• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 125 matches

• 2020
• 
  Hervice Roméo Fogno Fotso, Claude Vidal Aloyem Kazé, Germaine Djuidje Kenmoe:
  Optimal Input Variables Disposition of Artificial Neural Networks Models for Enhancing Time Series Forecasting Accuracy. Appl. Artif. Intell. 34(11): 792-815 (2020)
• 
  Shuo-Wen Chang, Chung-Ling Chang, Long-Tin Li, Shih-Wei Liao:
  Reinforcement Learning for Improving the Accuracy of PM2.5 Pollution Forecast Under the Neural Network Framework. IEEE Access 8: 9864-9874 (2020)
• 
  Vincent B. Getanda, Hidetoshi Oya, Tomohiro Kubo, Yosuke Sato:
  Data Grouping Techniques' Performance Analysis in GM(1, 1)'s Prediction accuracy Improvement for Forecasting Traffic parameters. Mechatron. Syst. Control. 48(1) (2020)
• 
  Nghiem Van Tinh:
  Enhanced Forecasting Accuracy of Fuzzy Time Series Model Based on Combined Fuzzy C-Mean Clustering with Particle Swam Optimization. Int. J. Comput. Intell. Appl. 19(2): 2050017:1-2050017:26 (2020)
• 
  Abdelhakim El hendouzi, Abdennaser Bourouhou, Omar Ansari:
  The Importance of Distance between Photovoltaic Power Stations for Clear Accuracy of Short-Term Photovoltaic Power Forecasting. J. Electr. Comput. Eng. 2020: 9586707:1-9586707:14 (2020)
• 
  Taikyeong Jeong:
  Deep Neural Network Algorithm Feedback Model with Behavioral Intelligence and Forecast Accuracy. Symmetry 12(9): 1465 (2020)
• 
  Theresa Maria Rausch, Tobias Albrecht:
  The Impact of Lead Time and Model Selection on the Accuracy of Call Center Arrivals' Forecasts. ECIS 2020
• 
  Xianjiao Wu, Hong Hong, Qiang Ye:
  Professional Connections within Analyst Teams and Forecast Accuracy. HICSS 2020: 1-10
• 
  Takashi Tanizaki, Yuta Hanayama, Takeshi Shimmura:
  Forecasting Customers Visiting Using Machine Learning and Characteristics Analysis with Low Forecasting Accuracy Days. APMS (2) 2020: 670-678
• 
  Thomas Orth, Michael Bloodgood:
  Early Forecasting of Text Classification Accuracy and F-Measure with Active Learning. ICSC 2020: 77-84
• 
  Pavel Atanasov, Jens Witkowski, Lyle Ungar, Barbara A. Mellers, Philip Tetlock:
  Small Steps to Accuracy: Incremental Belief Updaters Are Better Forecasters. EC 2020: 873-874
• 
  Thomas Orth, Michael Bloodgood:
  Early Forecasting of Text Classification Accuracy and F-Measure with Active Learning. CoRR abs/2001.10337 (2020)
• 
  Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir:
  Improving the Accuracy of Global Forecasting Models using Time Series Data Augmentation. CoRR abs/2008.02663 (2020)
• 
  Xuan Bi, Gediminas Adomavicius, William Li, Annie Qu:
  Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness. CoRR abs/2011.03452 (2020)
• 
  Sella Nevo, Gal Elidan, Avinatan Hassidim, Guy Shalev, Oren Gilon, Grey Nearing, Yossi Matias:
  ML-based Flood Forecasting: Advances in Scale, Accuracy and Reach. CoRR abs/2012.00671 (2020)
• 2019
• 
  Muhammad Uzair Yousuf, Ibrahim Al-Bahadly, Ebubekir Avci:
  Current Perspective on the Accuracy of Deterministic Wind Speed and Power Forecasting. IEEE Access 7: 159547-159564 (2019)
• 
  Toly Chen, Chungwei Ou, Yu-Cheng Lin:
  A fuzzy polynomial fitting and mathematical programming approach for enhancing the accuracy and precision of productivity forecasting. Comput. Math. Organ. Theory 25(2): 85-107 (2019)
• 
  Jiao Wang, Zhibing Liu, Ruiqing Zhao:
  On the interaction between asymmetric demand signal and forecast accuracy information. Eur. J. Oper. Res. 277(3): 857-874 (2019)
• 
  Ümit Çavus Büyüksahin, Seyda Ertekin:
  Improving forecasting accuracy of time series data using a new ARIMA-ANN hybrid method and empirical mode decomposition. Neurocomputing 361: 151-163 (2019)
• 
  Dongha Kim, JongRoul Woo, Jungwoo Shin, Jongsu Lee, Yongdai Kim:
  Can search engine data improve accuracy of demand forecasting for new products? Evidence from automotive market. Ind. Manag. Data Syst. 119(5): 1089-1103 (2019)
• 
  Dazhi Yang, Allan N. Zhang:
  Impact of Information Sharing and Forecast Combination on Fast-Moving-Consumer-Goods Demand Forecast Accuracy. Inf. 10(8): 260 (2019)
• 
  Shuk Ying Ho, Ka Wai (Stanley) Choi, Fan (Finn) Yang:
  Harnessing Aspect - Based Sentiment Analysis: How A re Tweets Associated with Forecast Accuracy? J. Assoc. Inf. Syst. 20(8): 2 (2019)
• 
  Nicholas G. Reich, Craig J. McGowan, Teresa K. Yamana, Abhinav Tushar, Evan L. Ray, Dave Osthus, Sasikiran Kandula, Logan C. Brooks, Willow Crawford-Crudell, Graham Casey Gibson, Evan Moore, Rebecca Silva, Matthew Biggerstaff, Michael A. Johansson, Roni Rosenfeld, Jeffrey Shaman:
  Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the U.S. PLoS Comput. Biol. 15(11) (2019)
• 
  Jaroslav Frnda, Marek Durica, Jan Nedoma, Stanislav Zabka, Radek Martinek, Michal Kostelansky:
  A Weather Forecast Model Accuracy Analysis and ECMWF Enhancement Proposal by Neural Network. Sensors 19(23): 5144 (2019)
• 
  Sarat Chandra Nayak:
  Escalation of Forecasting Accuracy through Linear Combiners of Predictive Models. EAI Endorsed Trans. Scalable Inf. Syst. 6(22): e2 (2019)
• 
  David Rosewater, Summer Ferreira, David Schoenwald, Jonathan Hawkins, Surya Santoso:
  Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy. IEEE Trans. Smart Grid 10(3): 2453-2462 (2019)
• 
  Hossein Shafizadeh-Moghadam:
  Improving spatial accuracy of urban growth simulation models using ensemble forecasting approaches. Comput. Environ. Urban Syst. 76: 91-100 (2019)
• 
  Maria Rosienkiewicz:
  Accuracy Assessment of Artificial Intelligence-Based Hybrid Models for Spare Parts Demand Forecasting in Mining Industry. ISAT (3) 2019: 176-187
• 
  Thomas Ott, Stefan Glüge, Richard Bödi, Peter Kauf:
  Economic Measures of Forecast Accuracy for Demand Planning: A Case-Based Discussion. Applied Data Science 2019: 371-386
• 2018
• 
  Sachit Mahajan, Hao-Min Liu, Tzu-Chieh Tsai, Ling-Jyh Chen:
  Improving the Accuracy and Efficiency of PM2.5 Forecast Service Using Cluster-Based Hybrid Neural Network Model. IEEE Access 6: 19193-19204 (2018)

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