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Box-jenkins and genetic algorithm hybrid model for electricity forecasting system
Published 2005“…The investigation is simulated using Intelligent Electricity Forecasting System (IEFS) developed in this research which written in Borland Delphi 7.0 programming.…”
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Thesis -
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms
Published 2024“…We created a machinelearning- based solution for the wellness program industry that uses Internet Of Medical Things (IoMT) devices to forecast cardiovascular risk. …”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem
Published 2023Conference Paper -
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…There are various techniques for identifying and observing the stock market patterns, one of the techniques is to use Python programming to evaluate and possibly forecast stock market behaviour through predictive modelling, combining both machine learning and Econophysics insights. …”
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Book Section -
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Evaluation of the accuracy of soft computing learning algorithms in performance prediction of tidal turbine
Published 2021“…This study shows that the application of the new procedure resulted in confident generality performance and learns faster than orthodox learning algorithms. In conclusion, the assessment indicated that the advanced Extreme Learning Machine simulation was capable as a promising alternative to existing numerical methods for computing the coefficient of performance for turbines. …”
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Forecast of Muslimah fashion trends in Caca's company / Muhammad Saifullah Mohd Taip
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Student Project -
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A novel hybrid evolutionary mating algorithm for Covid19 confirmed cases prediction based on vaccination
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Examining the potential of machine learning for predicting academic achievement: A systematic review
Published 2023“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Examining the potential of machine learning for predicting academic achievement: A systematic review
Published 2023“…Predicting student academic performance is a critical area of education research. Machine learning (ML) algorithms have gained significant popularity in recent years. …”
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Improved voting technique for ensemble of MLP system applied on various classification data / Saodah Omar, Iza Sazanita Isa and Junita Mohd Saleh.
Published 2010“…The MLP networks are trained using two types of learning algorithm, which are the Levenberg Marquardt and the Resilient Back Propagation algorithms. …”
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Research Reports -
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Artificial Intelligence (AI) to predict dental student academic performance based on pre-university results
Published 2022“…Methods: Various Machine Learning (ML) algorithms were applied using academic result samples of graduates of the Kulliyyah of Dentistry, IIUM from 2012-2017. …”
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Proceeding Paper -
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…The dataset of 297 instances comprised attributes such as Course Code, Course Name, Course Type, Faculty, Program, Campus, Total Number of Students Enrolled and Approval Status. …”
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Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education
Published 2025journal-article
