Principal Component Analysis Aware BP Neural Network for Personal Information Prediction in Internet Based Services
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[1] Jianqiang Yi,et al. BP neural network prediction-based variable-period sampling approach for networked control systems , 2007, Appl. Math. Comput..
[2] Dan Jong Kim,et al. A study of mobile user engagement (MoEN): Engagement motivations, perceived value, satisfaction, and continued engagement intention , 2013, Decis. Support Syst..
[3] Feng Yu,et al. A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network , 2014 .
[4] Anantha Chandrakasan,et al. An SRAM using output prediction to reduce BL-switching activity and statistically-gated SA for up to 1.9× reduction in energy/access , 2013, 2013 IEEE International Solid-State Circuits Conference Digest of Technical Papers.
[5] Paul van Schaik,et al. Attitudes towards user experience (UX) measurement , 2014, Int. J. Hum. Comput. Stud..
[6] Katja Filippova,et al. User Demographics and Language in an Implicit Social Network , 2012, EMNLP.
[7] Varun Grover,et al. A model of consumers' perceptions of the invasion of information privacy , 2013, Inf. Manag..
[8] P. Paatero,et al. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .
[9] Shifei Ding,et al. An optimizing BP neural network algorithm based on genetic algorithm , 2011, Artificial Intelligence Review.
[10] Nitesh V. Chawla,et al. Inferring user demographics and social strategies in mobile social networks , 2014, KDD.
[11] Wen Jin,et al. The improvements of BP neural network learning algorithm , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.
[12] Shuo Ding,et al. Approximation Performance of BP Neural Networks Improved by Heuristic Approach , 2013 .
[13] Tharam S. Dillon,et al. Neural-Network-Based Models for Short-Term Traffic Flow Forecasting Using a Hybrid Exponential Smoothing and Levenberg–Marquardt Algorithm , 2012, IEEE Transactions on Intelligent Transportation Systems.
[14] Pertti Saariluoma,et al. Emotional Dimensions of User Experience: A User Psychological Analysis , 2014, Int. J. Hum. Comput. Interact..
[15] Michael T. Orchard,et al. Overlapped block motion compensation: an estimation-theoretic approach , 1994, IEEE Trans. Image Process..
[16] Steven X. Ding,et al. A Review on Basic Data-Driven Approaches for Industrial Process Monitoring , 2014, IEEE Transactions on Industrial Electronics.
[17] Ling Xu. Mixture models of human resource management flexibility and firm performance , 2012 .
[18] Wang Weiming,et al. Resource scheduling algorithm and ecnomic model in ForCES networks , 2014, China Communications.
[19] Christian Janiesch,et al. A Method and Tool for Predictive Event-Driven Process Analytics , 2013, Wirtschaftsinformatik.
[20] Reza Zafarani,et al. Understanding User Migration Patterns in Social Media , 2011, AAAI.
[21] Fang Zhang,et al. Based on Improved BP Neural Network to Forecast Demand for Spare Parts , 2009, 2009 Fifth International Joint Conference on INC, IMS and IDC.
[22] K. Abhishek,et al. A rainfall prediction model using artificial neural network , 2012, 2012 IEEE Control and System Graduate Research Colloquium.
[23] Andrew W. Fitzgibbon,et al. Real-time human pose recognition in parts from single depth images , 2011, CVPR 2011.
[24] Yang Zhang,et al. Exploring Communities for Effective Location Prediction , 2015, WWW.
[25] Daniel A. Sternberg,et al. The largest human cognitive performance dataset reveals insights into the effects of lifestyle factors and aging , 2013, Front. Hum. Neurosci..
[26] Holger R. Maier,et al. Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications , 2000, Environ. Model. Softw..