Search Results - (( normal distribution bat algorithm ) OR ( parameters variation bayes algorithm ))

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  1. 1

    Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging by Panahi F., Ehteram M., Ahmed A.N., Huang Y.F., Mosavi A., El-Shafie A.

    Published 2023
    “…Climate models; Flood control; Floods; Forecasting; Information management; Inverse problems; Mean square error; Multilayer neural networks; Multilayers; Normal distribution; Particle swarm optimization (PSO); Reservoir management; Reservoirs (water); Risk management; Rivers; Stream flow; Uncertainty analysis; Bat algorithms; Bayesian model averaging; Bayesian modelling; Copula bayesian model; Gamma test; Inclusive multiple model; Multilayers perceptrons; Multiple-modeling; Natural hazard; Optimization algorithms; Bayesian networks; flood; flood control; North Atlantic Oscillation; perception; reservoir; streamflow; uncertainty analysis; Kelantan; Malaysia; West Malaysia…”
    Article
  2. 2

    Characterisation of pineapple cultivars under different storage conditions using infrared thermal imaging coupled with machine learning algorithms by Mohd Ali, Maimunah, Hashim, Norhashila, Abd Aziz, Samsuzana, Lasekan, Ola

    Published 2022
    “…A total of 14 features from the thermal images were obtained to determine the variation in terms of image parameters among the different pineapple cultivars. …”
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  3. 3

    Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

    Published 2020
    “…Other system parameter variations are 4 different fault resistances (0.001 Ω, 10 Ω, 50 Ω, 100 Ω), and two inception angles (0 oC and 30 oC). …”
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  4. 4

    Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images by Farzan, Ali

    Published 2015
    “…A minimal set of feature who passed the above criteria and can differentiate all of cognitive score pairs is selected by using a genetic search algorithm. Chernoff bound as upper bound of Bayes error for class separability is computed for evaluating the feature selection method. …”
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    Thesis