PMID- 25506358
OWN - NLM
STAT- MEDLINE
DCOM- 20150707
LR  - 20191210
IS  - 1687-5273 (Electronic)
IS  - 1687-5265 (Print)
VI  - 2014
DP  - 2014
TI  - A novel adjustment method for shearer traction speed through integration of T-S 
      cloud inference network and improved PSO.
PG  - 865349
LID - 10.1155/2014/865349 [doi]
LID - 865349
AB  - In order to efficiently and accurately adjust the shearer traction speed, a novel 
      approach based on Takagi-Sugeno (T-S) cloud inference network (CIN) and improved 
      particle swarm optimization (IPSO) is proposed. The T-S CIN is built through the 
      combination of cloud model and T-S fuzzy neural network. Moreover, the IPSO 
      algorithm employs parameter automation adjustment strategy and velocity resetting 
      to significantly improve the performance of basic PSO algorithm in global search 
      and fine-tuning of the solutions, and the flowchart of proposed approach is 
      designed. Furthermore, some simulation examples are carried out and comparison 
      results indicate that the proposed method is feasible, efficient, and is 
      outperforming others. Finally, an industrial application example of coal mining 
      face is demonstrated to specify the effect of proposed system.
FAU - Si, Lei
AU  - Si L
AD  - School of Mechatronic Engineering, China University of Mining & Technology, 
      Xuzhou 221116, China.
FAU - Wang, Zhongbin
AU  - Wang Z
AD  - School of Mechatronic Engineering, China University of Mining & Technology, 
      Xuzhou 221116, China.
FAU - Liu, Xinhua
AU  - Liu X
AUID- ORCID: 0000-0002-8632-6532
AD  - School of Mechatronic Engineering, China University of Mining & Technology, 
      Xuzhou 221116, China ; Xuyi Mine Equipment and Materials R&D Center, China 
      University of Mining & Technology, Huai'an 211700, China.
FAU - Yang, Yinwei
AU  - Yang Y
AD  - School of Mechatronic Engineering, China University of Mining & Technology, 
      Xuzhou 221116, China.
FAU - Zhang, Lin
AU  - Zhang L
AUID- ORCID: 0000-0003-0866-7937
AD  - School of Mechatronic Engineering, China University of Mining & Technology, 
      Xuzhou 221116, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20141123
PL  - United States
TA  - Comput Intell Neurosci
JT  - Computational intelligence and neuroscience
JID - 101279357
SB  - IM
MH  - Algorithms
MH  - *Computer Simulation
MH  - Humans
MH  - *Mechanical Phenomena
MH  - *Models, Theoretical
MH  - *Neural Networks, Computer
MH  - *Traction
PMC - PMC4259143
EDAT- 2014/12/17 06:00
MHDA- 2015/07/08 06:00
PMCR- 2014/11/23
CRDT- 2014/12/16 06:00
PHST- 2014/07/10 00:00 [received]
PHST- 2014/11/10 00:00 [accepted]
PHST- 2014/12/16 06:00 [entrez]
PHST- 2014/12/17 06:00 [pubmed]
PHST- 2015/07/08 06:00 [medline]
PHST- 2014/11/23 00:00 [pmc-release]
AID - 10.1155/2014/865349 [doi]
PST - ppublish
SO  - Comput Intell Neurosci. 2014;2014:865349. doi: 10.1155/2014/865349. Epub 2014 Nov 
      23.