首页|Research Conducted at Beijing Jiaotong University Has Provided New Information a bout Support Vector Machines (Short-term High-speed Rail Passenger Flow Predicti on By Integrating Ensemble Empirical Mode Decomposition With Multivariate Grey . ..)
Research Conducted at Beijing Jiaotong University Has Provided New Information a bout Support Vector Machines (Short-term High-speed Rail Passenger Flow Predicti on By Integrating Ensemble Empirical Mode Decomposition With Multivariate Grey . ..)
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A new study on Support Vector Machines is now available. According to news reporting from Beijing, People's Republic o f China, by NewsRx journalists, research stated, "Short-term prediction of high- speed rail (HSR) passenger flow provides a daily ridership estimation for the ne ar future, which is critical to HSR planning and operational decision making. Th is paper proposes a new methodology that integrates ensemble empirical mode deco mposition with multivariate support vector machines (EEMDMSVM)." Funders for this research include National Natural Science Foundation of China ( NSFC), Beijing Jiaotong University, China.
BeijingPeople's Republic of ChinaAsi aEmerging TechnologiesMachine LearningSupport Vector MachinesVector Mach inesBeijing Jiaotong University
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