Haochen Wang
China University of Petroleum
14 Papers
Haochen Wang is an academic researcher from China University of Petroleum. The author has contributed to research in topics: Computer science & Medicine. The author has an hindex of 1, co-authored 2 publications.
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Papers
Data-Driven Niching Differential Evolution with Adaptive Parameters Control for History Matching and Uncertainty Quantification
TL;DR: A novel data-driven niching differential evolution algorithm with adaptive parameter control for nonuniqueness of inversion, called DNDE-APC, designed to balance exploration and convergence in solving the multimodal inverse problems is proposed.
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Infectivity versus fatality of SARS-CoV-2 mutations and influenza
TL;DR: In this article , the authors developed transmission models for SARS-CoV-2 variants and influenza, in which transmission, death, and vaccination rates were taken to be time-varying.
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An Interpretable Interflow Simulated Graph Neural Network for Reservoir Connectivity Analysis
Haochen Wang,Jianfa Han,Kai Zhang,Chuanjin Yao,Xiaopeng Ma,Liming Zhang,Yongfei Yang,Huaqing Zhang,Jun Yao +8 more
TL;DR: An interpretable recurrent graph neural network is proposed to construct an interacting process imitating the real interwell flow regularity and overcoming the weakness in previous methods, showing significant advantages to other methods due to its reasonable structure and great ability to fit nonlinear mapping.
12
Long-Term Forecast of HIV/AIDS Epidemic in China with Fear Effect and 90-90-90 Strategies
Ling Xue,Kai Zhang,Haochen Wang +2 more
TL;DR: Wang et al. as mentioned in this paper formulated a compartmental model considering behavioral changes of susceptible individuals due to fear to assess the transmission dynamics of HIV/AIDS in mainland China and found that preventive measures are more effective than post-infection measures in eliminating the epidemic.
An Evolutionary Sequential Transfer Optimization Algorithm for Well Placement Optimization Based on Task Characteristics
TL;DR: In this article , a sequential ETO algorithm based on task characteristics and an autoencoder is developed to speed up the search for the optimal well locations and reduce the required time for WPO.
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