Search Results - (( intelligence based means algorithm ) OR ( intelligence based training algorithm ))

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    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
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    Thesis
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    Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone by Md Jamal, Norezmi

    Published 2022
    “…Moreover, the task of removing noises without causing speech distortion is also challenging, in which the quality and intelligibility of speech are affected. In order to overcome these issues, a supervised Deep Neural Network (DNN) algorithm predicted constrained Wiener Filter (cWF) target mask algorithm based on extracted Gammatone filter bank power spectrum (GF-TF) features and trained model is developed. …”
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    Thesis
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    Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

    Published 2022
    “…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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    Thesis
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    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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    Article
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    Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

    Published 2015
    “…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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    Thesis
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    Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

    Published 2022
    “…Therefore, a fully artificial intelligent (AI)-integrated sun-tracking algorithm is proposed and can be used in any type of sun-tracking systems such as concentrated photovoltaic (CPV), flat photovoltaic (PV) or heliostat systems. …”
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    Final Year Project / Dissertation / Thesis
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    Intelligent technique for grading tropical fruit using magnetic resonance imaging by A. Balogun, Wasiu, Salami, Momoh Jimoh Emiyoka, J. McCarthy, Michael, Mohd Mustafah, Yasir, Aibinu, Abiodun Musa

    Published 2013
    “…Levenberg-Marquardt algorithm (trainlm) gave the best performance fitness out of different types of backpropagation algorithm used with least Mean Square Error (MSE) of 0.0814 corresponding to R-value of 0.8094. …”
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    Article
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    Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

    Published 2006
    “…Multilayer Perceptron (MLP) network and Radial Basis Function (RBF) network will be developed using MATLAB in which MLP network is trained with Back Propagation, Bayesian Rule and Levenberg-Marquardt learning algorithm and RBF network is trained with k-means clustering algorithm. …”
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    Monograph
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    A layer-sensitivity based artificial neural network for characterization of oil palm fruitlets by Adedayo, Ojo O., Onibonoje, Moses, Isa, Maryam

    Published 2021
    “…To further investigate the generalization ability of the trained neural network, three other neural network training algorithms were deployed for the same dataset. …”
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    Article
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    Development of an accurate AI-based dermatology assistant for skin disease recognition using YOLOv8 models by Huzaini, Muhammad Irfan Darwish, Mansor, Hasmah, Gunawan, Teddy Surya, Ahmad, Izanoordina

    Published 2024
    “…After 500 training epochs, the YOLOv8 Small Model was the most accurate, achieving a precision of 84%, a recall of 77.1%, and a mean average precision (mAP) of 84%. …”
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    Proceeding Paper
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    A least-square-driven functional networks type-2 fuzzy logic hybrid model for efficient petroleum reservoir properties prediction by Fatai Adesina, Anifowose, Jane, Labadin, Abdulazeez, Abdulraheem

    Published 2013
    “…This paper presents a computational intelligence hybrid model to overcome some of the limitations of the standalone type-2 fuzzy logic system (T2FLS) model by using a least-square-fitting-based model selection algorithm to reduce the dimensionality of the input data while selecting the best variables. …”
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    Article
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    Integrated geophysical, hydrogeochemical and artificial intelligence techniques for groundwater study in the Langat Basin, Malaysia / Mahmoud Khaki by Mahmoud, Khaki

    Published 2014
    “…These results confirm that, for all the networks the Levenberg-Marquardt algorithm is the most effective algorithm to model the groundwater level. …”
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    Thesis
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    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
    “…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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    Thesis
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    Modelling and Control of Ankle Foot Orthosis (AFO) for Children Utilising Soft Computing Towards Intelligent Approach by Aida Suriana, Abdul Razak

    Published 2024
    “…In controllers’ development, the research employed both conventional and intelligent Proportional–Integral–Derivative (PID) based controllers. …”
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    Thesis