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  1. 1
    Optimal input features selection of wavelet-based EEG signals using GA

    Optimal input features selection of wavelet-based EEG signals using GA by Mohd. Daud, Salwani, Yunus, Jasmy

    Published 2004
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  2. 2
    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments

    A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments by Khaksar, Weria

    Published 2013
    “…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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  3. 3
    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy

    Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy by Ehteram M., Ahmed A.N., Fai C.M., Afan H.A., El-Shafie A.

    Published 2023
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  4. 4
    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA)

    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.…”
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  5. 5
    Reactive approach for automating exploration and exploitation in ant colony optimization

    Reactive approach for automating exploration and exploitation in ant colony optimization by Allwawi, Rafid Sagban Abbood

    Published 2016
    “…Ant colony optimization (ACO) algorithms can be used to solve nondeterministic polynomial hard problems. …”
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  6. 6
    Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network

    Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network by Darajeh, Negisa, Masoumi, Hamid Reza Fard, Kalantari, Katayoon, Ahmad @ Ayob, Mansor, Shameli, Kamyar, Basri, Mahiran, Khandanlou, Roshanak

    Published 2016
    “…In this study, a wavelet neural network (WNN) based on the incremental backpropagation (IBP) algorithm was used in conjunction with an experimental design. …”
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  7. 7
    Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong

    Modified ant colony optimization algorithms for deterministic and stochastic inventory routing problems / Lily Wong by Lily , Wong

    Published 2018
    “…The computational results also show that the algorithms of population based ACO performs better than the algorithms of non-population based ACO. …”
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  8. 8
    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana

    Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

    Published 2018
    “…Anomaly-based Intrusion Detection System (IDS) uses known baseline to detect patterns which have deviated from normal behaviour. …”
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  9. 9
    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending

    Neural Network Model and Finite Element Simulation of Spring back in Plane-Strain Metallic Beam Bending by Abu Khadra, Fayiz Y. M.

    Published 2006
    “…To validate the finite element model physical experiments were conducted. A neural network algorithm based on the backpropagation algorithm has been developed. …”
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  10. 10
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…We develop an active-set based block coordinate descent algorithm (BCD) to optimize exactly the group LASSO. …”
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  11. 11
    An enhanced sequential exception technique for semantic-based text anomaly detection

    An enhanced sequential exception technique for semantic-based text anomaly detection by Taiye, Mohammed Ahmed

    Published 2019
    “…If these challenges are not properly resolved, identifying semantic-based text anomaly will be less accurate. This study proposes an Enhanced Sequential Exception Technique (ESET) to detect semantic-based text anomaly by achieving five objectives: (1) to modify Sequential Exception Technique (SET) in processing unstructured text; (2) to optimize Cosine Similarity for identifying similar and dissimilar text data; (3) to hybridize modified SET with Latent Semantic Analysis (LSA); (4) to integrate Lesk and Selectional Preference algorithms for disambiguating senses and identifying text canonical form; and (5) to represent semantic-based text anomaly using First Order Logic (FOL) and Concept Network Graph (CNG). …”
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  12. 12
    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff

    Metacarpal phantom radiograph edge detection using genetic algorithm gradient based genotype / Norharyati Md Ariff by Md Ariff, Norharyati

    Published 2007
    “…For the image segmentation, genetic algorithm are use to segment the bone image and it is a new method that applies in the image processing field. …”
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  13. 13
    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms

    Multivariate Optimization of Biosynthesis of Triethanolamine-Based Esterquat Cationic Surfactant Using Statistical Algorithms by Fard Masoumi, Hamid Reza

    Published 2011
    “…All process parameters are selected to conduct the optimization by using some statistical algorithms such as Artificial Neural networks (ANNs), Response Surface Methodology (RSM), Wavelet Neural Network (WNN) and Partial Least Squares (PLS). …”
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  14. 14
    Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM

    Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM by Saxena N.K., Gao W.D., Kumar A., Mekhilef S., Gupta V.

    Published 2023
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  15. 15
    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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  16. 16
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  17. 17
    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio

    A multi-objective portfolio selection model with fuzzy Value-at-Risk ratio by Wang, B., Li, Y., Wang, S., Watada, J.

    Published 2018
    “…Then the proposed model is solved by a fuzzy simulation-based multi-objective particle swarm optimization algorithm, where the global best of each iteration is determined by an improved dominance times-based method. …”
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  18. 18
    Crossover and mutation operators of real coded genetic algorithms for global optimization problems

    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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  19. 19
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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  20. 20
    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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