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—Community network discovery algorithm requires many different community network data to evaluate the algorithm performance. The data sets currently we use are from the reality. During the experiment, these data sets require a large number of pre-work, but the range of their parameters is relatively limited. This paper presents two random community network generation algorithms. They can respectively generate uniform community network and non-uniform community network. At the same time, this paper builds a visible platform. Our experiment results show that the algorithms for generating random community network are feasible and can be used as test data sets generation to test community discovery algorithm.

Resource allocation in grid environment is a complex undertaking due to the heterogeneity and dynamic nature aroused by wide area sharing. To address the heterogeneous and computationally intractable problem of resource allocation optimization in grid, this paper presents an allocation algorithm for parallel tasks based on particle swarm optimization. The heterogeneity of grid user is tackled by introducing a universal utility function. And that computational intractability is solved using iterative searching of particle swarm. Experimental results show that the proposed algorithm is convergent and performs better than genetic algorithm.

A class of stochastic nonlinear systems with unknown bounded parameters and zero dynamics are considered in this paper. By a series of coordinate changes, the original system is re-parameterized, which is suit for using the reduced-order observer and 1-dimension adaptive law to reduce the dynamic order of closed-loop system. In adaptive backstepping design, the quadratic and the quartic Lyapunov functions are presented simultaneously to reduce the static order of nonlinearities. It is shown that all the solutions of the closed-loop system are regulated to an arbitrarily small neighborhood of the origin in probability. Due to the order reduction of the controller, the design scheme in this paper has more practical values. A simulation example demonstrates the control scheme.

The paper mainly discusses the waiting time of the kidney transplant problem to establish a M/M/C queuing model based on hierarchy process; the first tier is the classification method of the patient types, the second is grade, allocation policy and other factors of kidney origin concerned in the method. Each tier is structured by one or more M/M/C queuing model. To solve the model, the system is adjusted to be optimized in the service. In this paper, a group of patients are analyzed, the results can be easily generalized to the whole kidney transplantation service system.

This paper focuses on the robust passive control problem of singular systems with uncertainties which is described by state space. Specifically the impulse of the singular systems is considered. We develop a linear matrix inequality (LMI) approach for designing the robust impulse passive state feedback controller and the output feedback controller such that the closed-loop system is quadratically stable, strictly passive and impulse free for all the admissible uncertainties. Finally, we testify the feasibility of the theorems by the numerical examples.