循环群的子群交子群并子群积的构造

给出循环群的子群交、子群并、子群积的构造,这是一些新的结果.

循环群的子群交与子群并的构造

本文给出循环群的子群交与子群并的构造。

循环群的子群交图的一些性质

设G是一个群,群G的子群交图,记为Γ(G),是以G的非平凡子群为顶点,两个不同顶点H,K相连当且仅当H∩K≠{1}.一个图Γ的Wiener指标是指图Γ中任意两点的距离之和,记为W(Γ),即W(Γ)=∑x,y∈Γd(x,y).该文主要研究循环群的子群交图的自同构群和Wiener指标,得到了任意n阶循环群的子群交图的Wiener指标计算公式以及当循环群的阶的素因子不超过3个时,Γ(G)的自同构群的结构.

构造循环群的子群交与子群并

本文结合群论课教学构造了循环群的子群交和子群并。

非交换子群的交较大的有限p群

在有限p群中引进另一个新的子群概念-IAk(G),即G的所有Ak子群的交.IAk(G)是G的特征子群,并且IA1(G)就是群G的所有非交换子群的交.对于pn阶群G而言,本文完全分类了|IA1(G)|分别为pn-2和pn-3的pn阶群G.

Particle swarm optimization for train schedule of Y-type train routing in urban rail transit

The train schedule usually includes train stop schedule,routing scheme and formation scheme.It is the basis of subway transportation.Combining the practical experience of transport organizations and the principle of the best match between transport capacity and passenger flow demand,taking the minimum value of passenger travel costs and corporation operating costs as the goal,considering the constraints of the maximum rail capacity,the minimum departure frequency and the maximum available electric multiple unit,an optimization model for city subway Y-type operation mode is constructed to determine the operation section of mainline as well as branch line and the train frequency of the Y-type operation mode.The particle swarm optimization(PSO)algorithm based on classification learning is used to solve the model,and the effectiveness of the model and algorithm is verified by a practical case.The results show that the length of branch line in Y-type operation affects the cost of waiting time of passengers significantly.

Particle Swarm Optimization based predictive control of Proton Exchange Membrane Fuel Cell (PEMFC)

Proton Exchange Membrane Fuel Cells (PEMFCs) are the main focus of their current development as power sources because they are capable of higher power density and faster start-up than other fuel cells. The humidification system and output performance of PEMFC stack are briefly analyzed. Predictive control of PEMFC based on Support Vector Regression Machine (SVRM) is presented and the SVRM is constructed. The processing plant is modelled on SVRM and the predictive control law is obtained by using Particle Swarm Optimization (PSO). The simulation and the results showed that the SVRM and the PSO re-ceding optimization applied to the PEMFC predictive control yielded good performance.

Quantum Phase Transitions and Dimerized Phases in Frustrated Spin Ladder

In this paper, we study the phase diagram of a frustrated spin ladder model by applying the bosonization technique and the density-matrix renormalization-group （DMRG） algorithm. Effect of the intra-ehain next-nearest- neighbor （NNN） super-exchange interaction is investigated in detail and the order parameters are calculated to detect the emergence of the dimerized phases. We find that the intra-chain NNN interaction plays a key role in inducing dimerized phases.

An immune-swarm intelligence based algorithm for deterministic coverage problems of wireless sensor networks

A novel immune-swarm intelligence (ISI) based algorithm for solving the deterministic coverage problems of wireless sensor networks was presented.It makes full use of information sharing and retains diversity from the principle of particle swarm optimization (PSO) and artificial immune system (AIS).The algorithm was analyzed in detail and proper swarm size,evolving generations,gene-exchange individual order,and gene-exchange proportion in molecule were obtained for better algorithm performances.According to the test results,the appropriate parameters are about 50 swarm individuals,over 3 000 evolving generations,20%-25% gene-exchange proportion in molecule with gene-exchange taking place between better fitness affinity individuals.The algorithm is practical and effective in maximizing the coverage probability with given number of sensors and minimizing sensor numbers with required coverage probability in sensor placement.It can reach a better result quickly,especially with the proper calculation parameters.

