技能预测制度的理论意涵与域外镜鉴

经济体要实现提高生产力、促进就业和社会发展的目标,必须动态促进当前和未来的技能供需均衡,尤其要为未来提前储备技能。梳理欧盟、国际劳工组织和新加坡、芬兰、美国技能预测制度的实践发现,技能预测制度的构成主体因技能预测工作的复杂性而呈现多元特征,技能预测内容因经济发展战略和技能预测变量而异,技能预测方法聚焦于职位描述与技能描述。针对有效率的技能预测制度提出如下结论:技能预测的最优制度模式为“市场—政府”协作模式,建立遴选技能预测主体与建构伙伴合作关系的机制、设置技能参与者的培训课程是技能预测制度的关键保障,技能预测的重点内容涵盖技能供给和需求预测、全周期技能错配监测、技能预测结果的发布与使用等方面。

美国前景预测制度及其借鉴

如何建立前景预测制度,加强对该制度实施的监管,是发展中国家证券监管机构亟待解决的现实问题。借鉴美国前景预测制度,建立健全预测信息的披露制度,这将有效规范上市公司的前景预测信息披露行为,防范预测信息的滥用,切实保护投资者权益。

财务预测信息披露制度：特点·问题·完善

财务预测信息是上市公司所披露的一种重要的未来信息,与企业现行披露的历史财务信息相比更具相关性,它所提供的信息对投资者和债权人了解上市公司未来的生产经营状况,做出合理有效的投资决策,防范和化解投资风险,有更为重要的意义。因此,建立一套完善的财务预测信息披露制度无疑能更好地促进资本市场的发展。本文拟对我国目前财务预测信息披露制度的特点进行概括,对其存在的问题进行分析和探讨,并对建立完善的财务预测信息披露制度提出意见和建议。

对重组盈利预测补偿制度的运行分析及完善建议

因降低了并购重组中的信息不对称,能一定程度遏制恶意定价、维护交易公平并保护中小投资者利益,重组盈利预测补偿制度是上市公司并购重组有关制度的重要内容。但是,随着上市公司第三方并购交易的增多,强制单边业绩对赌在扭曲交易定价、妨碍交易公平、阻滞并购整合方面的弊端日显突出。为此,结合市场发展特点,适时启动对这一制度的修正不仅直接满足上市公司并购的现实需要,也有助于进一步推动并购市场发展,提升监管对实体经济的支持。

上市公司预测性信息披露制度探析

上市公司预测性信息披露制度是上市公司信息披露制度的一项重要内容,它对于证券市场的高效运行及监管起着日益重要的作用。但目前我国该制度尚不完善,鉴于其特殊性与重要性,通过探析预测性信息的界定、预测性信息披露制度的意义、现状及其成因,从而找出完善该制度的对策,以促进证券市场的高效健全发展。

简论上市公司盈利预测的审核

本文在总结我国上市公司盈利预测制度的基本特与的基础上，分析了公司管理当局对造成盈利预测偏差的编制责任和注册会计师的审核责任。

健全制度 降低施工成本

近年我国建筑市场日趋规范,政府采购、工程招投标等措施的颁布实施,使得建筑工程变得越来越薄利,这样就迫使建筑施工企业不断地改进成本管理.笔者认为施工企业的成本管理应从以下几方面建立健全制度,并实施严格的管理:

试论我国预测性信息披露制度的完善

上市公司信息披露问题一直是证券监管的重点 ,但是有关预测性信息披露的理论和司法实践尚处于起步阶段。本文通过分析我国在预测性信息披露问题上存在的立法缺陷 ,借鉴国外的成功经验 ,提出完善我国的预测性信息披露制度的重点在于建立预测性信息披露免责制度和完善民事责任承担制度。

上海人口发展呈现6大特点

上海是我国最早实行计划生育的城市，经过几十年努力，本市少出生人口700多万，接近于城市人口数的一半。上海在全国率先建立出生预报预测制度，开展家庭计划生育指导和服务、扶助独生子女困难家庭等实事工程，造福于民，赢得了民心。据透露，上海人口发展目前面临的6个特点及挑战包括：

风险管理——说到做不到的4个成因

新的、潜在的致命风险随时可能出现，顶尖金融机构不断致力于从更多元的环境建立预测制度，以避免风险，让企业得以永续经营。

Application of predictive control scheduling method to real-time periodic control tasks overrun

Based on the abort strategy of fixed periods, a novel predictive control scheduling methodology was proposed to efficiently solve overrun problems. By applying the latest control value in the prediction sequences to the control objective, the new strategy was expected to optimize the control system for better performance and yet guarantee the schedulability of all tasks under overrun. The schedulability of the real-time systems with p-period overruns was analyzed, and the corresponding stability criteria was given as well. The simulation results show that the new approach can improve the performance of control system compared to that of conventional abort strategy, it can reduce the overshoot and adjust time as well as ensure the schedulability and stability.

