Search Results - (( variable training learning algorithm ) OR ( data optimization method algorithm ))

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  1. 1

    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
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    Machine Learning Based Optimal Design of On-Road Charging Lane for Smart Cities Applications by Shanmugam Y., Narayanamoorthi R., Ramachandaramurthy V.K., Bernat P., Shrestha N., Son J., Williamson S.S.

    Published 2025
    “…The algorithm not only aids in estimating the infrastructure cost of the charging lane but also predicts optimal design parameters using trained data. …”
    Article
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    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
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    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…The application of FES optimized by GA on regionalization creates opportunities for further researches which utilizes different types of optimization like Ant Colony Optimization (ACO), ANN’s, Particle Swarm Optimization (PSO) and Imperialist Competitive Algorithm (ICA).…”
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    Thesis
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    Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

    Published 2012
    “…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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    Hypertension Prediction in Adolescents Using Anthropometric Measurements: Do Machine Learning Models Perform Equally Well? by Chai, Soo See, Goh, Kok Luong, Cheah, Whye Lian, Chang, Robin Yee Hui, Ng, Giap Weng

    Published 2022
    “…However, different machine learning algorithms were utilized in conjunction with various anthropometric data, either alone or in combination with other biophysical and lifestyle variables. …”
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    Article
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    Rank-based optimal neural network architecture for dissolved oxygen prediction in a 200L bioreactor by Mamat, Nor Hana, Mohd Noor, Samsul Bahari, Che Soh, Azura, Taip, Farah Saleena, Ab Rashid, Ahmad Hazri, Jufika Ahmad, Nur Liyana, Mohd Yusuff, Ishak

    Published 2017
    “…The ranks are applied together for both training and testing datasets. The backpropagation neural network model with Lavenberg Marquardt learning algorithm was developed using 1476 samples real process dataset obtained from a fermentation process in a 200L bioreactor. …”
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  9. 9

    Hypertension prediction in adolescents using anthropometric measurements: Do machine learning models perform equally well? by Chai, Soo See, Goh, Kok Luong, Cheah, Whye Lian, Chang, Yee Hui Robin, Ng, Giap Weng

    Published 2022
    “…However, different machine learning algorithms were utilized in conjunction with various anthropometric data, either alone or in combination with other biophysical and lifestyle variables. …”
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    Article
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    Optimization of Lipase Catalysed Synthesis of Sugar Alcohol Esters Using Taguchi Method and Neural Network Analysis by Adnani, Seyedeh Atena

    Published 2011
    “…In this system,similar insolvent system, three methods including one variable at a time, Taguchi method and ANN were used for optimization and prediction of percentage of conversion. …”
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    Thesis
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    Multivariate Based Analysis of Methane Adsorption Correlated to Toc and Mineralogy Impact from Different Shale Fabrics by Irfan, S.A., Azli, N.M., Abdulkareem, F.A., Padmanabhan, E.

    Published 2021
    “…The machine learning based SVR method is incorporated for its ability to handle the regression model for linear and nonlinear input data based on mathematical formulation called kernels. …”
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    Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption by Zamani, Seyed Ali

    Published 2015
    “…The input and output of the RSM design was used in artificial neural networks for training purpose. The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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    Improvement of an integrated global positioning system and inertial navigation system for land navigation application by Hasan, Ahmed Mudheher

    Published 2012
    “…This work also presents a new method for de-noising the GPS and INS data and estimate the INS error using wavelet multi-resolution analysis algorithm (WMRA) based particle swarm optimization (PSO) with a well designed structure appropriate for practical and real time implementations due to its very short optimizing time and elevated accuracy. …”
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    Thesis
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    SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

    Published 2012
    “…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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    Thesis
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    Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

    Published 2025
    “…The random forest algorithm was able to achieve 99.8% accuracy and 99.9% sensitivity in the training dataset. …”
    Article
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