| Time series forecasting using a deep belief network with restricted Boltzmann machines T Kuremoto, S Kimura, K Kobayashi, M Obayashi Neurocomputing 137, 47-56, 2014 | 600 | 2014 |
| Enhanced decision making mechanism of rule-based genetic network programming for creating stock trading signals S Mabu, K Hirasawa, M Obayashi, T Kuremoto Expert systems with applications 40 (16), 6311-6320, 2013 | 61 | 2013 |
| Time series forecasting using restricted Boltzmann machine T Kuremoto, S Kimura, K Kobayashi, M Obayashi Emerging Intelligent Computing Technology and Applications: 8th …, 2012 | 57 | 2012 |
| Time series prediction using DBN and ARIMA T Hirata, T Kuremoto, M Obayashi, S Mabu, K Kobayashi 2015 International Conference on Computer Application Technologies, 24-29, 2015 | 54 | 2015 |
| Ensemble learning of rule-based evolutionary algorithm using multi-layer perceptron for supporting decisions in stock trading problems S Mabu, M Obayashi, T Kuremoto Applied soft computing 36, 357-367, 2015 | 46 | 2015 |
| Forecast chaotic time series data by DBNs T Kuremoto, M Obayashi, K Kobayashi, T Hirata, S Mabu 2014 7th International Congress on Image and Signal Processing, 1130-1135, 2014 | 43 | 2014 |
| A visual system of citrus picking robot using convolutional neural networks YP Liu, CH Yang, H Ling, S Mabu, T Kuremoto 2018 5th international conference on systems and informatics (ICSAI), 344-349, 2018 | 29 | 2018 |
| Nonlinear prediction by reinforcement learning T Kuremoto, M Obayashi, K Kobayashi Advances in Intelligent Computing: International Conference on Intelligent …, 2005 | 22 | 2005 |
| Nonlinear prediction by reinforcement learning T Kuremoto, M Obayashi, K Kobayashi Advances in Intelligent Computing: International Conference on Intelligent …, 2005 | 22 | 2005 |
| Parameterless-Growing-SOM and its application to a voice instruction learning system T Kuremoto, T Komoto, K Kobayashi, M Obayashi Journal of Robotics 2010, 2010 | 21 | 2010 |
| Adaptive swarm behavior acquisition by a neuro‐fuzzy system and reinforcement learning algorithm T Kuremoto, M Obayashi, K Kobayashi International Journal of Intelligent Computing and Cybernetics 2 (4), 724-744, 2009 | 21 | 2009 |
| A reinforcement learning system for swarm behaviors T Kuremoto, M Obayashi, K Kobayashi, H Adachi, K Yoneda 2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008 | 19 | 2008 |
| A learning fuzzy Petri net model L Feng, M Obayashi, T Kuremoto, K Kobayashi IEEJ transactions on electrical and electronic engineering 7 (3), 274-282, 2012 | 18 | 2012 |
| A functional model of limbic system of brain T Kuremoto, T Ohta, K Kobayashi, M Obayashi International Conference on Brain Informatics, 135-146, 2009 | 17 | 2009 |
| A dynamic associative memory system by adopting an amygdala model T Kuremoto, T Ohta, K Kobayashi, M Obayashi Artificial Life and robotics 13, 478-482, 2009 | 17 | 2009 |
| A meta-learning method based on temporal difference error K Kobayashi, H Mizoue, T Kuremoto, M Obayashi Neural Information Processing: 16th International Conference, ICONIP 2009 …, 2009 | 17 | 2009 |
| A gesture recognition system with retina-V1 model and one-pass dynamic programming T Kuremoto, Y Kinoshita, L Feng, S Watanabe, K Kobayashi, M Obayashi Neurocomputing 116, 291-300, 2013 | 15 | 2013 |
| Cooperative behavior acquisition in multi-agent reinforcement learning system using attention degree K Kobayashi, T Kurano, T Kuremoto, M Obayashi Neural Information Processing: 19th International Conference, ICONIP 2012 …, 2012 | 15 | 2012 |
| A self-organized fuzzy-neuro reinforcement learning system for continuous state space for autonomous robots M Obayashi, T Kuremoto, K Kobayashi 2008 International Conference on Computational Intelligence for Modelling …, 2008 | 15 | 2008 |
| Neural forecasting systems T Kuremoto, M Obayashi, K Kobayashi Reinforcement Learning, 2008 | 15 | 2008 |
Kunikazu KobayashiProfessor at Aichi Prefectural University and Vice President at RINGVerified email at ist.aichi-pu.ac.jp
