# A Review of Power System Fault Diagnosis with Spiking Neural P Systems
## 1 Introduction
Moreover, since P systems communicate with each other using rules, it is important to investigate communication complexity of the P systems [38]. Along with finding the analytic solutions for computationally hard problems using the concept of space-time trade-off, in recent years the study of constructing evolutionary algorithms by combining the structure and operations of membrane systems and capabilities of optimization algorithms has gained prominence [39]. Furthermore, approximate solutions of these problems are obtained by using the algorithms which are popularly known as \"membrane algorithms\". In [40], the solution of an well-known NP -complete problem, i.e., Graph coloring problem (GCP) is obtained by using OLMS (one level membrane structure (OLMS) [41; 42; 43]) membrane algorithm with dynamic operators. Automatic design of P systems is also an attractive work and promising research direction [44; 45; 46; 47]. Membrane computing models have a wide range of real-life applications [39; 48; 49; 50; 51; 52] and the investigation more problems from different areas of real-life applications which can be solved by these models has drawn huge interest amongst many researchers around the global. One of the most interesting application of membrane computing models has been in the area of \"Robotics\". In particular, the use of membrane computing models for designing of membrane controllers for single and multi-robot systems which further helps in navigation of the robot in unknown environments [48; 53; 54; 55]. In recent years, many variants of P systems such as enzymatic numerical P systems, XP-colonies, etc. have been used in single and multiple-robot applications. The membrane controllers based on the membrane computing models are efficient and have comparable performance with respect to traditional robot controllers [48]. Image processing is another area where membrane computing models have been used extensively. Parallel distributed architecture along with the multisets present in the membranes which is useful for encoding of the information, make P systems a suitable model for dealing with digital images. Furthermore, these models can be used in image segmentation, skeletonization, etc. [49]. Moreover, SNPS models can perform binary operations and these models are also suitable to be used in cryptographic applications [56]. Array rewriting P systems can be used as a tool for generation of Peano curve, the Hilbert curve, etc. In [57], a state-of-the-art based on the P systems with parallel rewriting was introduced for generation of the space-filling curves, and related curves. Membrane computing models also have been used for modelling and simulation of many phenomena existing in Biochemistry, Ecology, Robotics or Engineering [51]. These models also can model communities of very simple reactive agents living and acting in a joint shared environment. These types of membrane computing models are known as \"P colonies\" [58]. P colonies can simulate the interactive processes in other mechanisms such as reaction system which is inspired from the different chemical reactions happening in the environment [59]. P systems are also useful in modeling many biological phenomena such as swarming and aggregating behaviour in Myxobacteria bacterial populations [60; 61]. Neural-like P systems/Spiking neural P systems (SNPS) [62] have gained popularity amongst the researchers because of its similarities with third-generation neural networks, i.e., spiking neural networks (SNNs) [63]. In recent years, the research in SNPS also has gained huge momentum and many variants of SNPS have been introduced inspired by the properties present in the biological neurons. Many variants of it already have been introduced along with investigations regarding their computational power [64; 65], efficiency in solving computationally hard problems [66] and real-life applications [67; 68; 69]. A new variant of SNPS is introduced in [32] where the firing and forgetting rules are applied in generalized manner.