Ultra-fast Maize （Zea mays L.） Hybrid Growth Response to Plant Population Density

Current arable land and increasing food demand necessitates the practice of double and multiple cropping systems with inclusion of ultra-fast maize hybrids, which are characterized by smaller size, fewer leaves per plant, lower leaf area and fewer self-shading problems, under irrigation. In this context, a field experiment was conducted for two successive cropping seasons 2008/2009 to 2009/2010 at Kenilworth Experimental Station to evaluate the effect of row spacings and plant density on growth. Three row spacing （0.225, 0.45 and 0.90 m） and five plant densities （5, 7.5, 10, 12.5 and 15 plants m^-2） were used. Treatments were combined in a factorial combination and laid out in a completely randomized design with replications consisting of five single plants randomly selected from each treatment for destructive sampling. Growth factors reacted differently to row spacing by plant density. At crop establishment, growth indicators were not significantly affected by either main effects or a combination thereof. However, at the end of the vegetative phase, almost all growth indicators reached a maximum and were significantly affected by treatment interactions. Growth analysis showed that there was an interaction effect of row spacing by plant density on plant height, dry matter （DM） accumulation, leaf area index （LAI）, crop growth rate （CGR） and net assimilation rate （NAR） of maize. Therefore, the current investigation demonstrated that a row spacing of 0.45 m or 0.90 m with a plant density of 10 plants m^-2 was optimum for the selected ultra-fast maize hybrid under irrigation.

Linear Operators Strongly Preserving M-P Inverses of Matrices over Some Antinegative Commutative Semirings

Let S be an antinegative commutative semiring having no zero divisions or finite general Boolean Algebra and μ(S) the set of n×n matrices over S. In this paper we characterize the structure of the senigroup n,(S) of linear operators on μn,(S) that strongly preserve the M-P inverses of matrices.

Finite p-groups with a minimal non-abelian subgroup of index p(Ⅱ)

We classify completely three-generator finite p-groups G such that Ф(G)≤Z(G)and|G′|≤p2.This paper is a part of the classification of finite p-groups with a minimal non-abelian subgroup of index p,and solve partly a problem proposed by Berkovich.

Finite p-groups with a minimal non-abelian subgroup of index p(Ⅲ)

This paper finishes the classification of three-generator finite p-groups G such that Φ(G) Z(G).This paper is a part of classification of finite p-groups with a minimal non-abelian subgroup of index p, and partly solves a problem proposed by Berkovich(2008).

McKay quivers and absolute n-complete algebras

In this paper,we show that the McKay quiver of a finite subgroup of a general linear group is a regular covering of the McKay quiver of its intersection with the special linear group.Using this and our results on "returning arrows" in McKay quiver,we give an algorithm to construct the McKay quiver of a finite abelian group.Using this construction,we show how the cone and cylinder of an(n-1)-Auslander absolute n-complete algebra are truncated from the McKay quivers of abelian groups.

A scheduling method based on a hybrid genetic particle swarm algorithm for multifunction phased array radar

A hybrid optimization approach combining a particle swarm algorithm, a genetic algorithm, and a heuristic interleaving algorithm is proposed for scheduling tasks in the multifunction phased array radar. By optimizing parameters using chaos theory, designing the dynamic inertia weight for the particle swarm algorithm as well as introducing crossover operation and mutation operation of the genetic algorithm, both the efficiency and exploration ability of the hybrid algorithm are improved. Under the frame of the intelligence algorithm, the heuristic interleaving scheduling algorithm is presented to further use the time resource of the task waiting duration. A large-scale simulation demonstrates that the proposed algorithm is more robust and efficient than existing algorithms.

A Lower Bound on Unknotting Number

In this paper the authors use a modified Wirtinger presentation to give a lower bound on the unknotting number of a knot in S^3.

Wiener-Hopf Operators on Discrete Abelian Groups

The groupoid approach to study Wiener-Hopf operators on discrete abelian groups is realized.

Analytical and Numerical Studies of Quantum Plateau State in One Alternating Heisenberg Chain

By using the coupled duster method and the numerical density matrix renormalization group method, we investigate the properties of the quantum plateau state in an alternating Heisenberg spin chain. In the absence of a magnetic field, the results obtained from the coupled cluster method and density matrix renormalization group method both show that the ground state of the aiternating chain is a gapped dimerized state when the parameter a exceeds a critical point ac. The value of the critical points can be determined precisely by a detailed investigation of the behavior of the spin gap. The system therefore possesses an m = 0 plateau state in the presence of a magnetic field When a 〉 ac. In addition to the m = 0 plateau state, the results of density matrix renormaiization group indicate that there is an m = 1/4 plateau state that occurs between two critical fields in the alternating chain if a 〉 1. The mechanism for the m = 1/4 plateau state and the critical behavior of the magnetization as one approaches this plateau state are also discussed.