Reliability evaluation of distribution network based on fuzzy spiking neural P system with self-synapse

Huang, Yulei; Wang, Tao; Wang, Jun; Peng, Hong

doi:10.1007/s41965-020-00035-1

Cited by 17 publications

(2 citation statements)

References 31 publications

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“…e PNMS consists of neurons (single cells), a large number of which form a directed graph. Neurons send pulses to neighboring neurons through synapses, and the pulses undergo transformation (evolution) through excitation rules [33,34]. e PNMS with a definition of degree n is as follows:…”

Section: Construction Of Spatio-temporally Encoded Pulsed Neural Memb...mentioning

confidence: 99%

Spatio-Temporal Coding-Based Helicopter Trajectory Planning for Pulsed Neural Membrane System

Huang

et al. 2022

Computational Intelligence and Neuroscience

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For the trajectory planning problem under the nonlinear and strongly coupled characteristics of unmanned helicopters, membrane computing with distributed parallel processing capability is introduced for unmanned helicopter trajectory planning. The global and local spatial information is temporally characterized; the temporal characterization algorithm under mapping information is designed; the hierarchical discriminant regression algorithm is designed based on incremental principal component analysis to realize the process of building and identifying trees in trajectory planning; and the pulsed neural membrane system (PNMS) with spatio-temporal coding function under membrane computing is constructed. Compared with the RRT algorithm in two experimental environments, the original path length, the trimmed path length, the time used to plan the trajectory, and the number of search nodes have different levels of improvement; the feasibility and effectiveness of the PNMS in unmanned helicopter trajectory planning are verified. It expands the theoretical research of membrane computing in the field of optimal control and provides theoretical support for the subsequent application practice.

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Section: Construction Of Spatio-temporally Encoded Pulsed Neural Memb...mentioning

confidence: 99%

Spatio-Temporal Coding-Based Helicopter Trajectory Planning for Pulsed Neural Membrane System

Huang

et al. 2022

Computational Intelligence and Neuroscience

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“…Experiments show that the newer energy is connected to the power grid, the higher the reliability of the power grid and the reserve capacity of the distribution station is directly proportional to the reliability of the power grid. In [5], the authors tested the reliability of a distribution network based on fuzzy spiking neural P system, considering the uncertainty of new energy access to the power grid and the deviation in the interactive power of tie lines between regions. Aiming at the problems existing in the cross-regional dispatching of new energy, the authors in [6] propose to design the decentralized collaborative debugging path of the multiregional interconnected systems according to the debugging level and solve the main problems and subproblems in the debugging problem respectively.…”

Section: Instructionmentioning

confidence: 99%

Research on Static and Dynamic Fragile Node Identification Algorithms Based on Uncertainty in New Energy

Lin

Wang²,

Liu

et al. 2022

Scientific Programming

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In order to identify the uncertain static and dynamic fragile nodes in new energy, the instability and randomness of new energy bring new challenges to the identification of vulnerable nodes in a power grid. Due to the characteristics of low cost and low energy consumption of new energy, people have paid much attention to the exploration and development of new energy. Due to the uncertainty of new energy, it is needed to properly analyze the uncertainty factors. To analyze the uncertainty factors in new energy using the framework of power big data artificial intelligence analysis based on cost-benefit analysis (CBA), it is required to carry out Fourier transform and extract the data characteristic matrix so that a vulnerability risk prediction index can be obtained by using a fuzzy convolution algorithm and binarization, and the safety form between the uncertainty factors in new energy and power stations can be evaluated. In this paper, a fuzzy neural network algorithm is proposed to identify the static and dynamic fragile nodes based on the uncertainty in new energy, so as to ensure the security and stability of the power generation system. The safety performance of the power station system is detected through different levels of early warning sensitivity. The simulation model of the above algorithm is constructed in MATLAB. The simulation results show that the proposed algorithm increases the sensitivity of the early warning system of the power station and the sensitivity of triggering the early warning system and improves the security of the power station system as a whole.

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Research on Ship Speed Prediction Model Based on BP Neural Network

et al. 2022

Communications in Computer and Information Science

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Reliability evaluation of distribution network based on fuzzy spiking neural P system with self-synapse

Cited by 17 publications

References 31 publications

Spatio-Temporal Coding-Based Helicopter Trajectory Planning for Pulsed Neural Membrane System

Spatio-Temporal Coding-Based Helicopter Trajectory Planning for Pulsed Neural Membrane System

Research on Static and Dynamic Fragile Node Identification Algorithms Based on Uncertainty in New Energy

Research on Ship Speed Prediction Model Based on BP Neural Network

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