一种基于群件Notes的ODSS-CE设计与实现

诗集了面向并行工程的组织决策支持系统的概念模型，描述了群件Ｎotes适合于ＯＤＳＳ－ＣＥ开发的突出特性，在此基础上，阐述了基于群件Notes的ＯＤＳＳ－ＣＥ系统进行简要的总结。     

基于可信度约束的序列模式发现研究

结合可信度约束,提出解决序列模式发现研究的算法,并分别对以下两种方案展开研究.I:先寻找所有满足最小支持度的最大高频序列,后计算最大高频序列的各阶可信度.II:先计算最大高频序列的各阶可信度,后寻找所有满足最小支持度的最大高频序列。     

曲杏壳制备炭膜支撑体(英文)

以杏壳为原料,通过碳化法制备了碳膜支撑体,利用泡压法表征了支撑体的孔径分布。对杏壳原料进行预碳化、粉碎、筛分得到碳粉,将碳粉和添加剂混匀挤出成型得到支撑体原膜,经干燥、碳化得到无缺陷碳膜支撑体。实验结果表明,粘结剂用量增加会导致支撑体平均孔径变小,纯水能量减小。随着原料颗粒的减小支撑体平均孔径减小,纯水能量下降。     

EIS在高校高层管理中的应用

从支持高层管理者信息获取 ,提高高层管理者有效性、对高层管理者决策过程支持三个方面 ,分析了EIS在辅助高等院校高层管理者工作中的作用     

机械传动原理方案设计及其决策支持系统的构造

将专家系统技术与ＣＡＤ技术、模糊理论以及决策支持技术等集为一体，构造了“机械传动系统原理方案设计及其决策支持系统”，较为成功地解决了“机械传动原理方案设计及其决策”这一复杂问题。本文主要介绍了系统的基本组成、结构及开发方式。     

综采工作面收尾铺网新工艺的探讨

就综采工作面收尾铺网新工艺进行了分析,对锚杆支护所用时间和抽插梁所用时间进行了预算。     

Advances in SVM-Based System Using GMM Super Vectors for Text-Independent Speaker Verification

For text-independent speaker verification, the Gaussian mixture model （GMM） using a universal background model strategy and the GMM using support vector machines are the two most commonly used methodologies. Recently, a new SVM-based speaker verification method using GMM super vectors has been proposed. This paper describes the construction of a new speaker verification system and investigates the use of nuisance attribute projection and test normalization to further enhance performance. Experiments were conducted on the core test of the 2006 NIST speaker recognition evaluation corpus. The experimental results indicate that an SVM-based speaker verification system using GMM super vectors can achieve appealing performance. With the use of nuisance attribute projection and test normalization, the system performance can be significantly improved, with improvements in the equal error rate from 7.78% to 4.92% and detection cost function from 0.0376 to 0.0251.     

Traditional versus novel forecasting techniques: how much do we gain?

This article applies two novel techniques to forecast the value of US manufacturing shipments over the period 1956–2000: wavelets and support vector machines (SVM). Wavelets have become increasingly popular in the fields of economics and finance in recent years, whereas SVM has emerged as a more user‐friendly alternative to artificial neural networks. These two methodologies are compared with two well‐known time series techniques: multiplicative seasonal autoregressive integrated moving average (ARIMA) and unobserved components (UC). Based on forecasting accuracy and encompassing tests, and forecasting combination, we conclude that UC and ARIMA generally outperform wavelets and SVM. However, in some cases the latter provide valuable forecasting information that it is not contained in the former. Copyright © 2008 John Wiley & Sons, Ltd.     

深基坑工程风险评估的决策支持系统

对深基坑工程风险评估进行了讨论，分析决策支持系统的逻辑结构，认为将决策支持技术应用于深基坑工程风险评估，可以解决决策方案模糊性、决策目标冲突性以及结构不良等问题，提高科学决策水平。