论水利工程质量管理

本文分析了目前水利工程质量管理工作的状况和存在的问题,提出了施工中提高水利工程质量管理的方法,以正确处理项目建设过程中的各种关系,控制质量安全的关键点,杜绝"豆腐渣"工程,加强水利工程质量管理。     

中国政策性银行开展资本市场运作的路径选择

中国政策性银行作为中国支持国民经济的特殊职能部门,具有其自身的金融管理体制和经营体制特点,但与国外银行相比,存在诸多缺陷。中国政策性银行可利用扩充资本金规模、增加资金来源渠道和拓展资金运用方式等途径来开展资本市场运作,政策性银行开展资本市场运作应注意风险。     

烟草物流配送路线问题的实例研究

烟草物流配送问题可以抽象为车辆路径问题（VRP）,本文根据烟草物流配送的特点,设计相应的用于解决带时间窗的VRP问题的遗传算法.将该算法应用于具体的烟草物流配送案例中,编程实现并测试分析.最终验证了该方法在解决实际的大规模复杂问题的优越性.     

蚁群算法在物流配送路径优化问题上的应用

物流配送路径优化是现代物流配送服务的关键环节之一,需要一个快速而有效的求解算法,构建了物流配送路径优化问题的数学模型,并应用蚁群算法加以求解。在模拟试验基础上,得出了蚁群算法对物流配送路径优化问题十分有效的结论,探索出了一条高效求解物流配送路径优化问题的新途径。     

模拟植物生长算法在组合优化问题中的应用:研究进展

首先介绍了系统文献综述方法论与操作流程,从不同维度给出了文献分类标准;然后基于行政机构和出版来源分类标准,梳理了模拟植物生长算法(PGSA)的研究现状;接着分别针对电力系统、应急管理、设施选址、斯坦纳树、车间调度和旅行商等组合优化问题,对PGSA应用的代表性研究进行了综述,重点介绍了PGSA在若干领域的应用;最后从不同视角总结了已有研究成果,并指出PGSA解决组合优化问题的未来研究方向和具体内容。     

现代企业集团物资储备资金管理中的问题与对策

以国有大型企业重庆建设工业集团有限责任公司为例，对现代企业集团中储备资金管理存在的问题和对策进行了探讨。提出企业应加强储备资金管理，加速流动资金周转，完善自身管理，促进其经济效益的提高。     

The British low-wage sector and the employment prospects of the unemployed

Are low wages a way for the unemployed to switch to higher-paying jobs? Using data from the British Household Panel Survey, the labour market dynamics of unemployed, low-paid and higher-paid employed men are analysed. Moreover, the respective (un)employment duration and occupational skill level are accounted for. Results show that in general low wages significantly reduce the risk of future unemployment and increase the chances of ascending the salary ladder, especially in the case of long-term unemployment (>360 days). Furthermore, the occupational skill level has a substantial influence on the upward mobility of low-paid jobs: individuals working in the initial period in a low-paid and higher-skilled occupation have on average an 11 percentage points higher probability of entering higher pay compared to when working in a low-paid and low-skilled occupation.     

两型社会建设中建设用地集约利用问题探讨——以长株潭城市群为分析对象

集约利用建设用地是长株潭土地资源利用机制创新的关键。长株潭城市群应以交通建设为契机,推广人车人流节地模式、开发园区土地集约模式等成功做法,建立节约集约利用建设土地约束机制,加强建设用地控制标准建设评价工作和相关配套制度建设和改革,推动长株潭城市群建设用地的集约利用。     

A new multiscale decomposition ensemble approach for forecasting exchange rates

Due to the high complexity and strong nonlinearity nature of foreign exchange rates, how to forecast foreign exchange rate accurately is regarded as a challenging research topic. Therefore, developing highly accurate forecasting method is of great significance to investors and policy makers. A new multiscale decomposition ensemble approach to forecast foreign exchange rates is proposed in this paper. In the approach, the variational mode decomposition (VMD) method is utilized to divide foreign exchange rates into a finite number of subcomponents; the support vector neural network (SVNN) technique is used to model and forecast each subcomponent respectively; another SVNN technique is utilized to integrate the forecasting results of each subcomponent to generate the final forecast results. To verify the superiority of the proposed approach, four major exchange rates were chosen for model comparison and evaluation. The experimental results indicate that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach outperforms some other benchmarks in terms of forecasting accuracy and statistical tests. This demonstrates that our proposed VMD-SVNN-SVNN multiscale decomposition ensemble approach is promising for forecasting foreign exchange rates.