Search Results - feed-forward ((prediction algorithm) OR (((selection algorithm) OR (detection algorithm))))

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  1. 1
    Early detection of dengue disease using extreme learning machine

    Early detection of dengue disease using extreme learning machine by Suhaeri, Suhaeri, Mohd Nawi, Nazri, Fathurahman, Muhamad

    Published 2018
    “…Therefore, the proposed ELM model can be considered as an alternative algorithm to apply for early detection of Dengue disease.…”
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  2. 2
    A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction

    A Hybrid Neural Network-Based Improved PSO Algorithm for Gas Turbine Emissions Prediction by Yousif S.T., Ismail F.B., Al-Bazi A.

    Published 2025
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  3. 3
    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column

    Process fault detection and diagnosis using Boolean representation on fatty acid fractionation column by Othman, M. R., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

    Published 2003
    “…Through the proposed algorithm, various faults could be simulated and detected using the system. …”
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  4. 4
    Nonlinear response prediction of spar platform using artificial neural network / Md. Alhaz Uddin

    Nonlinear response prediction of spar platform using artificial neural network / Md. Alhaz Uddin by Md. Alhaz , Uddin

    Published 2012
    “…Environmental forces and structural parameters are used as inputs and FEM-based time history of spar platform responses are used as targets. Feed-forward neural networks with back-propagation algorithm are used to train the network. …”
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  5. 5
    Skin Hydration And Transepidermal Water Loss Measurement Using Vis/nir Spectroscopy And Feed-forward Backpropagation Neural Network

    Skin Hydration And Transepidermal Water Loss Measurement Using Vis/nir Spectroscopy And Feed-forward Backpropagation Neural Network by Tan, Chun Ho

    Published 2022
    “…Thus, this study proposed the use of visible/near-infrared (VIS/NIR) spectroscopy, specifically at wavelengths 698 nm, 970 nm, 1200 nm, 1450 nm, and 1950 nm to predict the skin hydration and TEWL. In this study, the prediction models were built using simple linear regression, multiple regression analysis, and feed-forward backpropagation neural network (FFBPNN) with gradient descent algorithm. …”
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  6. 6
    An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance

    An enhanced feed-forward neural networks and a rule-based algorithm for predictive modelling of students' academic performance by Raheem, Ajiboye Adeleke

    Published 2016
    “…Feed-forward Neural Networks, is a multilayer perceptron and a network structure capable of modelling the class prediction as a nonlinear combination of the inputs. …”
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  7. 7
    Wind power prediction using Artificial Neural Network: article

    Wind power prediction using Artificial Neural Network: article by Edik, Septony

    Published 2010
    “…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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  8. 8
    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah

    A preliminary study on automated freshwater algae recognition and classification system / Hayat Mansoor Abdullah by Mansoor Abdullah, Hayat

    Published 2012
    “…Then, Image segmentation applied by using canny edge detection algorithm with specific morphological operation to isolate the image objects components. …”
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  9. 9
    Intelligent technique for grading tropical fruit using magnetic resonance imaging

    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
    “…The features extracted from Magnetic Resonance Imaging (MRI), using any of the two proposed methods, were applied as an input to train artificial neural network (ANN) in order to predict the orange fruit status. Different structures of multi-layer perceptron neural networks with feed-forward and back-propagation learning algorithms were developed using MATLAB. …”
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  10. 10
    Wind power prediction using Artificial Neural Network

    Wind power prediction using Artificial Neural Network by Edik, Septony

    Published 2010
    “…In order to get an accurate wind power prediction, several network structures, training algorithms and transfer functions have been developed and tested with different sets of data. …”
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  11. 11
    Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli

    Development of artificial neural network models for predicting lipid profile using smartMF electrical parameters / Ahmad Zulkhairi Zulkefli by Ahmad Zulkhairi , Zulkefli

    Published 2021
    “…For TG, the LM algorithm with a testing accuracy of 76.7%, sensitivity of 28.6% and specificity of 91.3% was selected. …”
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  12. 12
    Automatic recognition of freshwater algae (Oscillatoria sp.) using image processing techniques with artificial neural network approach / Awatef Saad Salem Saad

    Automatic recognition of freshwater algae (Oscillatoria sp.) using image processing techniques with artificial neural network approach / Awatef Saad Salem Saad by Salem Saad, Awatef Saad

    Published 2012
    “…Computer-based image analysis and pattern recognition methods were used to construct a system that is able to identify, and classify selected Cyanobacteria genus automatically. An image analysis algorithm was implemented to contrast, filter, isolate and recognize objects from microscope images. …”
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  13. 13
    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In this research work, a modified backpropagation neural network is combined with a modified chaos-search genetic algorithm for STLF of one day and a week ahead. Multiple modifications are carried out on the conventional back-propagation (BP) algorithm such as, improvements in the momentum factor and adaptive learning rate. …”
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  14. 14
    Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N. H. Idris ...[et al.]

    Prediction of cascading collapse occurrence due to the effect of hidden failure protection system using different training algorithms feed-forward neural network / N.... by Idris, N. H., Salim, N. A., Othman, M. M., Yasin, Z. M.

    Published 2017
    “…The historical data obtained from NERC report is analyzed and being used in ANN for prediction purposed. This paper compares the supervised training algorithms of feed-forward neural network with backpropagation include Lavenberg- Marquadt (LM), Scale Conjugate Gradient (SCG) and Quasi Newton Backpropagation (BFG). …”
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  15. 15
    Predicting remaining useful life of rotating machinery based artificial neural network

    Predicting remaining useful life of rotating machinery based artificial neural network by Mahamad, Abd Kadir, Saon, Sharifah, Hiyama, Takashi

    Published 2010
    “…The ANN RUL prediction uses FeedForward Neural Network (FFNN) with Levenberg Marquardt of training algorithm. …”
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  16. 16
    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM

    PROPOSED METHODOLOGY FOR OPTIMIZING THE TRAINING PARAMETERS OF A MULTILAYER FEED-FORWARD ARTIFICIAL NEURAL NETWORKS USING A GENETIC ALGORITHM by ABDALLA, OSMAN AHMED

    Published 2011
    “…ANN can be categorized into three main types: single layer, recurrent network and multilayer feed-forward network. In multilayer feed-forward ANN, the actual performance is highly dependent on the selection of architecture and training parameters. …”
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  17. 17
    Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network

    Botnet Detection Using a Feed-Forward Backpropagation Artificial Neural Network by Ahmed, Abdulghani Ali

    Published 2019
    “…The current work proposes a technique to detect Botnet attacks using a feed-forward backpropagation artificial neural network. …”
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  18. 18
    Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data

    Using an Enhanced Feed-Forward BP Network for Predictive Model Building From Students’ Data by Ajiboye, Adeleke Raheem, Ruzaini, Abdullah Arshah, Qin, Hongwu

    Published 2015
    “…Feed-forward, Back Propagation (BP) Network is a network structure capable of modeling the class prediction as a nonlinear combination of the inputs. …”
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  19. 19
    Development of generalized feed forward network for predicting annual flood (depth) of a tropical river

    Development of generalized feed forward network for predicting annual flood (depth) of a tropical river by Salarpour, Mohsen, Zulkifli Yusop, Jajarmizadeh, Milad, Fadhilah Yusof

    Published 2014
    “…This study aimed at developing a Generalized Feed Forward (GFF) network model for predicting annual flood (depth) of Johor River in Peninsular Malaysia. …”
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  20. 20
    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network

    Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network by Sefidgar, Seyed Mohammad Hossein

    Published 2014
    “…First, the best set of structures for feed forward neural network were found by multi objective parallel genetic algorithm. …”
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