战略性新兴产业与经济发展耦合协调发展研究——基于安徽省的实证研究

基于系统耦合理论,对安徽省战略性新兴产业系统与区域经济系统的耦合协调发展状况进行测度和系统评价。结果显示,安徽省大多数地级市的战略性新兴产业与区域经济并未实现同步型发展,但两者发展的一致性程度在逐渐提升;就两者耦合协调度而言,总体偏低,大多数地级市仍处在中低度耦合阶段,但在时间序列上呈现逐渐提升的态势,总体状况趋于良性发展;在空间格局上,耦合协调度一定程度上呈现以合肥、芜湖为中心逐渐向外围扩散的趋势,但中心城市对周边地区耦合协调程度提升的辐射和带动作用还有待进一步加强。     

中国石化行业二氧化碳排放的影响因素分解——基于广义迪氏指数分解法

采用广义迪氏指数分解法对我国石化行业2000—2016年的二氧化碳排放演变进行分解,进行阶段性及累计效应分析,考察投资、产出、能源消费以及相应的碳强度、能源强度和投资效率的变化对二氧化碳排放变化的贡献情况。结果表明,投资、产出及能源消费规模是促进二氧化碳排放增长的主要因素;投资碳强度和产出碳强度是主要的促降因素;能源碳强度、投资效率和能源强度作用较弱,具有很大的改善空间,是未来石化行业减碳政策制定的主要着手点。     

Intermittent control strategy for synchronization of fractional-order neural networks via piecewise Lyapunov function method

In this paper, the synchronization problem of fractional-order neural networks (FNNs) with chaotic dynamics is investigated via the intermittent control strategy. Two types of intermittent control methods, the aperiodic one and the periodic one, are applied to achieve the synchronization of the considered systems. Based on the dynamic characteristics of the intermittent control systems, the piecewise Lyapunov function method is employed to derive the synchronization criteria with less conservatism. The results under the aperiodically intermittent control show more generality than the ones via the periodically intermittent control. For each of the aperiodic and periodic cases, a simple controller design process is presented to show how to design the corresponding intermittent controller. Finally, two numerical examples are provided to demonstrate the effectiveness of the obtained theoretical results.     

Fractional order sliding mode control of a pneumatic position servo system

Gas flow has fractional order dynamics; therefore, it is reasonable to assume that the pneumatic systems with a proportional valve to regulate gas flow have fractional order dynamics as well. There is a hypothesis that the fractional order control has better control performance for this inherent fractional order system, although the model used for fractional controller design is integer order. To test this hypothesis, a fractional order sliding mode controller is proposed to control the pneumatic position servo system, which is based on the exponential reaching law. In this method, the fractional order derivative is introduced into the sliding mode surface. The stability of the controller is proven using Lyapunov theorem. Since the pressure sensor is not required, the control system configuration is simple and inexpensive. The experimental results presented indicate the proposed method has better control performance than the fractional order proportional integral derivative (FPID) controller and some conventional integral order control methods. Points to be noticed here are that the fractional order sliding mode control is superior to the integral order sliding mode counterpart, and the FPID is superior to the corresponding integral order PID, both with optimal parameters. Among all the methods compared, the proposed method achieves the highest tracking accuracy. Moreover, the proposed controller has less chattering in the manipulated variable, the energy consumption of the controller is therefore substantially reduced.     

Linear output-feedback-based semi-global stabilization for switched nonlinear time-delay systems

This paper focuses on the problem of semi-global output-feedback stabilization for a class of switched nonlinear time-delay systems in strict-feedback form. A switched state observer is first constructed, then switched linear output-feedback controllers for individual subsystems are designed. By skillfully constructing multiple Lyapunov–Krasovskii functionals and successfully solving several troublesome obstacles, such as time-varying delay and switching signals and nonlinearity in the design procedure, the switched linear output-feedback controllers designed can render the resulting closed-loop switched system semi-globally stabilizable under a class of switching signals with average dwell time. Furthermore, under some milder conditions on nonlinearities, the semi-global output-feedback stabilization problem for switched nonlinear time-delay systems is also studied. Simulation studies on two examples, which include a continuous stirred tank reactor, are carried out to demonstrate the effectiveness of the proposed approach.     

Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.     

中国城市蔓延对绿色全要素生产率的影响

提高城市发展质量是现阶段经济高质量发展的应有之义,中国城镇化进程中的城市蔓延已成为影响城市高质量发展的重要因素。本文利用2004—2017年中国285个地级及其以上城市面板数据,实证考察了城市蔓延与绿色全要素生产率之间异质性关系。研究发现：①城市适度蔓延对绿色全要素生产率起显著提升作用,蔓延过度则呈现抑制效应或者影响不明显;②就人口集聚的区域差异而言,城市蔓延对东部地区促进作用突出,而对中西部地区更多表现出抑制效应;③此外,随着经济超过最优集聚区间,两者之间的反方向关联变为同向关系,进一步发现,两者之间显著存在基于制造业集聚的“倒U型”门槛效应,而在服务业集聚程度较高的城市,城市蔓延的促进效应并不显著。本文深化了对城市蔓延影响城市绿色发展基本规律的认识和理解,为城市高质量发展的“顶层设计”提供了有益的参考,对中国正在推进的以中心城市引领城市群和新型城镇化战略也有着启示意义。     

国外技术标准战略经验及其对广东的启示

分析“技术标准战略”概念内涵及其与产业发展的关系;研究和总结欧盟控制型、美国争夺型、日本谨慎重优型和韩国重点开拓型技术标准战略模式的实践经验.广东在“一带一路”和粤港澳大湾区建设背景下积极推进建设国内先进、国际化水平高的技术标准体系,但仍存在工作机制不完善、公众参与度低、技术研发与标准缺乏联动性以及重点产业标准化力度不...     

基于绿色创新补助政策的银企系统性风险研究

降低银行与绿色创新企业间面临的系统性风险已成为中国现阶段经济发展亟待解决的问题。本文将银行与绿色创新企业两类主体作为研究对象,构建人工银企系统,基于仿真实验着重考察其重要主体行为。具体地,着重于考察资产负债表构建与更新、主体行为动态演化、流动性资产更新以及违约清算机制等方面,通过仿真手段探究绿色创新补助政策形式与补助强度对银企系统性风险与系统总收益的影响机制,以对理论模型进行全面验证。本研究结论的意义在于：聚焦于绿色创新补助政策与银企系统性风险的内在关系,通过计算实验方法进行验证与延伸,为促进中国绿色创新企业健康发展,帮助政府与银行防范绿色创新企业可能导致的系统性风险提供理论机制参考与新观点。     

谁在主导中日韩的国际科学合作?

[目的/意义]为了探究中日韩的国际科学合作中的主导地位及变化趋势。[方法/过程]以"中日"、"中韩"和"中日韩"国际论文合著现象为分析对象,通过科学计量的方法和手段,从重要作者、高影响力论文和资助者三个维度来分析近40年来中日韩科学合作背后的主导力量。[结果/结论]研究结果发现中日科学合作呈现出日本主导趋势由强到弱,而中国主导趋势渐强并超过日本;中韩科学合作呈现双方共同主导的特征;在三国合作中,中国主导的论文影响力较强,但随着论文影响力的增大,中国显示出的主导优势却在减弱;中国作为科研资助者极大地推动了三国的科学合作。