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  1. 1
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…Even though fuzzy time series (FTS) algorithm is able to overcome moving holiday electricity load demand (MH-ELD) forecasting problem, the current FTS algorithm lacks final model interpretation, is less interpretability of fuzzy logical relationship strength, and does not provide a complete FTS forecasting process. …”
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  2. 2
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…Fuzzy time series (FTS) algorithm is able to overcome moving holiday electricity load demand (MH-ELD) forecasting problem, but the FTS algorithm lacks final model interpretation, less interpretability of fuzzy logical relationship strength, and does not provide a complete FTS forecasting process. …”
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  3. 3
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  4. 4
    Automated time series forecasting

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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  5. 5
    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing

    SecPath: Energy efficient path reconstruction in wireless sensor network using iterative smoothing by Abd, Wamidh Jwdat

    Published 2019
    “…This work uses iterative smoothing algorithm to find an alternative path with less distance and energy consumption. …”
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  6. 6
    Energy efficient path reconstruction in wireless sensor network using iPath

    Energy efficient path reconstruction in wireless sensor network using iPath by Hasan, Sazlinah, Abd, Wamidh Jwdat, Ariffin, Ahmad Alauddin

    Published 2019
    “…This work uses iterative boosting algorithm to find an alternative path with less distance and energy consumption. …”
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  7. 7
    The forecasting of poverty using the ensemble learning classification methods

    The forecasting of poverty using the ensemble learning classification methods by Zamzuri, Muhammad Haziq Adli, Nadilah, Sofian, Hassan, Raini

    Published 2023
    “…This research was conducted to forecast poverty using classification methods. Random Forest and Extreme Gradient Boosting (XGBoost) algorithms were applied to forecast poverty since they are supervised learning algorithms that use the ensemble learning approach for classification. …”
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  8. 8
    Visdom: Smart guide robot for visually impaired people

    Visdom: Smart guide robot for visually impaired people by Lee, Zhen Ting

    Published 2025
    “…Core functionalities such as path planning, autonomous movement, voice feedback, and app-to-robot communication have been thoroughly tested and optimized. …”
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  9. 9
    Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model

    Forecasting time series data using hybrid grey relational artificial neural network and auto regressive integrated moving average model by Salleh, Roselina, Shamsuddin, Siti Mariyam

    Published 2007
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  10. 10
    Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks

    Performance of various forecasting algorithms to reduce the number of transmitted packets by sensor node in wireless sensor networks by Husni, Muhammed Ihsan

    Published 2018
    “…The simulation experiments are done using MATLAB software for a variety of algorithms. The selected algorithms for the reduction algorithm in the transmissions include Move Average algorithm (MA), Autoregressive all-pole model parameters — Burg’s algorithm. …”
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  11. 11
    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…Furthermore, EEC in ASEAN-5 countries is forecasted by autoregressive integrated moving average (ARIMA) model and first-order single-variable grey model (GM (1, 1)) and their forecasts are compared with those obtained by the proposed method.…”
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  12. 12
    A new hybrid genetic algorithm-sarima-artificial neural network in forecasting Malaysian export amount of palm oil

    A new hybrid genetic algorithm-sarima-artificial neural network in forecasting Malaysian export amount of palm oil by Chai, Kah Chun

    Published 2021
    “…Malaysia is a significant export country of palm oil to all over the world. Therefore, forecasting of palm oil export is required to help in boosting the nation’s socioeconomic development as well as for the plantation companies to sustain and improve for a better management regarding export. …”
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  13. 13
    New Approach for E-Commerce Stock Prices Prediction : Combination of Machine Learning and Technical Analysis

    New Approach for E-Commerce Stock Prices Prediction : Combination of Machine Learning and Technical Analysis by Kelvin Lee, Yong Ming, Mohamad, Jais, Pick Soon, Lee

    Published 2022
    “…This study aimed to develop a new approach for forecasting the price movements of e-commerce stocks. …”
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  14. 14
    Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises

    Determining the order of a moving average model of time series using reversible jump MCMC: a comparison between laplacian and gaussian noises by Suparman, Suparman, Abdellah Salhi, Abdellah Salhi, Rusiman, Mohd Saifullah

    Published 2020
    “…Moving average (MA) is a time series model often used for pattern forecasting and recognition. …”
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  15. 15
    Forecasting road deaths in Malaysia using support vector machine

    Forecasting road deaths in Malaysia using support vector machine by Nurul Qastalani, Radzuan, Mohd Hasnun, Arif Hassan, Anwar P.P., Abdul Majeed, Rabiu Muazu, Musa, Khairil Anwar, Abu Kassim

    Published 2020
    “…This study proposes a new approach in forecasting the road deaths, by means of a machine learning algorithm known as Support Vector Machine. …”
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  16. 16
    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting

    Kelantan daily water level prediction model using hybrid deep-learning algorithm for flood forecasting by Loh, Eng Chuen

    Published 2021
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  17. 17
    Application of Evolutionary Algorithm for Assisted History Matching

    Application of Evolutionary Algorithm for Assisted History Matching by Zahari, Muhammad Izzat

    Published 2014
    “…Besides, algorithm based method has been widely used to forecast future result in various field for example art, biology, marketing including engineering. …”
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  18. 18
    Flood forecasting for Melaka using arima and nar modelling methods

    Flood forecasting for Melaka using arima and nar modelling methods by Wong, Wei Ming

    Published 2022
    “…A flash flood is challenging to forecast and requires a sophisticated algorithm and system compared to the seasonal flood. …”
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  19. 19
    Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction

    Artificial neural network model with different backpropagation algorithms and meteorological data for solar radiation prediction by Heng S.Y., Ridwan W.M., Kumar P., Ahmed A.N., Fai C.M., Birima A.H., El-Shafie A.

    Published 2023
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  20. 20
    Load demand analysis for high rise residentals of Petaling Jaya

    Load demand analysis for high rise residentals of Petaling Jaya by Ng, Pik San

    Published 2024
    text::Final Year Project
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