This paper proposed parking robot based on fuzzy reasoning and parking big data. The parking difficulty membership degree was computed on the basis of the time spent for looking for parking space at parking lot. The free membership degree at the current time corresponding to the parking difficulty membership degree of the parking lot can be reasoned out based on the parking difficulty membership degree and the free membership degree of the parking lot at each preset time point. The parking robot will reduce the cost needed to predict the free membership degree of the parking lot.
SuhrJ.K., JungH.G., BaeK., et al., Automatic free parking space detection by using motion stereo-based 3D reconstruction, Mach Vision Appl21(2) (2010), 163–176.
2.
MathewS.S., AtifY., ShengQ.Z., et al., Building sustainable parking lots with the Web of Things, Pers Ubiquit Comput18(4) (2014), 895–907.
3.
ChenZ., XiaJ.C. and IrawanB., Development of fuzzy logic forecast models for location-based parking finding services, Math Probl Eng2013 (2013).
4.
ZhuD., Boolean discrete network and dynamic equations to control parking fees, J Differ Equ Appl (2016), 1–15.
5.
PengH., WangJ., PéRez-JiméNezM.J., et al., Fuzzy reasoning spiking neural P system for fault diagnosis, Inform Sciences235 (2013), 106–116.
6.
MeloH. and WatadaJ., Gaussian-PSO with fuzzy reasoning based on structural learning for training a Neural Network, Neurocomputing172 (2016), 405–412.
7.
AminM. and SheblD., Reasoning dynamic fuzzy systems based on adaptive fuzzy higher order Petri nets, Inform Sciences286 (2014), 161–172.
8.
BingL., NingY. and YeHongD., LAV path planning by enhanced fireworks algorithm on prior knowledge, Appl Math Nonlinear Sci1(1) (2016), 63–73.
9.
ZhuL., PanY. and WangJ., Affine transformation based ontology sparse vector learning algorithm, Appl Math Nonlinear Sci2(1) (2017), 111–122.
10.
García-DiéguezC., HervaM. and RocaE., A decision support system based on fuzzy reasoning and AHP–FPP for the ecodesign of products: Application to footwear as case study, Appl Soft Comput26 (2015), 224–234.
11.
WangT., ZhangG., RongH., et al., Application of fuzzy reasoning spiking neural P systems to fault diagnosis, Int J Comput Commun9(6) (2014), 786–799.
12.
WangT., ZhangG., ZhaoJ., et al., Fault diagnosis of electric power systems based on fuzzy reasoning spiking neural P systems, IEEE T Power Syst30(3) (2015), 1182–1194.
