欢迎您！东篱公司
退出
-
申报数据库
-
立项数据库
-
成果数据库
-
项目获奖数据库
中文摘要：
在实际系统分析及建模中，人们往往需要保留一些特别重要的分析变量。本文改进了基于主基底的变量筛选方法，分两个阶段来筛选系统分析所需变量。用重要变量构建初始主基底超平面，作为筛选其他普通变量的起点。该方法既结合了人们的定性分析经验，又保留了基于主基底分析的变量筛选方法能够自动筛选系统分析所需最简变量集合的特点，达到了数据降维目的。实际案例分析验证了该方法的有效性。
英文摘要：
In practical system analysis and modeling, analysts always need to retain certain important indispensable variables. This paper proposed an improved variable selection method based on Principal Analysis, which selected variables by two stages. The indispensable variables were used to construct the initial Principal Basis hyperplane to select the general variables. This method referred to the qualitative analysis experiences and could also automatically select the simplest variable set to reduce the data dimension for system analysis as the original method. Practical case validated the effectiveness of this improved method.
同期刊论文项目
同项目期刊论文
Equity and efficiency analysis of pricing strategies in a bi-modal network with heterogeneous user g
Modeling the evolutions of day-to-day route choice and year-to-year ATIS adoption with stochastic us
Modeling time-dependent travel choice problems in road networks with multiple user classes and multi
One-step solution fabrication of magnetic chains consisting of jingle-bell-shaped cobalt mesospheres
Support vector machine forecasting method improved by chaotic particle swarm optimization and its ap
Static floor field and exit choice for pedestrian evacuation in rooms with internal obstacles and mu
A model for evaluation of transport policies in multimodal n etworks with r oad and p arking capacit
期刊信息
位置：