区域经济单位GDP能耗的解析研究

发布时间：2018-09-04 14:01

【摘要】：能源是重要的战略物资,能源的稀缺及不可再生性使其成为关乎民生、攸关社会经济发展的首要物资。区域经济的能源利用效率近年来成为颇受社会各界关注的热点问题,本文以辽宁省为例解析研究区域经济单位GDP能耗问题。本文对经济增长与能源消费之间的关系进行研究,以期把握区域经济单位GDP能耗的变化规律,构建合理有效的单位GDP能耗的预测、预警方法和系统,为转变发展方式,促进区域经济科学发展,建设资源节约型、环境友好型社会提供有力保障。本文主要研究单位GDP能耗的影响因素,在分析统计大量相关数据基础上,构建了区域经济单位GDP能耗的预测预警模型。工作内容主要分为以下五个方面：1)根据实际情况,分析统计局发布与备案的相关数据资料,主要研究了与单位GDP能耗密切相关的电量消耗、生产产值、产业结构和能源消费结构等方面的数据,对数据相关性进行分析,设计以电量消耗、历史能源消耗和历史GDP统计值作为构建预测预警模型的基础。在此基础上,对数据进行预处理,为单位GDP能耗预测模型的构建奠定数据基础。2)针对研究中数据量少的问题,采用支持向量机(SVM)算法进行模型构建。为了进一步提高所建立模型的精度,采用粒子群优化算法(PSO)对SVM算法的参数进行优化,使得本文所提出的算法针对不同数据时都能获得精度较好的预测模型。实验结果表明,本文提出的算法能够较好的跟随实际情况的变化,预测误差较低,能够满足实际需求。3)分析单位GDP能耗的预测结果,根据给定的单位GDP能耗预警范围实现单位GDP能耗的预警。单位GDP能耗的预警是预测结果的另一种表现形式,能够更加直观的表现预测结果,为决策者提供数据支持。4)研究可能对单位GDP能耗产生影响的相关因素,定性和定量的解析产业结构及能源消费结构与区域经济单位GDP能耗的关系,分析了对单位GDP能耗可能产生影响的因素及影响方式,对提高能源利用效率,降低单位GDP能耗提供可操作的理论方向。5)结合本文提出的预测预警算法,构建了区域经济单位GDP能耗预测系统及其预警子系统。在实现数据管理等基本功能的基础上,系统具有较好的单位GDP能耗预测能力,预测值与实际值的相对误差较小,满足对单位GDP能耗的管理要求；同时系统以预测分析结果为依据,构建单位GDP能耗预警子系统,并提供多种结果展示方式,实现良好的人机交互。
[Abstract]:Energy is an important strategic material. The scarcity and non-renewable of energy make it the most important material related to people's livelihood and social and economic development. The energy efficiency of regional economy has become a hot issue in recent years. This paper takes Liaoning Province as an example to analyze the energy consumption of regional economy unit GDP. In this paper, the relationship between economic growth and energy consumption is studied, in order to grasp the change law of energy consumption per unit GDP of regional economy, to construct reasonable and effective prediction, early warning method and system of unit GDP energy consumption, in order to change the mode of development. Promote regional economic and scientific development, build a resource-saving, environmental-friendly society to provide adequate protection. This paper mainly studies the influencing factors of unit GDP energy consumption. Based on the analysis and statistics of a large number of relevant data, the prediction and early warning model of unit GDP energy consumption in regional economy is established. The contents of the work are divided into the following five aspects: 1) according to the actual situation, the relevant data published and recorded by the Bureau of Statistics are analyzed, and the electricity consumption and production value closely related to the energy consumption per GDP are mainly studied. Based on the data of industrial structure and energy consumption structure, the correlation of data is analyzed, and the statistical value of electricity consumption, historical energy consumption and historical GDP are used as the basis of the prediction and early warning model. On this basis, the data is preprocessed to lay a data foundation for the construction of unit GDP energy consumption prediction model. (2) aiming at the problem of less data in the research, the support vector machine (SVM) algorithm is used to build the model. In order to further improve the accuracy of the established model, the particle swarm optimization algorithm (PSO) is used to optimize the parameters of the SVM algorithm. The experimental results show that the proposed algorithm can better follow the change of the actual situation, the prediction error is low, and it can meet the actual demand of 3. 3) the prediction results of unit GDP energy consumption can be analyzed. According to the given unit GDP energy consumption warning range, the unit GDP energy consumption warning is realized. The early warning of unit GDP energy consumption is another form of prediction results, which can more intuitively represent the predicted results and provide data support for decision makers.) the relevant factors that may affect the unit GDP energy consumption are studied. The relationship between industrial structure, energy consumption structure and energy consumption per unit of regional economy is analyzed qualitatively and quantitatively. The possible factors and ways of influencing energy consumption per unit GDP are analyzed, and the efficiency of energy utilization is improved. The theoretical direction of reducing the unit GDP energy consumption and providing operational direction 5) combined with the prediction and early warning algorithm proposed in this paper, a regional economic unit GDP energy consumption prediction system and its early warning subsystem are constructed. On the basis of realizing data management and other basic functions, the system has better prediction ability of unit GDP energy consumption, and the relative error between predicted value and actual value is small, which meets the management requirements of unit GDP energy consumption. At the same time, based on the prediction and analysis results, the system constructs a unit GDP energy consumption warning subsystem, and provides a variety of results display methods to achieve good human-computer interaction.
【学位授予单位】：东北大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F127;F205

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