A forecast of bulk-holding stock based on random forest

首先通过对基金重仓股的财务指标和市场指标的分析,建立一套科学合理的基金重仓股指标体系;其次利用随机森林建立基金重仓股的预测模型;最后通过实验验证了方法的有效性和优越性.本研究将为投资者提供一个投资决策的优良工具.Firstly we construct a system of scientific stock index by means of analysis of financing index and market index.Secondly we construct forecast model based on random forest.In the end,numerical results show that the method used is effective and advantageous.So this research provides an excellent decision-making tool for investors.国家自然科学基金资助项目(60704042

A UNIVERSAL AUTOMATIC FILM MEASURING SYSTEM

自动通用胶片判读仪是一种高智能化的精密光学测试设备,采用了计算机控制飞点扫描技术、精密光学测量技术、图象跟踪测量与信息处理技术。飞点管分辨率达4096×4096象元,通过光学系统胶片上获得6.55μm高分辨率,飞点扫描方式灵活多样且可随意控制,通用于目前我国靶场所有的电影经纬仪和高速摄影机35mm胶片的数据判读。具有自动判读和半自动判读两种工作模式,自动判读的速度为5帧/秒,自动判读的精度为σ=±0.011mm,半自动判读的精度为σ=±0.009mm,测量数据可以记录、打印和显示

Integrated application of uniform design and least-squares support vector machines to transfection optimization

National Natural Science Foundation of China [30750013]; Key Science Research Project Natural Science Foundation of Xiamen [WKZ0501]Background: Transfection in mammalian cells based on liposome presents great challenge for biological professionals. To protect themselves from exogenous insults, mammalian cells tend to manifest poor transfection efficiency. In order to gain high efficiency, we have to optimize several conditions of transfection, such as amount of liposome, amount of plasmid, and cell density at transfection. However, this process may be time-consuming and energy-consuming. Fortunately, several mathematical methods, developed in the past decades, may facilitate the resolution of this issue. This study investigates the possibility of optimizing transfection efficiency by using a method referred to as least-squares support vector machine, which requires only a few experiments and maintains fairly high accuracy. Results: A protocol consists of 15 experiments was performed according to the principle of uniform design. In this protocol, amount of liposome, amount of plasmid, and the number of seeded cells 24 h before transfection were set as independent variables and transfection efficiency was set as dependent variable. A model was deduced from independent variables and their respective dependent variable. Another protocol made up by 10 experiments was performed to test the accuracy of the model. The model manifested a high accuracy. Compared to traditional method, the integrated application of uniform design and least-squares support vector machine greatly reduced the number of required experiments. What's more, higher transfection efficiency was achieved. Conclusion: The integrated application of uniform design and least-squares support vector machine is a simple technique for obtaining high transfection efficiency. Using this novel method, the number of required experiments would be greatly cut down while higher efficiency would be gained. Least-squares support vector machine may be applicable to many other problems that need to be optimized