Search Results - (( parameter detection path algorithm ) OR ( variable extracting learning algorithm ))

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    Path Planning and Control of Mobile Robot in Road Environments using Sensor Fusion and Active Force Control by Ali, Mohammed A. H., Mailah, Musa

    Published 2018
    “…The sensor fusion algorithm is used to remove noises and uncertainties from sensors' data and provide optimum measurements for path planning. …”
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    Article
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    Surface defect detection and polishing parameter optimization using image processing for G3141 cold rolled steel by Zamri, Ruzaidi

    Published 2016
    “…To realize this, automatic cropping algorithm is developed to detect the region of interest and interpret the Ga value. …”
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    Thesis
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    Detection of black hole nodes in mobile ad hoc network using hybrid trustworthiness and energy consumption techniques by Mustafa, Ahmed Sudad

    Published 2017
    “…In this thesis, a hybrid detection algorithm mechanism has been proposed which combines two detection algorithms based on nodes’ trustworthiness and energy consumption in a parallel manner in order to detect the black hole nodes. …”
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    Thesis
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    Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad by Ahmad, Khairul Adilah

    Published 2018
    “…Due to the inherent and uncertain variability of the Harumanis features, fuzzy learning algorithm has been designed to classify these fruits similar to the ability of human experts. …”
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    Thesis
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    A novel bio-inspired routing algorithm based on ACO for WSNs by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

    Published 2019
    “…The issue of path selection to reach the nodes and vital correspondence parameters, for example, the versatility of nodes, their constrained vitality, the node residual energy and route length are considered since the communications parameters and imperatives must be taken into account by the imperative systems that mediate in the correspondence procedure, and the focal points of the subterranean insect framework have been utilized furthermore. …”
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    Article
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    Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

    Published 2024
    “…If the feature extraction process fails to capture the correct information, the performance or accuracy of the classification algorithm will be negatively impacted. …”
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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
    “…However, existing RUL prediction approaches have difficulties with variability and nonlinearity that occur during battery degradation, data extraction, feature extraction, hyperparameters optimization, and prediction model uncertainty. …”
    Article
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    Mobile robot safe navigation in unknown environment by Shayestegan, Mohsen, Marhaban, Mohammad Hamiruce

    Published 2012
    “…The information about the target and the low-range sensory information are used by the controller to produce the commands that gives a favorable direction in terms of reaching to the target within the collision detection. Furthermore, the mobile robot does not suffer from typical ushape environment by a planned local minimum trapping algorithm and also designed controller is easy to understand, simple, and not sensitive to the system model parameters. …”
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    Conference or Workshop Item
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    Effect of LiDAR mounting parameters and speed on HDL graph SLAM-Based 3D mapping for autonomous vehicles by Law, Jia Seng, Muhammad Aizzat, Zakaria, Younus, Maryam, Yong, Ericsson, Ismayuzri, Ishak, Mohamad Heerwan, Peeie, Muhammad Izhar, Ishak

    Published 2025
    “…Results showed that a 0° angle at 30 km/h produced the most accurate 3D map, achieving a Root Mean Square Error (RMSE) of 0.0812 for straight paths and 0.1345 for curved paths. These findings demonstrate the significance of physical mounting parameters and speed on mapping performance. …”
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    Article
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    Classification of Students' Performance in Computer Programming Course According to Learning Style by Norwawi, NM, Abdusalam, SF, Hibadullah, CF, Shuaibu, BM

    Published 2024
    “…The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. …”
    Proceedings Paper
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    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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    Article
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    Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

    Published 2004
    “…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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    Thesis
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    Mortality prediction in critically ill patients using machine learning score by Dzaharudin, Fatimah, Md Ralib, Azrina, Jamaludin, Ummu Kulthum, Mat Nor, Mohd Basri, Tumian, Afidalina, Har, Lim Chiew, Ceng, T C

    Published 2020
    “…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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    Proceeding Paper
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    Mortality prediction in critically ill patients using machine learning score by Fatimah, Dzaharudin, Azrina, Md Ralib, Ummu Kulthum, Jamaludin, Mohd Basri, Mat Nor, Afidalina, Tumian, Har, Lim Chiew, Ceng, T. C.

    Published 2020
    “…Various types of classification algorithms in machine learning were investigated using common clinical variables extracted from patient records obtained from four major ICUs in Malaysia to predict mortality and assign patient mortality risk scores. …”
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    Conference or Workshop Item