基于支持向量机的岩爆识别模型

岩爆的发生受多种因素的影响,这些因素关系错综复杂,以不同的特征和组合对岩爆产生综合影响,为科学、充分地利用现有的有限工程资料,本文从地下洞室围岩最大切向应力、岩石的单轴抗压强度和抗拉强度以及岩石冲击倾向指数四个主要因素出发,提出了基于支持向量机的岩爆识别模型,较好地解决小样本、非线性、高维数、局部极小点等的实际问题。     

遮掩式低回波金属支架的设计

本文推出了一种具有固定遮掩屏的低ＲＣＳ金属支架系统；介绍了其主要特点及设计方法；计算了该支架了多种数学模型的散射截面分布；试验研究了优化支架模型的散射特性。本文的计算及试验结果对于设计制做产用回波金属目标支架具有重要的参照价值。     

Metrological Support and Standards in the Design,Production, and Use of High-Load Weighing Machines in Russia

An analysis is presented on development, production, and use of high-capacity weighing machines in Russia in the last ten years. Aspects arising in type approval testing are considered for high-capacity weighing machines working over wide temperature ranges.     

基于移动端多天线系统的无线衰落信道模型

根据当前无线移动通信对多天线移动接收端性能仿真的要求，讨论并建立了适于空时信号处理的移动端矢量信道模型。通过分析无线移动信道特点。研究了影响接收信号幅度相位的诸多因素，建立了相应的数学模型。并对随机参数选取进行了探讨。其中考虑到移动端接收信号到达角扩散的特点，采用GBSB椭圆模型产生了适于移动端接收信号仿真的随机角度，改进了一种瑞利衰落生成算法。最后信道的数值仿真结果符合理论和经验。同时，通过TD-SCDMA系统链路级仿真，也证明了该信道模型的有效性。     

支持向量机的发展与应用

基于统计学习理论的支持向量机（SVM）是一种新型的机器学习方法，描述了SVM在模式识别和回归估计中的基本思想。在大训练样本情况下，用传统的方法求解SVM问题计算复杂，针对该问题探讨了一系列的SVM训练算法，并对其进行了比较。SVM由于其良好的泛化能力和全局最优性能．在模式识别、数据挖掘、非线性系统建模和控制等领域中展现出广泛的应用前景。     

Experiences with a parallel algorithm for data flow analysis

We have designed a family of parallel data flow analysis algorithms for execution on distributed-memory MIMD machines, based on general-purpose, hybrid algorithms for data flow analysis [Marlowe and Ryder 1990]. We exploit a natural partitioning of the hybrid algorithms and explore a static mapping, dynamic scheduling strategy. Alternative mapping-scheduling choices and refinements of the flow graph condensation used are discussed. Our parallel hybrid algorithm family is illustrated on Reaching Definitions, although parallel algorithms also exist for many interprocedural (e.g., Aliasing) and intraprocedural (e.g., Available Expressions) problems [Marlowe 1989]. We have implemented the parallel hybrid algorithm for Reaching Definitions on an Intel iPSC/2. Our empirical results suggest the practicality of parallel hybrid algorithms.An earlier version of this paper was presented at Supercomputing '90.The research reported here was supported, in part, by the New Jersey Commission on Science and Technology and the CAIP Center's Industrial Members, by Siemens Research Corporation and by National Science Foundation grant CCR-8920078.     

Ultrahigh-performance FFTs for the CRAY-2 and CRAY Y-MP supercomputers

In this paper a set of techniques for improving the performance of the fast Fourier transform (FFT) algorithm on modern vector-oriented supercomputers is presented. Single-processor FFT implementations based on these techniques are developed for the CRAY-2 and the CRAY Y-MP, and it is shown that they achieve higher performance than previously measured on these machines. The techniques include (1) using gather/scatter operations to maintain optimum length vectors throughout all stages of small-to medium-sized FFTs, (2) using efficient radix-8 and radix-16 inner loops, which allow a large number of vector loads/stores to be overlapped, and (3) prefetching twiddle factors as vectors so that on the CRAY-2 they can later be fetched from local memory in parallel with common memory accesses. Performance results for Fortran implementations using these techniques demonstrate that they are faster than Cray's library FFT routine CFFT2. The actual speedups obtained, which depend on the size of the FFT being computed and the supercomputer being used, range from about 5 to over 300%.     

Systematic modeling and model handling for manpower planning systems

The primary purpose of this paper is to show an efficient way of handling models and model data in a decision support system, in which it is usual to consider several variants of a model. The model data primarily consist of model-defining data, but the same approach may be used for the generated results as well. By efficient handling is meant the handling by the computer as well as by the user. For the user it is particularly important that new models can be conveniently defined as variants of existing models. The approach is introduced within the context of a decision support system for manpower planning based on Markov models. In the mean time the same approach has been used for the implementation of other decision support systems and has been found to be more generally applicable.