武定县走马地矿段铜矿成矿条件及找矿方向

武定地区区域矿产资源极丰富,矿区经过40多年的勘查,共发现各类矿点百余个,综合研究表明,武定县平地~左所铜矿床类型以"东川式"铜矿最重要,分布在金钟罩、鸡冠山、油基田、周家箐、走马地、黄龙河、牛德庄等地;次为稀矿山式,主要在蒿枝地,走马地等地。"东川式"铜矿:落雪组底部过渡层,"稀矿山式"铁铜矿:因民组下部,同生断裂旁侧,古火山机构中的火山洼地,火山旋回的中上部,富含Na2O的细碧角斑岩系,硅质岩、萤石岩、钠长岩等喷流岩以及黑云母、绿泥石火山凝灰岩的分布区。     

全站仪竖井平面联系测量的方法及精度分析

随着测绘科学技术的不断发展,全站仪测量精度的不断提高,它已逐步取代了经纬仪在矿山测量应用中的主导地位。本文介绍了利用全站仪进行竖井联系测量的方法,并结合实例,重点对此方法的测量结果的精度进行了分析。     

浅谈选煤厂建设投资估算影响因素及改进措施

本文对选煤厂建设工程投资估算中影响准确性的因素进行了分析,并结合BP神经网络理论基于Matlab软件对选煤厂带式输送机及栈桥单位工程进行了数值模拟,通过对比数值模拟结果与概算指标估算结果,详细阐述了可以提高选煤厂建设工程投资估算准确性的几点建议。     

浅析车削用量与实际生产的联系及车削的发展趋势

阐述了车削用量与实际生产的联系,提供了部分在保证机械产品性能和质量的基础上提高生产率和缩减成本的可靠性解决办法。在仔细分析了当前机加工行业的情况下,预测了车削加工的发展方向。     

建设工程预算准确性综合评价

在项目前期，准确的建设工程预算是投资者据以作出正确决策的基础。本文分析了造成建设工程预算偏差的因素，建立了预算准确性综合评价指标体系，并对工程预算的准确性进行了评估和分析。     

基于K-means算法的企业服务创新方向选择研究

企业在进行服务创新过程中,首先需要考虑到企业发展战略与其自身优势能力的匹配性,结合这两点来确定服务创新的发展方向。本文研究了企业基于自身已有的优势能力,运用K-means算法建立了企业服务创新战略方向选择模型,识别并确定了企业服务创新战略方向,由此得出企业进行服务创新时的最佳服务定位策略。     

Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task

We conducted laboratory experiments for analyzing the accuracy of three structured approaches (nominal groups, Delphi, and prediction markets) relative to traditional face-to-face meetings (FTF). We recruited 227 participants (11 groups per method) who were required to solve a quantitative judgment task that did not involve distributed knowledge. This task consisted of ten factual questions, which required percentage estimates. While we did not find statistically significant differences in accuracy between the four methods overall, the results differed somewhat at the individual question level. Delphi was as accurate as FTF for eight questions and outperformed FTF for two questions. By comparison, prediction markets did not outperform FTF for any of the questions and were inferior for three questions. The relative performances of nominal groups and FTF were mixed and the differences were small. We also compared the results from the three structured approaches to prior individual estimates and staticized groups. The three structured approaches were more accurate than participants’ prior individual estimates. Delphi was also more accurate than staticized groups. Nominal groups and prediction markets provided little additional value relative to a simple average of the forecasts. In addition, we examined participants’ perceptions of the group and the group process. The participants rated personal communications more favorably than computer-mediated interactions. The group interactions in FTF and nominal groups were perceived as being highly cooperative and effective. Prediction markets were rated least favourably: prediction market participants were least satisfied with the group process and perceived their method as the most difficult.     

A large factor model for forecasting macroeconomic variables in South Africa

This paper uses large Factor Models (FMs), which accommodate a large cross-section of macroeconomic time series for forecasting the per capita growth rate, inflation, and the nominal short-term interest rate for the South African economy. The FMs used in this study contain 267 quarterly series observed over the period 1980Q1-2006Q4. The results, based on the RMSEs of one- to four-quarter-ahead out-of-sample forecasts from 2001Q1 to 2006Q4, indicate that the FMs tend to outperform alternative models such as an unrestricted VAR, Bayesian VARs (BVARs) and a typical New Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model in forecasting the three variables under consideration, hence indicating the blessings of dimensionality.     

中小物流企业未来发展方向——虚拟物流

虚拟物流企业是我国物流企业,特别是中小物流企业未来的发展趋势。采取动态联盟的方式建立的虚拟物流企业可以形成规模经济,节约物流资源,达到社会效益的最大化;并指出了构建虚拟物流企业中存在的一些问题。     

A note on forecasting international tourism demand in Spain

This paper considers the extent to which price and income proxy variables help in forecasting tourist demand in Spain. Contrary to some recent studies, we found that the inputs' contribution in terms of fitting and forecasting is nil when compared with alternative univariate models. Whether these findings are the results of the restrictions embedded in building the proxy inputs or in a poor specification of the dynamics of these models remains to be seen. We also contend that when dealing with medium, long-term forecasting comparisons, the use of the traditional aggregate accuracy measures like RMSE and MAPE help very little in discriminating among competing models. In these situations, predicted annual growth rates may be a better alternative.