【北航经管学术论坛】
  
  
 
   
  
 
澳大利亚莫纳什大学
  
 
Christoph Bergmeir博士学术讲座
  
     
    
       
        
         
         
            
          
             
           
              
            
               
             
                
              
                 
               
                  
                
                   
                 
                    
                  
                     
                   
                      
                    
                       
                      
                     
                    
                   
                  
                 
                
               
              
             
            
           
          
          
          
          
         
        
       
        
        
       
        
 
    
    
   
 
题目:Forecasting Across Time Series Databases using Long Short-Term Memory Networks on Groups of Similar Series
  
 
主讲人:Dr. Christoph Bergmeir,Monash University
  
 
时间:2018年6月29日(星期五),15:00 pm– 16:00 pm
  
 
地点:新主楼A1028
   
 
邀请人:康雁飞 副教授
  
 
   
  
 
摘要:With the advent of Big Data, nowadays in many applications databases containing large quantities of similar time series are available. Forecasting time series in these domains with traditional univariate forecasting procedures leaves great potentials for producing accurate forecasts untapped. Recurrent neural networks, and in particular Long Short-Term Memory (LSTM) networks have proven recently that they are able to outperform state-of-the-art univariate time series forecasting methods in this context, when trained across all available time series. However, if the time series database is heterogeneous accuracy may degenerate, so that on the way towards fully automatic forecasting methods in this space, a notion of similarity between the time series needs to be built into the methods. To this end, we present a prediction model using LSTMs on subgroups of similar time series, which are identified by time series clustering techniques. The proposed methodology is able to consistently outperform the baseline LSTM model, and it achieves competitive results on benchmarking datasets, in particular outperforming all other methods on the CIF2016 dataset. 
  
 
   
  
 
   
  
 
简介:Dr. Christoph Bergmeir is a Lecturer in Data Science in the Monash Faculty of Information Technology. He works as a Data Scientist in a variety of projects with external partners in diverse sectors, e.g. in healthcare or infrastructure maintenance. Christoph holds a PhD in Computer Science from the University of Granada, Spain, and an M.Sc. degree in Computer Science from the University of Ulm, Germany. He has published on time series prediction using Machine Learning methods, recurrent neural networks and long short-term memory neural networks (LSTM), time series predictor evaluation, as well as on medical applications and software packages in the R programming language, in journals such as IEEE Transactions on Neural Networks and Learning Systems, Journal of Statistical Software, Computational Statistics and Data Analysis, and Information Sciences. 
  
 
   
  
 
   
  
 
经管学院科研办
  
 
2018-06-27