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  1. 1
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The focus of the paper is to propose a hybrid approach for the selection of the most influential input variables for the training and testing of neural network based hybrid models. …”
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  2. 2
    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…The efficacy of these models depends upon many factors such as, neural network architecture, type of training algorithm, input training and testing data set and initial values of synaptic weights. …”
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  3. 3
    Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms

    Power plant energy predictions based on thermal factors using ridge and support vector regressor algorithms by Afzal, Asif, Alshahrani, Saad, Alrobaian, Abdulrahman, Buradi, Abdulrajak, Khan, Sher Afghan

    Published 2021
    “…Initially, the Ridge algorithm-based modeling is performed in detail, and then SVR-based LR, named as SVR (LR), SVR-based radial basis function—SVR (RBF), and SVR-based polynomial regression—SVR (Poly.) algorithms, are applied. …”
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  4. 4
    Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System

    Multidimensional Minimization Training Algorithms for Steam Boiler Drum Level Trip Using Artificial Intelligence Monitoring System by Ismail, F. B., Al-Kayiem, Hussain H.

    Published 2010
    “…The selection of the relevant variables for the neural networks is based on merging between theoretical analysis base and the plant operator experience. …”
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  5. 5
    Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation

    Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation by Hamimu, La

    Published 2011
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  6. 6
    An algorithm for Elliott Waves pattern detection

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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  7. 7
    An algorithm for Elliott Waves pattern detection

    An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2018
    “…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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  8. 8
    A WAVELET BASED SIGNAL DENOISING AND HYDROCARBON PREDICTION ALGORITHM FOR A NEW MARINE CSEM ANTENNA DESIGN

    A WAVELET BASED SIGNAL DENOISING AND HYDROCARBON PREDICTION ALGORITHM FOR A NEW MARINE CSEM ANTENNA DESIGN by NYAMASVISVA, TADIWA ELISHA

    Published 2017
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  9. 9
    Design and implementation of cordic algorithm with sinusoidal pulse width modulation switching strategy

    Design and implementation of cordic algorithm with sinusoidal pulse width modulation switching strategy by Madzzaini, Nur Sofea Eleena

    Published 2017
    “…In addition, CORDIC algorithm has a low usage of memory space compared to Look Up table (LUT) technique. …”
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  10. 10
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…The primary concern is to acquire the clear picture of the implementation of Multi-Objective Genetic Algorithm and the essential of variable valve timing effects on the engine performances in various engine speeds. …”
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    Proceeding Paper
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  11. 11
    Quasi linear algorithm for modelling shoreline change from AIRSAR/POLSAR polarized data

    Quasi linear algorithm for modelling shoreline change from AIRSAR/POLSAR polarized data by Marghany, Maged, Hashim, Mazlan, Cracknell, Arthur P.

    Published 2007
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  12. 12
    Market prices trend forecasting supported by Elliott Wave's theory

    Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

    Published 2017
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  13. 13
    Neural network based model predictive control for a steel pickling process

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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  14. 14
    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network

    Development Of Water Quality Index Prediction Model For Penang Rivers Using Artificial Neural Network by Mohd Hamdan, Eleena Yasmeen

    Published 2021
    “…Prior to the development of ANN-based WQI prediction model, the BR algorithm was chosen with two-, three-, four-, five- and six-neuron architectures for 60% and 70% training. …”
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    Monograph
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  15. 15
    Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models

    Modeling and validation of base pressure for aerodynamic vehicles based on machine learning models by Quadros, Jaimon Dennis, Khan, Sher Afghan, Aabid, Abdul, Baig, Muneer

    Published 2023
    “…Based on the identical dataset, the GA-BP and PSO-BP algorithms are also compared to the PCA-BAS-ENN algorithm. …”
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  16. 16
    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning

    Reinforcement learning-based target tracking for unmanned aerial vehicle with achievement rewarding and multistage traning by Ahmed Abo Mosali, Najm Addin Mohammed

    Published 2022
    “…Third, the concept of multistage training based on the dynamic variables was proposed as an opposing concept to one-stage combinatory training. …”
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  17. 17
    Random traveling wave pulse coupled oscillator (RTWPCO) algorithm of energy-efficient wireless sensor networks

    Random traveling wave pulse coupled oscillator (RTWPCO) algorithm of energy-efficient wireless sensor networks by Al-Mekhlafi, Zeyad Ghaleb Aqlan, Mohd Hanapi, Zurina, Othman, Mohamed, Ahmad Zukarnain, Zuriati, Shamsan Saleh, Ahmed M.

    Published 2018
    “…As a result, it is more suitable and harder to identify demands in all applications. …”
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  18. 18
    The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach

    The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Muhammad Muaz, Alim, Mohamad Razali, Abdullah

    Published 2018
    “…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. SVM models with linear, quadratic, cubic, fine RBF, medium RBF, as well as the coarse RBF kernel functions, were trained based on the measured performance variables. …”
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  19. 19
    Algorithm enhancement for host-based intrusion detection system using discriminant analysis

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

    Published 2004
    “…Misuse detection algorithms model know attack behavior. They compare sensor data to attack patterns learned from the training data. …”
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  20. 20
    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA

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

    Published 2012
    “…The research work also investigates several recursive algorithms including recursive Kalman filter (RKF) and extended Kalman filter (EKF) using extreme learning machine (ELM) and hybrid linear/nonlinear training technique by incorporating the fiee derivative concept. …”
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