Impediments to the enforcement of youth access laws

OBJECTIVE: To recognise obstacles to the implementation of the effective enforcement of tobacco sales laws and to identify measures that could be taken to overcome these obstacles. DESIGN: Interviews were conducted with health department officials in Massachusetts communities to determine why their efforts to prevent illegal sales of tobacco to minors had been only partially successful. SETTING: Urban, suburban, and rural communities in Massachusetts, USA. RESULTS: Organisational problems, court challenges to citations, budgetary threats, and political pressure all combined to reduce the frequency of enforcement inspections to half the intended rate. Political pressure resulted in the exclusion of older youths from compliance tests, further undermining enforcement efficacy. CONCLUSIONS: Suggestions for addressing the problems include obtaining support from the community, keeping elected and court officials informed about plans for merchant education and law enforcement, using efficient enforcement protocols, setting merchant compliance goals, and advising the public and government officials about progress towards those goals, using older youths to make purchase attempts, and testing all merchants frequently.     

考虑多时间尺度电力交易市场下的配电网最大供电能力模型

为研究多时间尺度电力交易下配电网的最大供电能力,首先从中长期+现货交易模式入手,将多时间尺度下的交易转变为单时间尺度交易;其次,建立考虑多时间尺度电力交易市场下的配电网最大供电能力双层模型,并运用原始对偶内点法和改进的重复潮流算法求解;最后通过算例,对中长期+现货交易模式下的配电网最大供电能力进行计算分析。结果表明,考虑多尺度电力交易下的配电网最大供电能力得到了提升,且随着现货交易的深入,提升得越明显。研究成果可为电力市场环境下提升配电网最大供电能力提供参考。     

基于优化BP神经网络的销售预测算法研究

已知国内房屋售价具有一定的不完整的规律性,其会因季节变换、人群流动、国家相关政策等一系列因素而呈现一定的规律.与此同时,该规律性并没有确定的单一因子可以直接影响,故其售价与全部因素之间的关系也是非线性的.针对这一问题,利用神经网络输入量的非线性、冗杂性和可不完整性,对一段时期内的房屋售价进行预测是一种合理的预测方法.基...     

特殊事件对月售电量及其预测的影响分析

特殊事件会使月售电量发生很大变化,导致实际售电量曲线明显偏离典型售电量曲线。然而由不考虑特殊事件的传统预测模型得到的月售电量预测曲线却更接近于典型售电量曲线,这将不可避免地导致月售电量预测精度降低。为解决该问题,本文以异常高温,政治事件和超强台风为例,分析研究了特殊事件对月售电量及其预测的影响。首先,介绍了“互联网+”背景下基于大数据的月售电量预测模型,并对其预测精度进行了评估;其次,针对异常高温、政治事件及超强台风三种特殊事件,描述了各事件的特殊情况,以实际月售电量数据说明了特殊事件对月售电量的影响,然后利用月售电量预测模型研究了特殊事件对月售电量预测的影响,并详细分析了产生这种影响的原因,在此基础上,针对不同的特殊事件提出了相应的初步改善对策。     

Modelling the Retail Sales of Gasoline in a Portuguese Metropolitan Area

This paper describes the modelling approach for the sales of gasoline in service stations located in a Portuguese metropolitan area. The models were developed for planning purposes in order to assess potential sales of new sites. The estimates produced are more accurate than those made by previous models and are currently being used to support investment decisions of the largest Portuguese company. Starting from a basic multiplicative regression model, several segmentations of the service stations were obtained. Among these, the submodels for service stations located in urban areas and for service stations located along routes produced a better fit. The models reflect, without exception, the importance of the variables representing the size of service station and the "traffic" passing by, as well as variables which express location and road type. The fast growth experienced by this market explains the lesser impact on sales of the area sales potential and of competition.     

基于遗传算法的BP神经网络服装销售预测方法

针对服装企业产品销售的复杂性以及特殊性,提出一种有效的神经网络学习模型. 在对服装销售影响因子分析的基础上建立销售预测网络模型,利用遗传算法对后向传播神经网络的各连接权值进行优化计算. 方法综合了后向传播神经网格和遗传算法两者的优势,既具有神经网络强大的学习能力,又具有遗传算法的全局搜索能力.     

对当前钢铁市场营销环境的分析

文章简要阐述了在市场经济下,包钢销售工作的特点及相应的销售策略,如何提高单位的经济效益,在中国加入WTO后所实施的经营对策.     

成品油直销经营现状及市场开拓方向

2009年1月1日,我国成品油价格和燃油税费改革开始实施。未来几年,面对整个成品油经营环境的变化以及零售市场的发展趋势,如何开拓直销市场,把握成品油经营的方向？开拓市场的切入点在哪里？文章以广西地区成品油经营情况为例,探讨成品油直销经营现状及发展趋势,分析未来直销经营的市场开拓方向。     

基于时间序列的地区电网售电量预测方法研究

地区电网售电量的科学预测是电网建设规划的重要依据。考虑电量历史数据是一典型时间序列函数,本文建立了移动平均法、Winters、灰色马尔科夫三种预测模型,根据某地区的售电量历史数据求解模型,并对预测结果进行了分析和比较。结果表明,灰色马尔科夫模型预测结果与多年多年实际数据拟合效果最好、误差率最低,该方法的应用前景广阔。     

基于多层C/S结构的销售管理信息系统应用研究

论述了基于多层客户机/服务器结构的钢铁企业销售管理信息系统的设计、开发和应用。开发的钢铁企业销售管理信息系统基本满足了大中型钢铁企业在销售管理方面的需求,用户界面友好,功能强大,可以进行客户管理、款项管理、合同管理、商品岀入库管理等工作,大大提高了工作效率,减少了人力资源,增加了信息分析的准确性,对提高企业的市场竞争力具有重要意义。