To further understand the status quo and change tendency of ecological security in county area, we took the example of Ningwu County, the headstream of Fenhe River, confronting serious eco-environment problem and cons...To further understand the status quo and change tendency of ecological security in county area, we took the example of Ningwu County, the headstream of Fenhe River, confronting serious eco-environment problem and considerable human impacts. Taking Ningwu as the study area and using variation coefficient method to determine the weights of the indices, we built ecological security pattern based on Pressure-State-Response （P-S-R） Model of Organization for Economic Cooperation and Development. The ecological security status was evaluated by calculating eco-security index （ESI） with socio-economic statistical data of Ningwu during 2001 -2010. The results showed that the situation of eco-security had been improved from heavy alarm to relative safety during 2001 -2010. It reflected that the ecological economic system in Ningwu County tended to be relaxed constantly after experienced a sharp conflict between ecological environment and economic growth. The ecological safety awareness was growing, however, by force of the objective requirements of population growth and economic development, the situation of ecological security was still unstable.展开更多
Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced b...Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced by other important financial indexes across the world such as commodity price and financial technical indicators. This paper systematically investigated four supervised learning models, including Logistic Regression, Gaussian Discriminant Analysis (GDA), Naive Bayes and Support Vector Machine (SVM) in the forecast of S&P 500 index. After several experiments of optimization in features and models, especially the SVM kernel selection and feature selection for different models, this paper concludes that a SVM model with a Radial Basis Function (RBF) kernel can achieve an accuracy rate of 62.51% for the future market trend of the S&P 500 index.展开更多
【目的】研究陕西省的生态安全动态变化,为区域社会经济的可持续发展提供科学依据。【方法】以陕西省为研究区域,在参考国内外已有研究成果的基础上,借助压力-状态-响应模型(P-S-R模型)框架,构建了该区域生态安全评价指标体系,采用理想...【目的】研究陕西省的生态安全动态变化,为区域社会经济的可持续发展提供科学依据。【方法】以陕西省为研究区域,在参考国内外已有研究成果的基础上,借助压力-状态-响应模型(P-S-R模型)框架,构建了该区域生态安全评价指标体系,采用理想解法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS法),在时间尺度上(1996-2006年)对陕西省的生态安全进行定量评价。【结果】(1)1996-2006年,陕西省生态压力系统安全指数CP值有一定波动,但总体上呈下降趋势,生态负荷加大;状态系统安全指数CS值虽有波动但总体上表现出增长态势,安全状况逐渐好转;响应系统安全指数CR值呈明显的增长趋势,显示陕西省对生态系统的保护能力、保护力度有所增强。(2)陕西省生态安全指数从1996年的0.39增加至2006年的0.60,整体上呈增长趋势,表明生态系统状态由不安全转为较不安全,研究期末(2006年)陕西省的生态安全水平仍处在临界安全边缘。【结论】TOPSIS法简单直观,评价结果客观,且符合区域生态安全变化的实际情况,可用于不同区域生态安全的动态评价。展开更多
基金Supported by National Natural Science Fund,China(41271143)Soft Science Research Project of Shanxi,China(2013041059-04)
文摘To further understand the status quo and change tendency of ecological security in county area, we took the example of Ningwu County, the headstream of Fenhe River, confronting serious eco-environment problem and considerable human impacts. Taking Ningwu as the study area and using variation coefficient method to determine the weights of the indices, we built ecological security pattern based on Pressure-State-Response （P-S-R） Model of Organization for Economic Cooperation and Development. The ecological security status was evaluated by calculating eco-security index （ESI） with socio-economic statistical data of Ningwu during 2001 -2010. The results showed that the situation of eco-security had been improved from heavy alarm to relative safety during 2001 -2010. It reflected that the ecological economic system in Ningwu County tended to be relaxed constantly after experienced a sharp conflict between ecological environment and economic growth. The ecological safety awareness was growing, however, by force of the objective requirements of population growth and economic development, the situation of ecological security was still unstable.
文摘Forecasting the movement of stock market is a long-time attractive topic. This paper implements different statistical learning models to predict the movement of S&P 500 index. The S&P 500 index is influenced by other important financial indexes across the world such as commodity price and financial technical indicators. This paper systematically investigated four supervised learning models, including Logistic Regression, Gaussian Discriminant Analysis (GDA), Naive Bayes and Support Vector Machine (SVM) in the forecast of S&P 500 index. After several experiments of optimization in features and models, especially the SVM kernel selection and feature selection for different models, this paper concludes that a SVM model with a Radial Basis Function (RBF) kernel can achieve an accuracy rate of 62.51% for the future market trend of the S&P 500 index.
文摘【目的】研究陕西省的生态安全动态变化,为区域社会经济的可持续发展提供科学依据。【方法】以陕西省为研究区域,在参考国内外已有研究成果的基础上,借助压力-状态-响应模型(P-S-R模型)框架,构建了该区域生态安全评价指标体系,采用理想解法(Technique for Order Preference by Similarity to Ideal Solution,TOPSIS法),在时间尺度上(1996-2006年)对陕西省的生态安全进行定量评价。【结果】(1)1996-2006年,陕西省生态压力系统安全指数CP值有一定波动,但总体上呈下降趋势,生态负荷加大;状态系统安全指数CS值虽有波动但总体上表现出增长态势,安全状况逐渐好转;响应系统安全指数CR值呈明显的增长趋势,显示陕西省对生态系统的保护能力、保护力度有所增强。(2)陕西省生态安全指数从1996年的0.39增加至2006年的0.60,整体上呈增长趋势,表明生态系统状态由不安全转为较不安全,研究期末(2006年)陕西省的生态安全水平仍处在临界安全边缘。【结论】TOPSIS法简单直观,评价结果客观,且符合区域生态安全变化的实际情况,可用于不同区域生态安全的动态评价。
