Program for stream Business Analytics, Artificial Intelligence and Forecasting

WC-16: Analytics for Time Series Data
Stream: Business Analytics, Artificial Intelligence and Forecasting
Room: ZEU/250/Z
Chair(s): Kei Takahashi

• Simple Method for Unsupervised Anomaly Detection: An Application to Web Time Series Data
  Keisuke Yoshihara, Kei Takahashi
• Multivariate extrapolation - a tensor-based approach
  Josef Schosser
• Predicting prices of electric components in the B2B market
  Kei Takahashi

WD-16: Artificial intelligence
Stream: Business Analytics, Artificial Intelligence and Forecasting
Room: ZEU/250/Z
Chair(s): Birol Yüceoglu

• Machine learning in additive manufacturing and certification processes in aviation
  Maximilian Rosner, Denise Holfeld
• Predict the influence of anti-cancer drugs by designing an effective Deep Learning algorithm
  Seyyed Hassan Taheri, Amir Hossein Farzin, Mandana Fazeli Sangani
• Predicting egg sales using deep learning
  Birol Yüceoglu, Ömer Zeybek, Defne İdil Eskiocak, Buse Mert

TA-16: Forecasting
Stream: Business Analytics, Artificial Intelligence and Forecasting
Room: ZEU/250/Z
Chair(s): Julius Mehringer

• A benchmark on a new approach for the automation of energy forecasting
  Martin Seidler, Sabine Ritter, Maria Jüttner
• Predictive Demand Planning – A hybrid cloud based forecast algorithm
  Tony Alexander
• Short-term product price forecasting to schedule consumers’ purchase time decisions
  Benjamin Buchwitz, Anne Falkenberg, Ulrich Küsters
• Spare part demand forecasting with machine learning approaches
  Julius Mehringer, Christian Menden

TD-16: Business Analytics
Stream: Business Analytics, Artificial Intelligence and Forecasting
Room: ZEU/250/Z
Chair(s): Fabien Tricoire

• Related Search Recommendations via NLP Methods and Networks
  Robert Scheidweiler, Stefan Dresselhaus, Michael Bastubbe
• Machine learning-based queuing model regression - example selection, feature engineering and the role of traffic intensity
  Roland Braune