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Application of an Interpretable Machine Learning Model to Predict Lymph Node Metastasis in Patients with Laryngeal Carcinoma 期刊论文
JOURNAL OF ONCOLOGY, 2022, 卷号: 2022, 页码: 12
作者:  Feng, Menglong;  Zhang, Juhong;  Zhou, Xiaoqing;  Mo, Hailan;  Jia, Lifeng;  Zhang, Chanyuan;  Hu, Yaqin;  Yuan, Wei
收藏  |  浏览/下载:44/0  |  提交时间:2022/12/26
Predicting Monthly Runoff of the Upper Yangtze River Based on Multiple Machine Learning Models 期刊论文
SUSTAINABILITY, 2022, 卷号: 14, 期号: 18, 页码: 23
作者:  Li, Xiao;  Zhang, Liping;  Zeng, Sidong;  Tang, Zhenyu;  Liu, Lina;  Zhang, Qin;  Tang, Zhengyang;  Hua, Xiaojun
收藏  |  浏览/下载:42/0  |  提交时间:2022/12/26
monthly runoff prediction  machine learning  copula entropy  stepwise regression  Upper Yangtze River  
Revealing Physiochemical Factors and Zooplankton Influencing Microcystis Bloom Toxicity in a Large-Shallow Lake Using Bayesian Machine Learning 期刊论文
TOXINS, 2022, 卷号: 14, 期号: 8, 页码: 16
作者:  Wang, Xiaoxiao;  Wang, Lan;  Shang, Mingsheng;  Song, Lirong;  Shan, Kun
收藏  |  浏览/下载:113/0  |  提交时间:2022/10/14
Microcystis blooms  microcystins  nutrient  zooplankton  machine learning  risk management  Lake Taihu  
Bayesian Network Structure Learning Approach Based on Searching Local Structure of Strongly Connected Components 期刊论文
IEEE ACCESS, 2022, 卷号: 10, 页码: 67630-67638
作者:  Zhong, Kunhua;  Chen, Yuwen;  Zhang, Ju;  Qin, Xiaolin
收藏  |  浏览/下载:58/0  |  提交时间:2022/08/22
Bayes methods  Approximation algorithms  Search problems  Directed graphs  Heuristic algorithms  Periodic structures  Random variables  Bayesian network  structure learning  hill climbing search  strongly connected component