Membrane computing
Membrane computing
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DOI：
10.1080/17445760.2019.1659260
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发表时间：
2019-08
期刊：
影响因子：
--
通讯作者：
Gexiang Zhang
中科院分区：
文献类型：
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作者：
Gexiang Zhang
本特刊收录了第七届亚洲膜计算会议（ACMC 2018）的论文选集。由国际膜计算学会（IMCS）和新西兰奥克兰大学计算机科学系主办的ACMC 2018于2018年12月10日至14日在新西兰奥克兰大学成功举行。离散数学和理论计算机科学中心赞助了ACMC 2018，并出版了会议的预文集。膜计算作为自然计算的一个分支，于1998年由paulunb[1]教授发起，是一种充满活力的计算范式，其动机是活细胞的结构和功能，以及细胞在组织、器官、菌落（包括神经细胞）等群体中的合作方式，因此也包括大脑[2,3]。计算模型称为膜系统或膜系统。在过去的20年里，在计算能力、计算效率、机器人控制器、建模生态系统和实现等广泛的主题[4,5]中取得了大量的理论成果和实际应用[6-9]。更重要的是，膜计算界取得了一系列具有里程碑意义的成就：成立了国际膜计算学会（IMCS），组织了四个定期会议/研讨会，即ECMC， ACMC， BWMC和CWMC，以及两份定期出版物《膜计算杂志》（JMC）和《膜计算公报》（IMCS Bulletin）的孕育和诞生。ACMC是膜计算领域的旗舰会议之一，旨在为从事膜计算及相关领域的研究人员，特别是来自亚太地区的研究人员提供一个高水平的国际论坛。前六届展会分别在武汉（中国，2012）、成都（中国，2013）、哥印拜陀（印度，2014）、安徽（中国，2015）、Bangi（马来西亚，2016）和成都（中国，2017）成功举办。因此，国际非常规计算杂志（第9卷（5-6），2013年），罗马尼亚信息科学与技术杂志（第17卷(1)，2014年），计算与理论纳米科学杂志（第12卷(7)，2015年），自然计算（第15卷(4)，2016年），计算与理论纳米科学杂志（第13卷(6)，2016年），罗马尼亚信息科学与技术杂志（第20卷(1)，2017年），优化杂志（第2017,2017年），理论计算机科学（卷736,2018）和基础信息（卷164(2-3),2019）。这期的四篇论文主要关注膜计算的应用，包括脉冲神经P系统的故障诊断、图像分割、智能决策P系统的行人行为模拟和类组织P系统优化的K-means算法。第一篇论文由Sun等人提出了一种基于电突触传递的脉冲神经P系统（SNP系统），用于分布式代配电网的故障定位。在引入的模型中，在原有的SNP系统定义中加入了一些新的元素，如新的突触、双向模型、两种类型的神经元和取消轴突的延迟。讨论了基于电突触传递的SNP系统的故障定位模型和推理算法，该模型和推理具有精度高、计算量少、简单直观等特点。Liu等人的第二篇论文介绍了一种基于改进混合粒子群优化（PSO）的图像分割方法。更新基于全局优化、区域平衡和压缩因子相结合的粒子速度，提高粒子的搜索能力和改进粒子群的优化性能。
This special issue contains a selection of papers from the Seventh Asian Conference on Membrane Computing (ACMC 2018). ACMC 2018 was successfully held at the University of Auckland, New Zealand, 10–14 December 2018, which was organised by the International Membrane Computing Society (IMCS) and the Department of Computer Science at the University of Auckland, New Zealand. The Centre for DiscreteMathematics and Theoretical Computer Science sponsored ACMC 2018, which published the pre-proceedings of the conference. Membrane computing, initiated by Prof. Păun [1] in 1998 as a branch of natural computing, is a vigorous computational paradigmmotivatedby the structure and functioningof the living cells, and from the ways the cells cooperate in populations like tissues, organs, colonies, including neural cells, hence also thebrain [2, 3]. The computationalmodels are called eithermembrane systemsor P systems. In the past 20 years, a lot of theoretical results and real-life applications have been achieved in a broad range of topics [4, 5] like computing power, computing efficiency, robots controllers, modelling ecosystems and implementation [6–9].What ismore important,membrane computing community has succeeded to achieve a set of landmarking successes: the establishment of International Membrane Computing Society (IMCS), the organisation of four regular conference/workshop events, namely ECMC, ACMC, BWMC, and CWMC, and the gestation and birth of two periodic publications, Journal of Membrane Computing (JMC) and IMCS Bulletin. ACMC is one of the flagship conferences on membrane computing, aiming to provide a high-level international forum for researchers working in membrane computing and related areas, especially for those from the Asia-Pacific region. The six previous editions had successfully been held in Wuhan (China, 2012), Chengdu (China, 2013), Coimbatore (India, 2014), Anhui (China, 2015), Bangi (Malaysia, 2016) andChengdu (China, 2017), respectively. Accordingly, special issueswere edited in International Journal of Unconventional Computing (Vol. 9(5–6), 2013), Romanian Journal of Information Science and Technology (Vol. 17(1), 2014), Journal of Computational and Theoretical Nanoscience (Vol. 12(7), 2015), Natural Computing (Vol. 15(4), 2016), Journal of Computational and Theoretical Nanoscience (Vol. 13(6), 2016), Romanian Journal of Information Science and Technology (Vol. 20(1), 2017), Journal of Optimization (Vol. 2017, 2017), Theoretical Computer Science (Vol. 736, 2018), and Fundamenta Informaticae (Vol. 164(2–3), 2019). The four papers in this issue mainly focus on the applications of membrane computing, including fault diagnosis with spiking neural P systems, image segmentation, pedestrian behaviours simulation of intelligence decision P systems and K-means algorithm optimised by tissue-like P systems. The first paper, by Sun et al., presented an electrical synaptic transmission-based Spiking Neural P system (SNP system) for fault location of distribution network with distributed generations. In the introduced model, some new elements are added into the original definition of SNP systems, such as new synapses, bidirectional model, two types of neurons and cancelling the delay of axon. The fault location model and reasoning algorithm of the electrical synaptic transmission-based SNP system are discussed with respect to high accuracy, less computation, simple and intuitive model and reasoning. The secondpaper, by Liu et al., introducedanapproach for image segmentationbasedon improved hybrid particle swarm optimisation (PSO). The particle velocity based on the combination of global optimisation, region equilibrium and compression factor are updated to improve the search ability of the particle and optimisation performance of the improved PSO.