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  1. 1
    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control

    Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control by Mohd Hanafi, Muhammad Sidik

    Published 2020
    “…This method would be a control method to activate power assist system and selected based on conditions set in the algorithm. …”
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  2. 2
    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk

    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

    Published 2019
    “…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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  3. 3
    Development of a rule-based fault diagnostic advisory system for precut fractionation column

    Development of a rule-based fault diagnostic advisory system for precut fractionation column by Heng, Han Yann

    Published 2005
    “…The advisory system algorithm used process history based method and presented by rule-based approach. …”
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  4. 4
    On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay

    On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay by Aneesha Pillay , Balachandran Pillay

    Published 2024
    “…This study proposes using recursive feature elimination (RFE) method to reduce data dimensionality and select the most important attributes based on predictor importance ranking. …”
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  5. 5
    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm

    Data driven neuroendocrine pid controller for mimo plants based adaptive safe experimentation dynamics algorithm by Mohd Riduwan, Ghazali

    Published 2020
    “…Data-driven tools are an optimization method to find the optimal controller parameters using the system’s input and output data. …”
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  6. 6
    Development of dynamic programming algorithm for maintenance scheduling problem

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…This model was then simulated using the data collected to verify whether the model was operating effectively and can be used to achieve the objective of this research. …”
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  7. 7
    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques

    Intrusion Detection in Mobile Ad Hoc Networks Using Transductive Machine Learning Techniques by Farhan, Farhan Abdel-Fattah Ahmad

    Published 2011
    “…In machine learning algorithm, choosing the most relevant features for each attack is a very important requirement, especially in mobile ad hoc networks where the network topology dynamically changes. …”
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  8. 8
    Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki

    Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki by Mahmoud, Khaki

    Published 2014
    “…Ninety eight geoelectrical resistivity survey measurements were conducted to obtain subsurface resistivity data. The Wenner array was selected because of its sensitivity in detecting vertical changes in subsurface resistivity. …”
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  9. 9
    SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid

    SWAT and ANN model hydrological assessment using Malaysia soil data / Khairi Khalid by Khalid, Khairi

    Published 2017
    “…Both models produced good results in predicting streamflow, and the existing AWC soil data in the ANN model did not significantly change the value of the simulation output. …”
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  10. 10
    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models

    Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

    Published 2019
    “…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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  11. 11
    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches

    Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

    Published 2018
    “…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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  12. 12
    Neural network based adaptive pid controller for shell-and-tube heat exchanger

    Neural network based adaptive pid controller for shell-and-tube heat exchanger by Othman, Mohamad Hakimi

    Published 2019
    “…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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  13. 13
    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article

    Neural network based adaptive pid controller for shell-and-tube heat exchanger: article by Othman, Mohamad Hakimi

    Published 2019
    “…Dynamic time series neural network model was used together with Levenberg-Marquardt algorithm as the training method. Single hidden layer feed forward neural networks with 20 neurons in hidden layer was selected. …”
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  14. 14
    Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques

    Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques by Googhari, Shahram Karimi

    Published 2007
    “…Simulation results for the independent testing data series showed that the model can perform well in simulating peak flows as well as base flows. …”
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  15. 15
    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy

    Development of an artificial neural network algorithm for predicting the cutting force in end milling of Inconel 718 alloy by Hossain, Ishtiaq, Amin, A. K. M. Nurul, Patwari, Muhammed Anayet Ullah

    Published 2011
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  16. 16
    A new history matching sensitivity analysis framework with random forests and Plackett-Burman design

    A new history matching sensitivity analysis framework with random forests and Plackett-Burman design by Aulia, A., Jeong, D., Mohd Saaid, I., Shuker, M.T., El-Khatib, N.A.

    Published 2017
    “…The one-parameterat- a-time method requires 21 samples, and the selected top 4 parameters from this method are mainly fault transmissibilities. …”
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  17. 17
    Incremental learning for large-scale stream data and its application to cybersecurity

    Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

    Published 2015
    “…Whereas, the hash value of RBF bases that is identical with the hash value of the training data is used to select the RBF bases that is near to the training data. …”
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  18. 18
    CONTEXT AWARE TRAFFIC SCHEDULING ALGORITHM FOR COMMUNICATION SYSTEM IN POWER DISTRIBUTION NETWORK

    CONTEXT AWARE TRAFFIC SCHEDULING ALGORITHM FOR COMMUNICATION SYSTEM IN POWER DISTRIBUTION NETWORK by NURSHAZLINA SUHAIMY

    Published 2023
    “…In order to verify the advantages of the proposed algorithm, it is compared with simulation results without contextual aware algorithm. …”
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  19. 19
    Multiple equations model selection algorithm with iterative estimation method

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…Meanwhile, real data analysis using water quality index displays excellent accomplishments when compared to other selection procedures.Consequently, iterative feasible generalized least squares method is regarded as a more suitable estimation method in this automated selection.It can also be seen that simultaneous selections outperform the individual selections.This strategy by executing simultaneous selection with iterative estimation method is therefore proven to outclass in this analysis.…”
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  20. 20
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…Some of the features may contain irrelevant information caused by data redundancy or by noise. A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
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