A Hybrid Learning Method for the Data-Driven Design of Linguistic Dynamic Systems
文献类型：期刊论文
| 作者 | Li, Chengdong1; Yi, Jianqiang4 ; Lv, Yisheng3,4; Duan, Peiyong2
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| 刊名 | IEEE-CAA JOURNAL OF AUTOMATICA SINICA
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| 出版日期 | 2019-11-01 |
| 卷号 | 6期号:6页码:1487-1498 |
| 关键词 | Fuzzy set least square method linguistic dynamic system (LDS) multi-objective optimization |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2019.1911543 |
| 通讯作者 | Lv, Yisheng(yisheng.lv@ia.ac.cn) |
| 英文摘要 | In lots of data based prediction or modeling applications, uncertainties and/or noises in the observed data cannot be avoided. In such cases, it is more preferable and reasonable to provide linguistic (fuzzy) predicted results described by fuzzy memberships or fuzzy sets instead of the crisp estimates depicted by numbers. Linguistic dynamic system (LDS) provides a powerful tool for yielding linguistic (fuzzy) results. However, it is still difficult to construct LDS models from observed data. To solve this issue, this paper first presents a simplified LDS whose input-output mapping can be determined by closed-form formulas. Then, a hybrid learning method is proposed to construct the data-driven LDS model. The proposed hybrid learning method firstly generates fuzzy rules by the subtractive clustering method, then carries out further optimization of centers of the consequent triangular fuzzy sets in the fuzzy rules, and finally adopts multi-objective optimization algorithm to determine the left and right end-points of the consequent triangular fuzzy sets. The proposed approach is successfully applied to three real-world prediction applications which are: prediction of energy consumption of a building, forecasting of the traffic flow, and prediction of the wind speed. Simulation results show that the uncertainties in the data can be effectively captured by the linguistic (fuzzy) estimates. It can also be extended to some other prediction or modeling problems, in which observed data have high levels of uncertainties. |
| WOS关键词 | ENERGY-CONSUMPTION ; FUZZY ; IMPACT ; WORDS |
| 资助项目 | National Natural Science Foundation of China[61473176] ; National Natural Science Foundation of China[61773246] ; Natural Science Foundation of Shandong Province for Outstanding Young Talents in Provincial Universities[ZR2015JL021] ; Taishan Scholar Project of Shandong Province[TSQN201812092] |
| WOS研究方向 | Automation & Control Systems |
| 语种 | 英语 |
| WOS记录号 | WOS:000503189200018 |
| 出版者 | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
| 资助机构 | National Natural Science Foundation of China ; Natural Science Foundation of Shandong Province for Outstanding Young Talents in Provincial Universities ; Taishan Scholar Project of Shandong Province |
| 源URL | [http://ir.ia.ac.cn/handle/173211/29437]  |
| 专题 | 综合信息系统研究中心_飞行器智能技术 |
| 通讯作者 | Lv, Yisheng |
| 作者单位 | 1.Shandong Jianzhu Univ, Sch Informat & Elect Engn, Jinan 250101, Shandong, Peoples R China 2.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250014, Shandong, Peoples R China 3.Qingdao Acad Intelligent Ind, Qingdao 266109, Shandong, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Chengdong,Yi, Jianqiang,Lv, Yisheng,et al. A Hybrid Learning Method for the Data-Driven Design of Linguistic Dynamic Systems[J]. IEEE-CAA JOURNAL OF AUTOMATICA SINICA,2019,6(6):1487-1498. |
| APA | Li, Chengdong,Yi, Jianqiang,Lv, Yisheng,&Duan, Peiyong.(2019).A Hybrid Learning Method for the Data-Driven Design of Linguistic Dynamic Systems.IEEE-CAA JOURNAL OF AUTOMATICA SINICA,6(6),1487-1498. |
| MLA | Li, Chengdong,et al."A Hybrid Learning Method for the Data-Driven Design of Linguistic Dynamic Systems".IEEE-CAA JOURNAL OF AUTOMATICA SINICA 6.6(2019):1487-1498. |
入库方式： OAI收割
来源：自动化研究所
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