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Akademický článek

GCFC: Graph Convolutional Fusion CNN Network for Cross-Domain Zero-Shot Extraction of Winter Wheat Map

Autor: Chunyang Wang, Peipei Zhou, Yudong Zhang, Junding Sun, Bibo Lu, Zhaozhao Xu, Baishun Su, Xingwang Li

Publikováno v: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 9069-9089 (2024)

Accurate extraction of winter wheat and its planted area holds significance for agricultural research and government real-time food monitoring. Traditional machine learning methods often demand extensive data and corresponding labels for training in

Externí odkaz: https://doaj.org/article/3b33cc72f622404fa632ba21cce0c00f

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Akademický článek

Experimental study on the effect of Coumarone resin on the performance of SBS-modified asphalt.

Autor: Chenyu Feng, Chunhua Hu, Zhaobin Sun, Hao Zhang, Zhaozhao Xu

Publikováno v: PLoS ONE, Vol 19, Iss 4, p e0301528 (2024)

An inexpensive and high-performing solid Coumarone resin was added to Styrene-butadiene-styrene (SBS) copolymer-modified asphalt to enhance its storage stability and road performance. To assess the effect of Coumarone resin dosage on the SBS-modified

Externí odkaz: https://doaj.org/article/950af4b6a1024761b0193e2be4152fe6

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Akademický článek

A hybrid feature selection algorithm combining information gain and grouping particle swarm optimization for cancer diagnosis.

Autor: Fangyuan Yang, Zhaozhao Xu, Hong Wang, Lisha Sun, Mengjiao Zhai, Juan Zhang

Publikováno v: PLoS ONE, Vol 19, Iss 3, p e0290332 (2024)

BackgroundCancer diagnosis based on machine learning has become a popular application direction. Support vector machine (SVM), as a classical machine learning algorithm, has been widely used in cancer diagnosis because of its advantages in high-dimen

Externí odkaz: https://doaj.org/article/69267c895a6647b7847a9d86043375e7

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Akademický článek

CGUFS: A clustering-guided unsupervised feature selection algorithm for gene expression data

Autor: Zhaozhao Xu, Fangyuan Yang, Hong Wang, Junding Sun, Hengde Zhu, Shuihua Wang, Yudong Zhang

Publikováno v: Journal of King Saud University: Computer and Information Sciences, Vol 35, Iss 9, Pp 101731- (2023)

(Aim) Gene expression data is typically high dimensional with a limited number of samples and contain many features that are unrelated to the disease of interest. Existing unsupervised feature selection algorithms primarily focus on the significance

Externí odkaz: https://doaj.org/article/46a3e850623341f5a21d822188256445

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A cluster-based oversampling algorithm combining SMOTE and k-means for imbalanced medical data

Autor: Nan Yin, Zhaozhao Xu, Xi Han, Yue Kou, Tiezheng Nie, Derong Shen

Publikováno v: Information Sciences. 572:574-589

The algorithm of C4.5 decision tree has the advantages of high classification accuracy , fast calculation speed and comprehensible classification rules, so it is widely used for medical data analysis. However, for imbalanced medical data, the classif

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::0e519ab1c3fb424f7376e6f61b88c9f3
https://doi.org/10.1016/j.ins.2021.02.056

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A Synthetic Minority Oversampling Technique Based on Gaussian Mixture Model Filtering for Imbalanced Data Classification

Autor: Zhaozhao Xu, Derong Shen, Yue Kou, Tiezheng Nie

Publikováno v: IEEE transactions on neural networks and learning systems.

Data imbalance is a common phenomenon in machine learning. In the imbalanced data classification, minority samples are far less than majority samples, which makes it difficult for minority to be effectively learned by classifiers A synthetic minority

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6d969b28c3f5b92ad2b3111399973eed
https://pubmed.ncbi.nlm.nih.gov/35984792

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A hybrid feature selection algorithm combining ReliefF and Particle swarm optimization for high-dimensional medical data

Autor: Zhaozhao Xu, Yue Kou, Derong Shen, Tiezheng Nie

Publikováno v: Journal of Intelligent & Fuzzy Systems. :1-15

Due to high-dimensional feature and strong correlation of features, the classification accuracy of medical data is not as good enough as expected. feature selection is a common algorithm to solve this problem, and selects effective features by reduci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::6d1a98b07458e98c8166a584aa89b436
https://doi.org/10.3233/jifs-202948

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