Showing 241 - 260 results of 427 for search '"feature selection"', query time: 0.09s Refine Results
  1. 241

    Machine Learning Approaches for Developing Land Cover Mapping by Ali Alzahrani, Awos Kanan

    Published 2022-01-01
    “…In this work, a genetic algorithm-based feature selection approach is used to enhance the performance of urban land cover classification. …”
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    Article
  2. 242

    A Simultaneous Fault Diagnosis Method Based on Cohesion Evaluation and Improved BP-MLL for Rotating Machinery by Yixuan Zhang, Rui Yang, Mengjie Huang, Yu Han, Yiqi Wang, Yun Di, Dongke Su, Qidong Lu

    Published 2021-01-01
    “…In this paper, an improved simultaneous fault diagnostic algorithm with cohesion-based feature selection and improved backpropagation multilabel learning (BP-MLL) classification is proposed to localize and diagnose different simultaneous faults on gearbox and bearings in rotating machinery. …”
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    Article
  3. 243

    Capsule neural network and adapted golden search optimizer based forest fire and smoke detection by Luling Liu, Li Chen, Mehdi Asadi

    Published 2025-02-01
    “…Testing this model on wildfire smoke imagery and the BowFire dataset reveals that the proposed methodology outperformed traditional feature selection and classification methods. The integration of the modified CNN and AGSO facilitated rapid response and mitigation efforts, enhancing the accuracy and dependability of forest fire identification. …”
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    Article
  4. 244

    Analysis and Implementation of Optimization Techniques for Facial Recognition by Justice Kwame Appati, Huzaifa Abu, Ebenezer Owusu, Kwaku Darkwah

    Published 2021-01-01
    “…In this study, the principal component analysis (PCA) method with the inherent property of dimensionality reduction was adopted for feature selection. The resultant features were optimized using the particle swarm optimization (PSO) algorithm. …”
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    Article
  5. 245

    Data and Feature Reduction in Fuzzy Modeling through Particle Swarm Optimization by S. Sakinah S. Ahmad, Witold Pedrycz

    Published 2012-01-01
    “…In contrast to the existing studies, which are focused predominantly on feature selection (namely, a reduction of the input space), a position advocated here is that a reduction has to involve both data and features to become efficient to the design of fuzzy model. …”
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  6. 246

    An Approach to Fault Diagnosis for Gearbox Based on Image Processing by Yang Wang, Yujie Cheng

    Published 2016-01-01
    “…This work addresses a fault diagnosis method based on an image processing method for a gearbox, which overcomes the limitations of manual feature selection. Differing from the analysis method in a one-dimensional space, the computing method in the field of image processing in a 2-dimensional space is applied to accomplish autoextraction and fault diagnosis of a gearbox. …”
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    Article
  7. 247

    Feature subset evaluation method for upper limb rehabilitation training based on joint feature discernibility by Guoyu Zuo, Zhaokun Xu, Jiahao Lu, Daoxiong Gong

    Published 2019-03-01
    “…A feature subset discernibility hybrid evaluation method using Fisher score based on joint feature and support vector machine is proposed for the feature selection problem of the upper limb rehabilitation training motion of Brunnstrom 4–5 stage patients. …”
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    Article
  8. 248

    Automated Diagnosis of Coronary Artery Disease: A Review and Workflow by Qurat-ul-ain Mastoi, Teh Ying Wah, Ram Gopal Raj, Uzair Iqbal

    Published 2018-01-01
    “…Subsequently, stages (feature selection and classification) are same for both workflows. …”
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    Article
  9. 249

    Cloud-Based Framework for COVID-19 Detection through Feature Fusion with Bootstrap Aggregated Extreme Learning Machine by Amjad Rehman Khan, Tanzila Saba, Tariq Sadad, Seng-phil Hong

    Published 2022-01-01
    “…The gain ratio is applied for feature selection to remove insignificant features. An extreme learning machine (ELM) is a neural network modification with a high capability for pattern recognition and classification problems for COVID-19 detection. …”
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    Article
  10. 250

    Looking for Peer Circles: Graph-Mining-Based Educational Assessment and Refinement Toward Physical Instructors by Yuhe Zhu

    Published 2025-01-01
    “…To overcome these challenges, we propose a geometry-based feature selection technique to identify high-quality features that best represent each instructor’s teaching style. …”
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    Article
  11. 251