Control-oriented dynamic fuzzy model and predictive control for proton exchange membrane fuel cell stack

Proton exchange membrane fuel cell (PEMFC) stack temperature and cathode stoichiometric oxygen are very important control parameters. The performance and lifespan of PEMFC stack are greatly dependent on the parameters. So, in order to improve the performance index, tight control of two parameters within a given range and reducing their fluctuation are indispensable. However, control-oriented models and control strategies are very weak junctures in the PEMFC development. A predictive control algorithm was presented based on their model established by input-output data and operating experiences. It adjusts the operating temperature to 80 ℃. At the same time, the optimized region of stoichiometric oxygen is kept between 1.8?2.2. Furthermore, the control algorithm adjusts the variants quickly to the destination value and makes the fluctuation of the variants the least. According to the test results, compared with traditional fuzzy and PID controllers, the designed controller shows much better performance.

Vector control of permanent magnet synchronous motor based on dynamic matrix control

Aiming at the control problem of strongly nonlinear and coupled permanent magnet synchronous motor(PMSM)oil rig,this paper presents a predictive control method based on dynamic matrix model.In this method,the dynamic matrix algorithm using multistep prediction technique is applied to the speed loop control of the motor vector control.And its control effect is compared with the traditional proportional integral(PI)control of the motor.By comparing the initial dynamic response and the steady-state recovery under load interference of the two methods,it is shown that the dynamic response and the robustness of the motor controlled by the new method is better than that controlled by conventional PI method.And the feasibility of new control in the application of PMSM oil rig is verified.

Yield strength prediction of rolled Al-(1.44-12.40)Si-0.7Mg alloy sheets under T4 condition

The effects of Si content on the microstructure and yield strength of Al-(1.44-12.40)Si-0.7 Mg(wt.%)alloy sheets under the T4 condition were systematically studied via laser scanning confocal microscopy(LSCM),DSC,TEM and tensile tests.The results show that the recrystallization grain of the alloy sheets becomes more refined with an increase in Si content.When the Si content increases from 1.44 to 12.4 wt.%,the grain size of the alloy sheets decreases from approximately 47 to 10μm.Further,with an increase in Si content,the volume fraction of the GP zones in the matrix increases slightly.Based on the existing model,a yield strength model for alloy sheets was proposed.The predicted results are in good agreement with the actual experimental results and reveal the strengthening mechanisms of the Al-(1.44-12.40)Si-0.7 Mg alloy sheets under the T4 condition and how they are influenced by the Si content.

Rolling force prediction for strip casting using theoretical model and artificial intelligence

Rolling force for strip casting of 1Cr17 ferritic stainless steel was predicted using theoretical model and artificial intelligence.Solution zone was classified into two parts by kiss point position during casting strip.Navier-Stokes equation in fluid mechanics and stream function were introduced to analyze the rheological property of liquid zone and mushy zone,and deduce the analytic equation of unit compression stress distribution.The traditional hot rolling model was still used in the solid zone.Neural networks based on feedforward training algorithm in Bayesian regularization were introduced to build model for kiss point position.The results show that calculation accuracy for verification data of 94.67% is in the range of ±7.0%,which indicates that the predicting accuracy of this model is very high.

Prediction of preheating conditions for inclined laser assisted machining

For laser assisted machining,shape of preheating laser heat source is changed irregularly because of complexity of material shape.So,the preheating temperature should be controlled by adjusting the feed rate or the laser power.Thermal analyses of the laser assisted machining process for inclination planes were performed.By analyzing the obtained temperature profile,a proper feed rate control method was proposed according to the inclination angles.In addition,the temperature distribution of the cross section after feed rate control was predicted.The correlation equation between inclination angles and adjusted proper feed rate was proposed.The results of this analysis can be used to predict the preheating effect on workpiece and can be applied as a preheating temperature control method in laser assisted machining processes.