In this paper,we consider restricted edge-connectivity λ′ of Kautz digraph K(d,n) and Kautz undirected graph UK(d,n),which are two classes of important network models.
This paper examines the use of mixed P2P network models for the distribution of resources in the network for metadata search method and the introduction of a new generation of P2P Sun JXTA as a system to achieve development platforms.
On the basis of analyzing two kinds of assembly model structures, the hierarchical tree shaped model and the relationship net model, and in accordance with the requirements of assembly sequence planning, the product's assembly information model that satisfied the assembly sequence planning was established by applying the object orientation method, and the corresponding data structure was put forward, thus provided reasonable information frame of product for the sequence planning of virtual assembly.
Experimental results indicate that the disadvantage of the high nonlinear model of tool wear,which depicts cutting conditions by a multi-linear equation,is overcome,the nonlinearity essence of correlative factors is exactly explained and the tool wear extent in different cutting conditions can be calculated by using the net model of cutting tool wear.
A network model was developed for dynamic multicast traffic grooming with resource constraints and an algorithm that can provide quality of service (QoS) was proposed.
An improved susceptible-infected-susceptible (SIS) model in the local-world evolving network model is presented to study the epidemic spreading behavior with time delay, which is added into the infected phase.
Two typical delay regimes, i.e., uniform and degree-dependent delays are incorporated into the SIS epidemic model to investigate the epidemic infection processes in the local-world network model.
For the RBF neural network model, which is more effective for monitoring weld quality than the others, the average error validated is 2.88% and the maximal error validated is under 10%.
At the same time, linear regression, nonlinear regression and radial basis function (RBF) neural network models are set up to evaluate weld quality between the selected parameters and tensile-shear strength.
The utilization of the Petri net model realized the environment where the trainee can behave freely, and also made it possible to equip the system with the function of showing the next action of the trainee whenever he wants.
This paper aims at exploring computational properties of dynamic processes in neural systems, studying their mathematical formulation, and applying the results to artificial neural network modeling.