    Enhanced classification of medicinal plants using deep learning and optimized CNN architectures by Hicham Bouakkaz, Mustapha Bouakkaz, Chaker Abdelaziz Kerrache, Sahraoui Dhelim

    Published 2025-02-01
    “…In this framework, a CNN architecture with residual and inverted residual block configurations is selected, and a set of data augmentation is applied to improve the dataset. Concerning feature selection, it adopts Binary Chimp Optimization and serial feature fusion regarding accuracy and speed. …”
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    Article
  12. 252

    Flight Delay Classification Prediction Based on Stacking Algorithm by Jia Yi, Honghai Zhang, Hao Liu, Gang Zhong, Guiyi Li

    Published 2021-01-01
    “…In this research, the principle of the Stacking classification algorithm is introduced, the SMOTE algorithm is selected to process imbalanced datasets, and the Boruta algorithm is utilized for feature selection. There are five supervised machine learning algorithms in the first-level learner of Stacking including KNN, Random Forest, Logistic Regression, Decision Tree, and Gaussian Naive Bayes. …”
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    Article
  13. 253

    A Multiple-Classifier Framework for Parkinson’s Disease Detection Based on Various Vocal Tests by Mahnaz Behroozi, Ashkan Sami

    Published 2016-01-01
    “…When our methodology comes with filter-based feature selection, it enhances classification accuracy up to 15%.…”
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    Article
  14. 254

    Application of an Improved TF-IDF Method in Literary Text Classification by Lin Xiang

    Published 2022-01-01
    “…Using the improved TF-IDF method suggested in this research with the random forest (RF) classifier, the experimental results show that the classifier has a good classification impact, which can meet the actual work needs, based on comparative experiments on feature dimension selection, feature selection algorithm, feature weight algorithm, and classifier. …”
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  15. 255

    HYEI: A New Hybrid Evolutionary Imperialist Competitive Algorithm for Fuzzy Knowledge Discovery by D. Jalal Nouri, M. Saniee Abadeh, F. Ghareh Mohammadi

    Published 2014-01-01
    “…Initially, the best feature subset is selected by using the embedded ICA feature selection, and then these features are used to generate basic fuzzy-classification rules. …”
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    Article
  16. 256

    GA-Attention-Fuzzy-Stock-Net: An optimized neuro-fuzzy system for stock market price prediction with genetic algorithm and attention mechanism by Burak Gülmez

    Published 2025-02-01
    “…The model's superior performance is attributed to its unique integration of evolutionary optimization, attention-based feature selection, and fuzzy logic's ability to handle uncertainty in financial data.…”
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    Article
  17. 257

    Online multi‐object tracking based on time and frequency domain features by Mahbubeh Nazarloo, Meisam Yadollahzadeh‐Tabari, Homayun Motameni

    Published 2022-01-01
    “…The modified cuckoo optimization algorithm is utilized for feature selection, which has the ability such as fast convergence and global optima finding. …”
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    Article
  18. 258

    Fault Diagnosis Method for Rotating Machinery Based on Hierarchical Amplitude-Aware Permutation Entropy and Pairwise Feature Proximity by Ling Shu, Jinxing Shen, Xiaoming Liu

    Published 2021-01-01
    “…Combined with the pairwise feature proximity (PWFP) feature selection method and gray wolf algorithm optimization support vector machine (GWO-SVM), a new intelligent fault diagnosis method for rotating machinery is proposed. …”
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    Article
  19. 259

    AquaYOLO: Enhancing YOLOv8 for Accurate Underwater Object Detection for Sonar Images by Yanyang Lu, Jingjing Zhang, Qinglang Chen, Chengjun Xu, Muhammad Irfan, Zhe Chen

    Published 2025-01-01
    “…In addition, we introduce Dynamic Selection Aggregation Module (DSAM) and Context-Aware Feature Selection (CAFS) in the neck network. These modifications allow AquaYOLO to capture intricate details better and reduce feature redundancy, leading to improved performance in underwater object detection tasks. …”
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    Article
  20. 260

    Federated Learning-Based Load Forecasting for Energy Aggregation Service Providers by HUANG Yichuan, SONG Yuhui, JING Zhaoxia

    Published 2025-01-01
    “…First,an artificial neural network with multidimensional environmental feature selection is established according to the task requirements. …”
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