Search Results - machine ((((loading program) OR (learning programs))) OR (learning program))

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    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele B.V., Mustapa S.I., Kanthasamy R., Mohammad N., AlTurki A., Babu T.S.

    Published 2023
    “…Biomass; Catalysis; Digital storage; Gasification; Gaussian distribution; Hydrogen production; Learning algorithms; Lime; Palm oil; Quadratic programming; Regression analysis; Sensitivity analysis; Synthesis gas; Co-gasification; Gaussian process regression; Hydrogen-rich syngas; Machine learning algorithms; Non-linear response; Performance; Quadratic modeling; Renewable energies; Support vectors machine; Syn gas; Support vector machines…”
    Article
  3. 3

    Single phase induction motor studies using MATLAB / Izmir Mohd Yatim by Mohd Yatim, Izmir

    Published 2007
    “…Simulation of a single phase induction machine will be performed by M-File programming and Simulink. …”
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    Thesis
  4. 4

    Genetic programming based machine learning in classifying public-private partnerships investor intention / Ahmad Amin ... [et al.] by Amin, Ahmad, Rahmawaty, Rahmawaty, Lautania, Maya Febrianty, Abdul Rahman, Rahayu

    Published 2023
    “…The PPP data was analyzed in this study using two machine learning approaches, Genetic Programming and conventional machine learning, with testing results showing that all machine learning algorithms from both approaches achieved high accuracy rates of over 80%, with the Genetic Programming machine learning outperformed the conventional approach. …”
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    Article
  5. 5

    A new domain specific scripting language for automated machine learning pipeline by Masrom, S., Rahman, A.S.A., Omar, N., Baharun, N.

    Published 2019
    “…In light of this situation, automated machine learning pipeline is highly beneficial. Research has proved that Genetic Programming is highly useful to find the best pipeline of an automated machine learning model. …”
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    Article
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    Effects Of Machine-learning Programming Simulator On Performance, Engagement And Perceived Motivation Of University Students In Learning Programming by Astono, Putri Tansa Trisna

    Published 2024
    “…The two technologies—Machine Learning Programming Simulator (MLProgramming Simulator) and Non Machine Learning Programming Simulator (NoML-Programming Simulator)—were the independent variable in this study. …”
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    Thesis
  7. 7

    Predictive analytics for learning performance in first-year university programming course by Kartiwi, Mira, Gunawan, Teddy Surya, Md Yusoff, Nelidya

    Published 2024
    “…This research aims to develop a machine learning model to predict student performance in programming courses offered within IT programs by analyzing gender, type of activity (readings, coding exercises, assignments), and frequency of access to different activities. …”
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    Proceeding Paper
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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    Article
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…One of the progressing works for automated machine learning improvement is the inclusion of evolutionary algorithm such as Genetic Programming. …”
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    Article
  10. 10

    Implementation of Health Monitoring System for Patients using Machine Learning Algorithms by Hariprasad, U.S., UshaSree, R.

    Published 2024
    “…Additionally, to enhance overall equipment effectiveness (OEE), lower electricity costs, and decrease unplanned downtime in manufacturing settings, we created a real-time system leveraging smart systems and machine learning. During testing on a manufacturing blender, this device tracked operational phases and load-balancing conditions well. …”
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    Article
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    Rapid software framework for the implementation of machine learning classification models by Rahman, A.S.A., Masrom, S., Rahman, R.A., Ibrahim, R.

    Published 2021
    “…However, to implement a complete machine learning model involves some technical hurdles such as the steep learning curve, the abundance of the programming skills, the complexities of hyper-parameters, and the lack of user friendly platform to be used for the implementation. …”
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    Article
  12. 12

    Teaching and learning via chatbots with immersive and machine learning capabilities by Nantha Kumar Subramaniam

    Published 2019
    “…Each of these chatbots focuses on different programming concepts or constructs. These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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    Conference or Workshop Item
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    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
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    Article
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    Harmonic effect between VSI and CSI using PWM control scheme by Muhammad Hifdzan Ilias

    Published 2009
    “…These simulations are implemented in the PSIM program in order to study the harmonics effects. These simulations are implemented by using two types of loads which are RL load and the induction motor fed drive. …”
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    Learning Object
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    PLC-based water filling machine simulator for teaching and learning activities / Kamaru Adzha Kadiran … [et al.] by Kadiran, Kamaru Adzha, Rifin, Rozi, Hussin, Mohamad Zhafran, Mat Saat, Ezril Hisham

    Published 2023
    “…The Omron PLC-Based Water Filling Machine Simulator has demonstrated remarkable success in enhancing teaching and learning activities in industrial automation. …”
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    Book Section
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    PLC-based water filling machine simulator for teaching and learning activities / Kamaru Adzha Kadiran … [et al.] by Kadiran, Kamaru Adzha, Rifin, Rozi, Hussin, Mohamad Zhafran, Mat Saat, Ezril Hisham

    Published 2023
    “…The Omron PLC-Based Water Filling Machine Simulator has demonstrated remarkable success in enhancing teaching and learning activities in industrial automation. …”
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    Book Section
  17. 17

    Artificial intelligence with scratch programming by Toha, Siti Fauziah, Ibrahim, Azhar Mohd, Azmi, Nur Liyana, Abu Hanifah, Rabiatuladawiah, Abdul Malik, Muhammad Hafizi, Mohd Romlay, Muhammad Rabani

    Published 2021
    “…Among the important branches of AI is ‘machine learning’ and further the annotation of ‘deep learning’ intertwined which is the ability of machines that are able to 'learn' to be smart. …”
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    Book
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    Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

    Published 2022
    “…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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    Thesis
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    Building extraction of worldview3 imagery via support vector machine using scikit-learn module / Najihah Ismail by Ismail, Najihah

    Published 2021
    “…Consequently, this study is intending to apply Support Vector Machine (SVM) classification which using Scikit-learn module for building classification. …”
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    Thesis
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    Performance analysis of support vector machine, Gaussian Process Regression, sequential quadratic programming algorithms in modeling hydrogen-rich syngas production from catalyzed... by Ayodele, B.V., Mustapa, S.I., Kanthasamy, R., Mohammad, N., AlTurki, A., Babu, T.S.

    Published 2022
    “…Taking advantage of the data generated from the process, this study explores the performance of twelve machine learning algorithms built on the support vector machine (SVM), the Gaussian process regression (GPR), and the non-linear response quadratic model (NLRQM) using Sequential quadratic programming, and the Levenberg-Marquardt algorithms. …”
    Get full text
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    Article