Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems ...Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.展开更多
This paper presents an intelligent technique to fault diagnosis of power transformers dissolved and free gas analysis (DGA). Fuzzy Reasoning Spiking neural P systems (FRSN P systems) as a membrane computing with distr...This paper presents an intelligent technique to fault diagnosis of power transformers dissolved and free gas analysis (DGA). Fuzzy Reasoning Spiking neural P systems (FRSN P systems) as a membrane computing with distributed parallel computing model is powerful and suitable graphical approach model in fuzzy diagnosis knowledge. In a sense this feature is required for establishing the power transformers faults identifications and capturing knowledge implicitly during the learning stage, using linguistic variables, membership functions with “low”, “medium”, and “high” descriptions for each gas signature, and inference rule base. Membership functions are used to translate judgments into numerical expression by fuzzy numbers. The performance method is analyzed in terms for four gas ratio (IEC 60599) signature as input data of FRSN P systems. Test case results evaluate that the proposals method for power transformer fault diagnosis can significantly improve the diagnosis accuracy power transformer.展开更多
Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as ...Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as the computing power of reversible SN P systems. Reversible SN P systems are proved to have Turing creativity, that is, they can compute any recursively enumerable set of non-negative integers by simulating universal reversible register machine.展开更多
为了解决区域综合能源系统(regional integrated energy system,RIES)实际应用中难以确定最优供能路径的问题,提出一种区域综合能源下带时间约束的标注模糊有色脉冲神经膜系统(tagged fuzzy colored spiking neural P system with time ...为了解决区域综合能源系统(regional integrated energy system,RIES)实际应用中难以确定最优供能路径的问题,提出一种区域综合能源下带时间约束的标注模糊有色脉冲神经膜系统(tagged fuzzy colored spiking neural P system with time sequence constraint,tscTFCSNPS)供能路径寻优推理模型,以研究系统在参变量相同条件下,不同供能路径运行的优劣情况。首先,在满足负荷需求的情况下,使用RIES-tscTFCSNPS模型选出所有符合约束条件的供能路径;然后,将运行成本和CO_(2)排放量两个目标函数进行加权组合,建立一个新的目标函数,并使用遗传算法对其进行优化求解;最后,通过分析优化结果,得到在不同场景下的最优供能方案。以某综合园区为例,设置4种不同场景进行实验分析,仿真结果表明所提模型有效提高了系统的经济性,并降低了CO_(2)的排放量。展开更多
考虑在一种新的生物计算装置(即脉冲神经膜系统)上处理任意两个自然数的乘积问题.首先给出了具有单个输入神经元的脉冲神经膜系统,它可以求解n-addition问题(即n个自然数的求和);其次,构造了一族脉冲神经膜系统,使该族中的每个系统可以...考虑在一种新的生物计算装置(即脉冲神经膜系统)上处理任意两个自然数的乘积问题.首先给出了具有单个输入神经元的脉冲神经膜系统,它可以求解n-addition问题(即n个自然数的求和);其次,构造了一族脉冲神经膜系统,使该族中的每个系统可以求解给定二进制位长度的任意两个自然数的乘积.文中解决了Miguel A Gutirrez-Naranjo和Alberto Leporati提出的一个公开问题.展开更多
基金supported by the National Natural Science Foundation of China(6103300361100145+1 种基金91130034)the China Postdoctoral Science Foundation(2014M550389)
文摘Spiking neural P systems with anti-spikes （ASN P systems） are variant forms of spiking neural P systems, which are inspired by inhibitory impulses/spikes or inhibitory synapses. The typical feature of ASN P systems is when a neuron contains both spikes and anti-spikes, spikes and anti-spikes wil immediately annihilate each other in a maximal way. In this paper, a restricted variant of ASN P systems, cal ed ASN P systems without anni-hilating priority, is considered, where the annihilating rule is used as the standard rule, i.e., it is not obligatory to use in the neuron associated with both spikes and anti-spikes. If the annihilating rule is used in a neuron, the annihilation wil consume one time unit. As a result, such systems using two categories of spiking rules （identified by （a, a） and （a,a^-）） can achieve Turing completeness as number accepting devices.
文摘This paper presents an intelligent technique to fault diagnosis of power transformers dissolved and free gas analysis (DGA). Fuzzy Reasoning Spiking neural P systems (FRSN P systems) as a membrane computing with distributed parallel computing model is powerful and suitable graphical approach model in fuzzy diagnosis knowledge. In a sense this feature is required for establishing the power transformers faults identifications and capturing knowledge implicitly during the learning stage, using linguistic variables, membership functions with “low”, “medium”, and “high” descriptions for each gas signature, and inference rule base. Membership functions are used to translate judgments into numerical expression by fuzzy numbers. The performance method is analyzed in terms for four gas ratio (IEC 60599) signature as input data of FRSN P systems. Test case results evaluate that the proposals method for power transformer fault diagnosis can significantly improve the diagnosis accuracy power transformer.
基金This work was supported by the National Natural Science Foundation of China （Grant Nos. 61033003, 91130034, 61170183, 61100145, 61272071）, PhD Programs Foundation of Ministry of Education of China （20100142110072, 20120142130008）, National Science Foundation of Hubei Province （2011CDA027）, and Scientific Research Foundation for the Excellent Middle-Aged and Youth Scientists of Shandong Province of China （BS2011SW025）.
文摘Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as the computing power of reversible SN P systems. Reversible SN P systems are proved to have Turing creativity, that is, they can compute any recursively enumerable set of non-negative integers by simulating universal reversible register machine.
文摘为了解决区域综合能源系统(regional integrated energy system,RIES)实际应用中难以确定最优供能路径的问题,提出一种区域综合能源下带时间约束的标注模糊有色脉冲神经膜系统(tagged fuzzy colored spiking neural P system with time sequence constraint,tscTFCSNPS)供能路径寻优推理模型,以研究系统在参变量相同条件下,不同供能路径运行的优劣情况。首先,在满足负荷需求的情况下,使用RIES-tscTFCSNPS模型选出所有符合约束条件的供能路径;然后,将运行成本和CO_(2)排放量两个目标函数进行加权组合,建立一个新的目标函数,并使用遗传算法对其进行优化求解;最后,通过分析优化结果,得到在不同场景下的最优供能方案。以某综合园区为例,设置4种不同场景进行实验分析,仿真结果表明所提模型有效提高了系统的经济性,并降低了CO_(2)的排放量。
文摘考虑在一种新的生物计算装置(即脉冲神经膜系统)上处理任意两个自然数的乘积问题.首先给出了具有单个输入神经元的脉冲神经膜系统,它可以求解n-addition问题(即n个自然数的求和);其次,构造了一族脉冲神经膜系统,使该族中的每个系统可以求解给定二进制位长度的任意两个自然数的乘积.文中解决了Miguel A Gutirrez-Naranjo和Alberto Leporati提出的一个公开问题.
