11 Papers
8 Citations
Tong Li is an academic researcher from Yunnan Agricultural University. The author has contributed to research in topics: Computer science & Statistical classification. The author has an hindex of 3, co-authored 11 publications.
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Papers
Conditional Wasserstein generative adversarial network-gradient penalty-based approach to alleviating imbalanced data classification
TL;DR: Experiments demonstrate that CWGAN-GP increases the quality of synthetic data and outperforms the other oversampling approaches based on three evaluation metrics (F-measure, G-mean, and the area under the receiver operating characteristic curve) for five classifiers.
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Traffic Accident’s Severity Prediction: A Deep-Learning Approach-Based CNN Network
TL;DR: A novel traffic accident's severity prediction-convolutional neural network (TASP-CNN) model for traffic accident’s severity prediction is proposed that considers combination relationships among traffic accident′s features and has a better performance.
UFFDFR: Undersampling framework with denoising, fuzzy c-means clustering, and representative sample selection for imbalanced data classification
Ming Zheng,Tong Li,Xiaoyao Zheng,Qingying Yu,Chuanming Chen,Ding Zhou,Changlong Lv,Weiyi Yang +7 more
TL;DR: A novel three-stage undersampling framework with denoising, fuzzy c-means clustering, and representative sample selection (UFFDFR) is proposed that improves the classification performance on imbalanced data by removing noise and unrepresentative samples from the majority class.
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An automatic sampling ratio detection method based on genetic algorithm for imbalanced data classification
TL;DR: In this article, the authors proposed three algorithms to automatically determine the sampling ratios for oversampling, undersampling and hybrid sampling methods, based on a genetic algorithm, to obtain satisfactory and stable classification performance.
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ETC-Oriented Efficient and Secure Blockchain: Credit-Based Mechanism and Evidence Framework for Vehicle Management
TL;DR: A blockchain architecture for the ETC system based on an open-source alliance blockchain framework called Hyperledger Fabric, which is more in line with the current application scenarios of ETC systems and reduces the number of illegal acts, completes the evidence inspection, and improves the security of the data.
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