@article {doi:10.1142/S0129065720500495,
	title = {Spiking Neural P Systems with Extended Channel Rules},
	journal = {International Journal of Neural Systems},
	volume = {31},
	number = {ja},
	year = {2021},
	pages = {2050049},
	doi = {10.1142/S0129065720500495},
	author = {Zeqiong Lv and Tingting Bao and Nan Zhou and Hong Peng and Xiangnian Huang and Agust{\'\i}n Riscos-N{\'u}{\~n}ez and Mario J. P{\'e}rez-Jim{\'e}nez}
}
@article {WANG2019102,
	title = {Interval-valued fuzzy spiking neural P systems for fault diagnosis of power transmission networks},
	journal = {Engineering Applications of Artificial Intelligence},
	volume = {82},
	year = {2019},
	pages = {102 - 109},
	abstract = {It is a challenge problem how to deal with the uncertainty in fault diagnosis of power systems. To solve the challenge problem, this paper introduces an interval-valued fuzzy spiking neural P system (IVFSNP system), where the interval-valued fuzzy logic is integrated into spiking neural P systems to characterize the uncertainty. Based on the IVFSNP system, a fuzzy reasoning algorithm is presented, and the corresponding fault diagnosis model is developed. IVFSNP system is capable of describing the incomplete and uncertain fault signals from a supervisory control and data acquisition system equipped together with electric power systems. In order to evaluate the availability and effectiveness of the proposed fault diagnosis model, two case studies of fault diagnosis of a transmission network are discussed and analyzed, including complex and multiple fault situations with the incomplete and uncertain status signals. The results of the case studies demonstrate that IVFSNP system can be used to diagnose the faulty sections in power transmission networks accurately and effectively.},
	keywords = {Fault diagnosis, Fuzzy spiking neural P systems, Interval-valued fuzzy logic, Power transmission networks},
	issn = {0952-1976},
	doi = {https://doi.org/10.1016/j.engappai.2019.03.014},
	url = {http://www.sciencedirect.com/science/article/pii/S0952197619300648},
	author = {Jun Wang and Hong Peng and Wenping Yu and Jun Ming and Mario J. P{\'e}rez-Jim{\'e}nez and Chengyu Tao and Xiangnian Huang}
}
