API Spec 15HP-1995《高压玻璃纤维管线管规范》的分析与介绍

本文介绍了高压玻璃纤维管线管规范的制定技术背景和主要特点,分析了前后两版的修订内容及原因.     

外汇高顺差形势下外汇统计监测应对策略探讨

在当前外汇收支统计监测中，资本项目和经常项目外汇收支相互融合，离岸外汇收支混入在岸外汇收支，个人跨境外汇收支流动增势迅猛。要加强外汇统计监测，就要加快设计和构建外汇信息统计监测体系，加强统计监测，建立各类监测分析的快捷反应机制。     

中资银行迎接外资银行全面竞争的策略研究

随着中国银行业市场不断扩大对外资银行的开放程度,在华外资银行已在市场份额、客户营销、业务经营及人才吸引等方面对中资银行的经营形成挑战。中资银行只有加快改革进程,进一步提升自身的竞争力,才能在2006年底中国银行业全面开放后从容应对外资银行的激烈竞争。本文结合当前中国银行业的改制过程,提出了中资银行的应对策略,即通过与外资银行的业务及股权合作来弥补自身不足,通过调整经营结构实现经营战略的转型,通过完善公司治理培育自身的核心竞争力,通过解决经营中的实际问题提高市场应变力,通过落实“以人为本”的理念切实提升人力资源价值。     

输送钢管的质量特性与驻厂监理的全过程控制

介绍了输送钢管的质量特点，提出了钢材及钢管质量控制方案和质量控制模式，将这种模式体现在输送铜管生产全过程质量控制和生产全过程驻厂监理实施中，保证了钢管质量和输送安全。     

西气东输工程用大口径X70级螺旋埋弧焊钢管的力学性能研究

以大量生产检验数据,对西气东输管线的力学性能进行了综合研究,并对其受包申格效应的影响情况进行了分析.     

Machine learning in individual claims reserving

Machine learning techniques make it feasible to calculate claims reserves on individual claims data. This paper illustrates how these techniques can be used by providing an explicit example in individual claims reserving.     

股权制衡、非国有股东委派董事与公司绩效

从公司治理层面完善国有控股企业的股权制衡是国企混合所有制改革的重点和难点,以往学者仅仅研究了股权制衡与公司绩效之间的关系,很少研究两者关系的作用路径和影响机理.因此,引入非国有股东委派董事这一概念,研究非国有股东委派董事在股权制衡与公司绩效之间发挥的中介效应.结果表明:股权制衡有利于公司绩效的提升,非国有股东委派董事在股权制衡与公司绩效两者之间发挥了中介效应.     

Marriage between credit cards and the Internet: Buying is just a click away!

This paper examines whether Internet access positively affects credit card balances. To that end, we compare the 2010 and 2013 Surveys of Consumer Finances, analyze the consistency of the results over time, and provide the rationale for any resulting differences. Using the censored techniques, our results indicate that Internet access has a positive effect on credit card balances, which suggests that consumers with Internet access are prone to higher balances compared to those without. The probability of carrying positive balances was larger in 2010 compared to 2013. Overall, the results suggest that, while the financial crisis might have contributed to higher balances in 2010, the economic recovery afterward seems to have eased the burden of credit card debt.     

Asking ‘Why’ in AI: Explainability of intelligent systems – perspectives and challenges

Recent rapid progress in machine learning (ML), particularly so‐called ‘deep learning’, has led to a resurgence in interest in explainability of artificial intelligence (AI) systems, reviving an area of research dating back to the 1970s. The aim of this article is to view current issues concerning ML‐based AI systems from the perspective of classical AI, showing that the fundamental problems are far from new, and arguing that elements of that earlier work offer routes to making progress towards explainable AI today.     

On the importance of the long-term seasonal component in day-ahead electricity price forecasting with NARX neural networks

Daily and weekly seasonalities are always taken into account in day-ahead electricity price forecasting, but the long-term seasonal component has long been believed to add unnecessary complexity, and hence, most studies have ignored it. The recent introduction of the Seasonal Component AutoRegressive (SCAR) modeling framework has changed this viewpoint. However, this framework is based on linear models estimated using ordinary least squares. This paper shows that considering non-linear autoregressive (NARX) neural network-type models with the same inputs as the corresponding SCAR-type models can lead to yet better performances. While individual Seasonal Component Artificial Neural Network (SCANN) models are generally worse than the corresponding SCAR-type structures, we provide empirical evidence that committee machines of SCANN networks can outperform the latter significantly.