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  1. 1

    Pure intelligent monitoring system for steam economizer trips by Basim Ismail F., Hamzah Abed K., Singh D., Shakir Nasif M.

    Published 2023
    “…Economizers; Failure (mechanical); Fault detection; Knowledge acquisition; Learning algorithms; Learning systems; Neural networks; Plant shutdowns; Steam; Thermoelectric power plants; Extreme learning machine; Fault detection and diagnosis systems; Intelligent modeling; Intelligent monitoring systems; Network methodologies; Operational conditions; Operational variables; Thermal power plants; Steam power plants…”
    Conference Paper
  2. 2

    Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

    Published 2003
    “…Voltage stability problems have been one of the major concerns for electric utilities as a result of a system heavy loading. This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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    Thesis
  3. 3

    One day ahead daily peak hour load forecasting by using invasive weed optimization learning algorithm based Artificial Neural Network by Rahim, Muhammad Fitri

    Published 2012
    “…Hence, this indicates that Invasive Weed Optimization could be implemented as a new learning algorithm for an Artificial Neural Network.…”
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    Student Project
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    Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

    Published 2007
    “…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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    Thesis
  6. 6

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

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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    Thesis
  7. 7

    Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data by Ong, Song Quan, Pradeep Isawasan, Ahmad Mohiddin Mohd Ngesom, Hanipah Shahar, As’malia Md Lasim, Gomesh Nair

    Published 2023
    “…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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    Article
  8. 8

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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    Thesis
  9. 9

    Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

    Published 2022
    “…Here, the memory consumption can be reduced by enabling a feature selection algorithm that excludes nonrelevant features and preserves the relevant ones. the algorithm is developed based on the variable length of the PSO. …”
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    Thesis
  10. 10

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    “…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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    Article
  11. 11

    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 ML approach, which predicts optimal design parameters with a trained dataset, is more efficient with reduced duration than conventional finite element analysis (FEA) tools and stochastic methods. The learning algorithms consider variables such as core structure, cross-coupling effect, and coil flux pipe length. …”
    Article
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    A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

    Published 2005
    “…The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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    Monograph
  14. 14

    Synchronizing Artificial Intelligence Models for Operating the Dam and Reservoir System by Allawi, Mohammed Falah, Jaafar, Othman, Ehteram, Mohammad, Mohamad Hamzah, Firdaus, El-Shafie, Ahmed

    Published 2018
    “…It is demonstrated that shark machine learning algorithm would be a promising tool in handling the long-term optimization problem in operation a reservoir system.…”
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    Article
  15. 15

    Pure intelligent monitoring system for steam economizer trips by Basim Ismail, F., Hamzah Abed, K., Singh, D., Shakir Nasif, M.

    Published 2017
    “…However, these methodologies are hard to be achieved due to certain boundaries such as system learning ability and the weakness of the system beyond its domain of expertise. …”
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    Article
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    MCMAC–CVT: a novel on-line associative memory based CVT transmission control system by Kai, Keng Ang, Quek, Chai, Abdul Rahman, Abdul Wahab

    Published 2002
    “…Engng, 10 (1996) 135) with momentum, neighborhood learning and Averaged Trapezoidal Output (MCMAC-ATO) as the neural control algorithm for controlling the CVT. …”
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    Article
  18. 18

    Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions by Shamshad, H., Ullah, F., Ullah, A., Kebande, V.R., Ullah, S., Al-Dhaqm, A.

    Published 2023
    “…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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    Article
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    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…To address these problems, this paper introduces a novel hybrid approach for RUL prediction, combining a Lightning Search Algorithm (LSA) with a Long-Short Term Memory (LSTM) deep learning model. …”
    Article