Search Results - (( feature classification using algorithm ) OR ( using optimization sensor algorithm ))

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  1. 1

    Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

    Published 2025
    “…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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  2. 2

    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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  3. 3

    Integrated approach using data mining-based decision tree and object-based image analysis for high-resolution urban mapping of WorldView-2 satellite sensor data by Hamedianfar, Alireza, Mohd Shafri, Helmi Zulhaidi

    Published 2016
    “…Many features were explored by using a DM algorithm, which created the classification rules as a decision tree (DT) structure from the first study area. …”
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  4. 4

    Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

    Published 2019
    “…It applies the characteristic of ReliefF algorithm to rank and select top scoring features for feature selection. …”
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  5. 5

    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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  6. 6

    Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti by Abd Mukti, Shahrul Nizan

    Published 2022
    “…The study set four main objectives to achieve its aim: (1) To analyse RGB and multispectral sensor calibration, (2) To evaluate the optimal flight parameters for pothole modelling production using RGB imagery, (3) To investigate various classifier algorithms and band combinations for pothole region areas using multispectral imagery and (4) To validate geometric information from the extracted pothole. …”
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  7. 7

    Ensemble Filter Based Feature Selection Technique for Classification of Human Activity Recognition by Norfadzlan, Yusup, Azlan, Mohd Zain

    Published 2025
    “…An ensemble Random Forest (RF) was used as the base classifier to evaluate the performance of the hybrid algorithm. …”
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  8. 8

    Drowsiness Detection Using Ocular Indices from EEG Signal by Tarafder, S., Badruddin, N., Yahya, N., Nasution, A.H.

    Published 2022
    “…In this study, we used the BLINKER algorithm to extract 25 blink-related features from a public dataset comprising raw EEG signals collected from 12 participants. …”
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    Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

    Published 2019
    “…In conclusion, the electromyography controlled hand robot prototype was successfully developed with improved features, optimal structural durability, higher accurate movement capability, reliable system and lower number of sensor used with higher accuracy of the signal pattern classification.…”
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  11. 11

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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  12. 12

    Framework for pedestrian walking behaviour recognition to minimize road accident by Hashim Kareem, Zahraa

    Published 2021
    “…The results indicate the following: (1) From 262 samples, 66.80% and 48.10% of respondents use mobile phones for calling and chatting, respectively. (2) 263 samples of participants are obtained and analysed, and 90 features are extracted from each sample. (3) 100% classification accuracy are obtained for each class (normal walking, calling, chatting, and running) using the grid optimiser method in machine learning. (4) The precision of classification using Euclidean algorithm for normal walking and calling is 70%. …”
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    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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    Evaluation of multiple In Situ and remote sensing system for early detection of Ganoderma boninense infected oil palm by Ahmadi, Seyedeh Parisa

    Published 2018
    “…In the next phase, the SVM classifier was trained to achieve the best classification using training data and test data integrated with selected features. …”
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    Utilizing artificial bee colony algorithm as feature selection method in Arabic text classification by Hijazi, Musab, Zeki, Akram M., Ismail, Amelia Ritahani

    Published 2023
    “…One of the widely used algorithms for feature selection in text classification is the Evolutionary algorithm . …”
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  18. 18

    Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification by Petwan, Montha

    Published 2023
    “…However, the FGCDR produced a substantial amount of redundant and insignificant features. The ant colony optimisation (ACO) algorithm have been used to select feature subset. …”
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  19. 19

    A novel hybrid classification model of genetic algorithms, modified k-Nearest Neighbor and developed backpropagation neural network by Salari, Nader, Shohaimi, Shamarina, Najafi, Farid, Nallappan, Meenakshii, Karishnarajah, Isthrinayagy

    Published 2014
    “…Second, the obtained results that included arrays of the top-ranked features were used as the initial population of a genetic algorithm to produce optimum arrays of features. …”
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    ABC: android botnet classification using feature selection and classification algorithms by Abdullah, Zubaile, Mohd Saudi, Madihah, Anuar, Nor Badrul

    Published 2017
    “…In this paper, a new approach for Android botnet classification based on features selection and classification algorithms is proposed. …”
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