Search Results - (( parameter estimation using algorithm ) OR ( learning classification using algorithm ))

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  1. 1

    Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

    Published 2021
    “…Therefore, this study aimed to used OBIA method with selected machine learning algorithm to estimate the mangrove age by using Sentinel 2A image. …”
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    Thesis
  2. 2

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…The multi-class classification strategy is used to ensure quick estimation of the multi-class NN algorithms. …”
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  3. 3

    Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

    Published 2023
    “…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
    Conference Paper
  4. 4

    Extremal region selection for MSER detection in food recognition by Razali, Mohd Norhisham, Manshor, Noridayu, Abdul Halin, Alfian, Mustapha, Norwati, Yaakob, Razali

    Published 2021
    “…UECFOOD-100 and UNICT-FD1200 are the two food datasets used to benchmark the proposed algorithm. The results of this research have found that the ERS algorithm by using optimum parameters and thresholds, be able to reduce the number of extremal regions with sustained classification performance.…”
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    Article
  5. 5

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…In addition, the hyperparameter tuning problem is considered in this research to improve the developed hybrid model by using the AOA algorithm. Lastly, a new hybrid technique suggests tackling the current image encryption application problem by using the estimated parameters of chaotic systems with an optimization algorithm, the SKF algorithm. …”
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  6. 6
  7. 7

    Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

    Published 2018
    “…Furthermore, researchers have mainly used metaheuristic algorithms to avoid the problem of local minima in standard learning method. …”
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  8. 8

    Extremal Region Selection for MSER Detection in Food Recognition by Mohd Norhisham Razali @ Ghazali, Noridayu Manshor, Alfian Abdul Halin, Norwati Mustapha, Razali Yaakob

    Published 2021
    “…UECFOOD-100 and UNICT-FD1200 are the two food datasets used to benchmark the proposed algorithm. The results of this research have found that the ERS algorithm by using optimum parameters and thresholds, be able to reduce the number of extremal regions with sustained classification performance.…”
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    Article
  9. 9

    A new LoRa based positioning algorithm utilizing sequence based deep learning technique by Suseenthiran, Kavetha

    Published 2023
    “…Furthermore, an analysis of classification using different sequence length is done. Then, a new positioning algorithm is developed which incorporates distance estimation, Kalman Filter and trilateration technique according to the classification with different sequence length data and the positioning error is being analysed. …”
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  10. 10

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  11. 11

    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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  12. 12

    Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

    Published 2012
    “…There is no existing tool to assist faculties in estimating the number of students that can achieve the objective, hence a prediction model using Backpropagation Algorithm is proposed by using a case study of UiTM Bandaraya Melaka Bachelor of Administrative Science students. …”
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    Research Reports
  13. 13

    Information Theoretic-based Feature Selection for Machine Learning by Muhammad Aliyu, Sulaiman

    Published 2018
    “…Three major factors that determine the performance of a machine learning are the choice of a representative set of features, choosing a suitable machine learning algorithm and the right selection of the training parameters for a specified machine learning algorithm. …”
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  14. 14

    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
    “…These parameters are used to develop a standalone intelligently machine learning adaptive distance relay (ML-ADR) modification. …”
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  15. 15

    Evaluating Adan vs. Adam: an analysis of optimizer performance in deep learning by Ismail, Amelia Ritahani, Azhary, Muhammad Zulhazmi Rafiqi, Hitam, Nor Azizah

    Published 2025
    “…Adaptive Moment Estimation (Adam) and Adaptive Nesterov Accelerated Gradi- ent (Adan), two well-known optimizers, are widely used in deep learning for their ability to handle large-scale data and complex models efficiently. …”
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    Proceeding Paper
  16. 16

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…General linear model (GLM) is used to find the unknown parameters of every individual voxel and the classification is done using multi-class support vector machine (SVM). …”
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    Article
  17. 17

    Development of predictive modeling and deep learning classification of taxi trip tolls by Al-Shoukry, Suhad, M. Jawad, Bushra Jaber, Zalili, Musa, Sabry, Ahmad H.

    Published 2022
    “…Commercial navigation includes a wealth of trip-related data, including distance, expected journey time, and tolls that may be encountered along the way. Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
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    Article
  18. 18

    Classification of heart sound signals for the detection of heart diseases / N. Shamsuddin and M. N. Taib by Shamsuddin, N., Taib, M. N.

    Published 2012
    “…The obtained frequency pattern features were fed to the FFNN and trained using Resilient Backpropagation (RPROP) algorithm. …”
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    Article
  19. 19

    DEVELOPMENT OF PREDICTIVE MODELING AND DEEP LEARNING CLASSIFICATION OF TAXI TRIP TOLLS by Al-Shoukry S., Jawad B.J.M., Musa Z., Sabry A.H.

    Published 2023
    “…Commercial navigation includes a wealth of trip-related data, including distance, expected journey time, and tolls that may be encountered along the way. Using a classification algorithm, it is possible to extract drop-off and pickup locations from taxi trip data and estimate if the tour would incur tolls. …”
    Article
  20. 20

    Development of a modified adaptive protection scheme using machine learning technique for fault classification in renewable energy penetrated transmission line by Olufemi, Osaji Emmanuel

    Published 2020
    “…The hybrid Wavelet Multiresolution Analysis and Machine learning algorithm (WMRA-ML) is used to extracts the useful hidden knowledge from decomposed one-cycle fault transient signals (voltage & current) from four Matlab/Simulink CIGRE models. …”
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