不常用备件基于AHP的ABC分类模型

分析了传统ABC分类法在不常用备件库存分类中的应用,针对传统ABC分类法的缺陷.文章应用基于AHP的ABC分类方法,将备件单价、采购提前期、年采购费用、年使用次数、备件类型、重要性等级作为分类准则,对每一备件相对准则层进行ABC分类,然后结合准则层对目标层的权重计算备件组合权重并再次进行ABC分类,建立了不常用备件基于...     

基于模糊理论的Ad Hoc网络可信性研究

在分析Adhoc网络的通信能力的基础上,确定网络可信度影响因子,并采用模糊层次分析法计算可信度影响因子的权重值.提出了基于模糊理论的AdHoc网络可信性评判模型.该模型对Adhoc网络进行了单因素评判和综合评判,并通过实例运算证明了模型的科学性与合理性.     

飞行器姿态控制系统中的一种计算机仿真研究

针对飞行器姿态控制系统的参数时变性和不确定性干扰等特点,本文给出了一种基于Ackermann规则的滑模变结构控制器,并在设计滑模面时,引入积分项来消除干扰等因素给系统带来的稳态误差;为消除抖动,在控制器中引入模糊系统来实现去抖;同时设计灰色补偿控制项来抵消不确定项对系统造成的不利影响。最后进行了计算机数字仿真,结果表明本文所设计的控制器具有很好的效果。     

Innovative product design based on customer requirement weight calculation model

In the processes of product innovation and design, it is important for the designers to find and capture customer's focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.     

扩频通信技术及其应用

扩频通信是现代通信系统中新的通信方式,它具有较强的抗干扰、抗衰落和抗多径性能,频谱利用率高的特点。扩展频谱通信是一种将信息的带宽扩展很多倍进行通信的技术,近年来在现代科技的许多领域中,应用非常广泛。着重叙述了扩频通信的工作原理、特点、及其发展应用。     

Saturation in multivariate simultaneous approximation

In this paper we present a new result on the saturation of sequences of linear operators in a multivariate and simultaneous setting. Specifically, a small o saturation result is obtained for the partial derivatives of the classical Bernstein bivariate operators on the unit simplex. Solutions of boundary value problems for certain partial differential equations of elliptic type play an important role.     

The voting analytic hierarchy process method for discriminating among efficient decision making units in data envelopment analysis

Making optimal use of available resources has always been of interest to humankind, and different approaches have been used in an attempt to make maximum use of existing resources. Limitations of capital, manpower, energy, etc., have led managers to seek ways for optimally using such resources. In fact, being informed of the performance of the units under the supervision of a manager is the most important task with regard to making sensible decisions for managing them. Data envelopment analysis (DEA) suggests an appropriate method for evaluating the efficiency of homogeneous units with multiple inputs and multiple outputs. DEA models classify decision making units (DMUs) into efficient and inefficient ones. However, in most cases, managers and researchers are interested in ranking the units and selecting the best DMU. Various scientific models have been proposed by researchers for ranking DMUs. Each of these models has some weakness(es), which makes it difficult to select the appropriate ranking model. This paper presents a method for ranking efficient DMUs by the voting analytic hierarchy process (VAHP). The paper reviews some ranking models in DEA and discusses their strengths and weaknesses. Then, we provide the method for ranking efficient DMUs by VAHP. Finally we give an example to illustrate our approach and then the new method is employed to rank efficient units in a real world problem.     

基于模糊层次分析法的计算机网络安全评价

根据计算机网络的特点及网络安全涉及的因素,建立计算机网络安全评价的层次结构模型,运用基于三角模糊数的模糊层次分析法实现对网络安全的综合量化评价。实例的计算结果表明模糊层次分析法适用于定性判断的量化综合,它为计算机网络安全评价提供了一种探索性方法。     

Mean square asymptotic behavior of stochastic neural networks with infinitely distributed delays

In this paper, according to classic -matrix method, integral–differential inequality technique and Ito formula, we study asymptotic behavior in mean square sense of stochastic neural networks with infinitely distributed delays by establishing a generalized Halanay inequality. This is a new means for investigating asymptotic behavior of stochastic differential equation. Some useful results are derived. Especially, our methods can be extended to research p-moment asymptotic behavior easily. At last, example and simulations demonstrate the power of our methods.