WANG , Jun

The power coordination control of a photovoltaic/battery microgrid is performed with a novel bio-computing model within the framework of membrane computing. First, a neural-like P system with state values (SVNPS) is proposed for describing complex logical relationships between different modes of Photovoltaic (PV) units and energy storage units....

Spiking neural P systems (in short, SN P systems) and their variants, in- cluding fuzzy spiking neural P systems (in short, FSN P systems), generally lack learning ability so far. Aiming at this problem, a class of modi ed FSN P systems are proposed in this paper, called adaptive fuzzy spiking neural P systems (in short, AFSN P systems). The...

Spiking neural P systems (SN P systems) have been well established as a novel class of distributed parallel computing models. Some features that SN P systems possess are attractive to fault diagnosis. However, handling fuzzy diagnosis knowledge and reasoning is required for many fault diagnosis applications. The lack of ability is a major...

Spiking neural P systems were proved to be Turing complete as function computing or number generating devices. Moreover, it has been considered in several papers that spiking neural P systems are also computationally efficient devices working in a non-deterministic way or with exponential pre-computed resources. In this paper, neuron budding...

Spiking neural P systems (SN P systems) are a new class of computing models inspired by the neurophysiological be-havior of biological spiking neurons. In order to make SN P sys-tems capable of representing and processing fuzzy and uncertain knowledge, we propose a new class of spiking neural P systems in this paper called weighted fuzzy...

An optimization spiking neural P system (OSNPS) provides a novel way to directly use a P system to solve optimization problems. This paper discusses the practical application of OSNPS for the first time and uses it to solve the power system fault section estimation problem formulated by an optimization problem. When the status information of...

In this paper, intuitionistic fuzzy spiking neural P (IFSNP) systems as a variant are proposed by integrating intuitionistic fuzzy logic into original spiking neural P systems. Compared with a common fuzzy set, intuitionistic fuzzy set can more finely describe the uncertainty due to its membership and non-membership degrees. Therefore, IFSNP...

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...

This paper proposes a graphic modeling approach, fault diagnosis method based on fuzzy reasoning spiking neural P systems (FDSNP), for power transmission networks. In FDSNP, fuzzy reasoning spiking neural P systems (FRSN P systems) with trapezoidal fuzzy numbers are used to model candidate faulty sections and an algebraic fuzzy reasoning...

The conventional methods are not effective and efficient for image multi-level thresholding due to time-consuming and expensive computation cost. The multi-level thresholding problem can be posed as anoptimization problem, optimizing some thresholding criterion. In this paper, membrane computing isintroduced to propose an efficient and robust...

Membrane computing (known as P systems) is a class of distributed parallel computing models, this paper presents a novel algorithm under membrane computing for solving the data clustering problem, called as membrane clustering algorithm. The clustering algorithm is based on a tissue-like P system with a loop structure of cells. The objects of...

Energy Internet (EI) is an inevitable development trend of energy systems under the background of technology development, environmental pressure and energy transition. Multi-energy flow coupling is one of the key characteristics of the EI, which enhances the interoperability of different types of energy flows while consequently increases the...

Communication networks as smart infrastructure systems play an important role in smart girds to monitor, control, and manage the operation of electrical networks. However, due to the interdependencies between communication networks and electrical networks, once communication networks fail (or are attacked), the faults can be easily propagated...

To reveal fault propagation paths is one of the most critical studies for the analysis of power system security; however, it is rather dif cult. This paper proposes a new framework for the fault propagation path modeling method of power systems based on membrane computing.We rst model the fault propagation paths by proposing the event spiking...

Multi-level thresholding methods are a class of most popular image segmentation techniques, however, they are not computationally efficient since they exhaustively search the optimal thresholds to optimize the objective function. In order to eliminate the shortcoming, a novel multi-level thresholding method for image segmentation based on...

Membrane computing (known as P systems) is a novel class of distributed parallel computing models inspired by the structure and functioning of living cells and organs, and its application to the real-world problems has become a hot topic in recent years. This paper discusses an interesting open problem in digital watermarking domain, optimal...

This paper focuses on the unsupervised learning problem within membrane computing, and proposes an innovative solution inspired by membrane computing techniques, the fuzzy membrane clustering algorithm. An evolution–communication P system with nested membrane structure is the core component of the algorithm. The feasible cluster centers are...

Pulse coupled neural networks (PCNN, for short) are models abstracting the synchronization behavior observed experimentally for the cortical neurons in the visual cortex of a cat's brain, and the intersecting cortical model is a simplified version of the PCNN model. Membrane computing (MC) is a kind computation paradigm abstracted from the...

This paper focuses on power system fault diagnosis based on Weighted Corrective Fuzzy Reasoning Spiking Neural P Systems with real numbers (rWCFRSNPSs) to propose a graphic fault diagnosis method, called FDWCFRSNPS. In the FD-WCFRSNPS, an rWCFRSNPS is proposed to model the logical relationships between faults and potential warning messages...