmiaidil, Putera Mohd Yusof

    Published 2022
    “…Conclusions: The application of digital imaging and deep learning techniques used by the DP-AC and convolutions neural network algorithms to segment and identify premolars provides promising results for semi-automated forensic dental staging in the future…”
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  7. 7
    Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network

    Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network by Asirvadam , Vijanth Sagayan, McLoone, Sean

    Published 2007
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  8. 8
    Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations

    Applications of Data-driven Models for Daily Discharge Estimation Based on Different Input Combinations by Kumar M., Elbeltagi A., Pande C.B., Ahmed A.N., Chow M.F., Pham Q.B., Kumari A., Kumar D.

    Published 2023
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  9. 9
    3D modeling of indoor surfaces with occlusion and clutter

    3D modeling of indoor surfaces with occlusion and clutter by S. A., Abdul Shukor, K. W., Young, Rushforth, E. J.

    Published 2011
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  10. 10
    Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis

    Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis by Ahmad Izzuddin, Tarmizi, Mat Safri, Norlaili, Othman, Mohd Afzan

    Published 2021
    “…Recently, due to the popularity of end-to-end deep learning, the applicability of algorithms such as convolutional neural networks (CNN) has been explored to achieve the mentioned tasks. …”
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  11. 11
    Control of direct multi- input multi-output (MIMO) using single-phase matrix converter (SPMC) topology / Mohd Shukri Mohd Ghazali

    Control of direct multi- input multi-output (MIMO) using single-phase matrix converter (SPMC) topology / Mohd Shukri Mohd Ghazali by Mohd Ghazali, Mohd Shukri

    Published 2023
    “…There are numerous studies demonstrating the practical applications of power electronic converters. There are four types of converters, DC-DC, AC-AC, AC-DC, and DC-AC energy conversion. …”
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  12. 12
    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome

    Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

    Published 2014
    “…Accordingly, the proposed “hybrid model” demonstrated to be applicable for classification problems in different medical areas, particularly for early detection of ACS. …”
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  13. 13
    Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review

    Prediction of oil and gas pipeline failures through machine learning approaches: A systematic review by Al-Sabaeei, A.M., Alhussian, H., Abdulkadir, S.J., Jagadeesh, A.

    Published 2023
    “…This review also includes a bibliometric analysis of the literature, highlighting common ML techniques, investigated failures, and experimental tests. It also provides in-depth details, summarized in tables, on different failure types, commonly used ML algorithms, and data resources, with critical discussions. …”
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  14. 14
    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution

    Parameter extraction of solar photovoltaic modules using penalty-based differential evolution by Ishaque, K., Salam, Z., Mekhilef, Saad, Shamsudin, A.

    Published 2012
    “…The analyses carried out using synthetic current-voltage (I-V) data set showed that the proposed P-DE outperforms other Evolutionary Algorithm methods, namely the simulated annealing (SA), genetic algorithm (GA), and particle swarm optimization (PSO). …”
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  15. 15
    Short-Term forecasting of floating photovoltaic power generation using machine learning models

    Short-Term forecasting of floating photovoltaic power generation using machine learning models by Mohd Herwan, Sulaiman, Mohd Shawal, Jadin, Zuriani, Mustaffa, Mohd Nurulakla, Mohd Azlan, Hamdan, Daniyal

    Published 2024
    “…The results indicate that the Neural Networks model consistently outperforms the other machine learning algorithms in terms of predictive accuracy. …”
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  16. 16
    Segmentation Word to Improve Performance Sentiment Analysis for Indonesian Language

    Segmentation Word to Improve Performance Sentiment Analysis for Indonesian Language by Siti Mujilahwati, Siti Mujilahwati, M. Safar, Noor Zuraidin, Supriyanto, Catur

    Published 2024
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  17. 17
    InnoSAT Attitude Control System Based on Adaptive Neuro-Controller

    InnoSAT Attitude Control System Based on Adaptive Neuro-Controller by Sharun, Siti Maryam, Mashor, Mohd Yusoff, Mohd Nazid, Norhayati, Yaacob, Sazali, Wan Jaafar, Wan Nurhadani

    Published 2011
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  18. 18
    Optimization of waterjet paint removal operation using artificial neural network

    Optimization of waterjet paint removal operation using artificial neural network by Alzaghir, Abdullah Faisal, Mohd Nazir, Mat Nawi, Asmelash, Mebrahitom Asmelash, Azmir, Azhari

    Published 2022
    “…Into training and testing, a back-propagation algorithm used in the ANN model has successfully predicted the surface roughness with an average of 80% accuracy and 3.02 mean square error. …”
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  19. 19
    Development of an integrated circuit topology using multilevel inverter and matrix converter

    Development of an integrated circuit topology using multilevel inverter and matrix converter by Al-Mahrouk, Akram Mohammed

    Published 2020
    “…Multilevel Inverter (MI) is a device to convert Direct Current (DC) power to Alternating Current (AC) power. The MI is widely used in renewable energy applications such as Photovoltaic (PV) solar cells and wind turbine systems. …”
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  20. 20
    Indirect Rotor Field Oriented Control of Induction Motor With Rotor Time Constant Estimation

    Indirect Rotor Field Oriented Control of Induction Motor With Rotor Time Constant Estimation by Moh'd Radwan, Eyad Moh'd

    Published 2004
    “…Field oriented control of induction motor is gaining wides acceptance in high performance AC motor drive applications. Field oriented control, in its both forms as a direct or indirect, gives the AC motor dynamics that are equivalent to that of a DC motor. …”
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