Open Access
| Issue |
E3S Web Conf.
Volume 358, 2022
5th International Conference on Green Energy and Sustainable Development (GESD 2022)
|
|
|---|---|---|
| Article Number | 01018 | |
| Number of page(s) | 5 | |
| Section | Invited Contributions | |
| DOI | https://doi.org/10.1051/e3sconf/202235801018 | |
| Published online | 27 October 2022 | |
- Li Xingrong, Tong Le, Wang Lu, et al. Review of polymer flooding technology [J]. Contemporary Chemical Industry, 2017, 46(6): 1228–1230. [Google Scholar]
- Xu Hao. Optimization of alternate polymer injection parameters in polymer flooding oilfield [J]. Chemical Management, 2017 (11). [Google Scholar]
- Shi Chengfang, Xiao Wei, Wang Fenglan. Prediction model of polymer flooding development index [J]. Acta petrolei sinica, 2005, 26(5): 78–84. [Google Scholar]
- Zhao Guozhong, Meng Shuguang, Jiang Xiangcheng. A neural network method for predicting water content in polymer flooding [J]. Acta petrolei sinica, 2004, 25(1): 70–73. [Google Scholar]
- Qiu Haiyan, Ding Xianfeng, Hu Xiaoyun, et al. Prediction of oil production by polymer flooding using combinatorial model [J]. Xinjiang petroleum geology, 2010, 31(2): 194–196. [Google Scholar]
- Hou Jian, Zhao Hui, Du Qingjun, et al. Study on sensitive parameters affecting the performance of polymer flooding [J]. Journal of oil and gas technology, 2007, 29(1): 118–121. [Google Scholar]
- Hou Jian, Guo Lanlei, Yuan Fuqing, et al. Quantitative characterization of polymer flooding production performance of different types of reservoirs in shengli oilfield [J]. Acta petrolei sinica, 2008, 29(4): 577–581. [Google Scholar]
- Guo Qing. Research on Uncertain Information System and Decision Making Based on Rough Set Theory [D]. Hefei University of Technology, 2017. [Google Scholar]
- Zhang Qinghua, Xue Yubin, Wang Guoyin. Optimal Approximation Sets for Rough Sets [J]. Journal of Software, 2016, 27(2): 295–308. [Google Scholar]
- Li Jia, Liang Jiye, Pang Tianjie. A multi-attribute decision ranking method based on Dominant Rough Set [J]. Journal of Nanjing University (Natural Sciences), 2016, 52(5): 844–852. [Google Scholar]
- An Ruoming, So bright. Application of Neighborhood Rough Set in Attribute Reduction and Weight Calculation [J]. Computer Engineering and Applications, 2016, 52(7): 160–165. [Google Scholar]
- Xu Feng, Yao Sheng, Ji Xia, et al. Uncertainty measurement method of information system based on Fuzzy Neighborhood Rough Set [J]. Journal of Nanjing University (Natural Science), 2017(5):926–936. [Google Scholar]
- Shen Lin, Chen Jianhui. Variable Accuracy Neighborhood Rough Set attribute Reduction Algorithm based on lower approximate distribution [J]. Journal of Guizhou University (Natural Science Edition), 2017, 34(4): 53–58. [Google Scholar]
- Zhao Wei, Lin Nan, Han Ying, et al. An improved collaborative filtering algorithm based on K-means clustering [J]. Journal of Anhui University (SelfScience Edition), 2016, 40(2): 32–36. [Google Scholar]
- Ou Hui, Xia Zhuoqun, Wu Zhiwei. Rough Set K- means Clustering Algorithm based on Improved manifold Distance [J]. Computer Engineering and Applications, 2016, 52(14): 84–89 [Google Scholar]
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