| Presentation | 2023-01-29 Indoor air quality prediction using multi-reservoir echo state network with attention mechanism Wenrui Qiu, Gouhei Tanaka, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Indoor air quality (IAQ) is a critical matter of concern in terms of its impact on public health and well-being. Researchers have been trying to find better machine learning models to improve IAQ prediction. Echo state network (ESN) is a particular type of recurrent neural network (RNN), which usually uses a regression-based learning algorithm and works with a much lower training cost than other RNNs trained with a gradient-based algorithm. In this study, a novel structure of ESN with a combination of multiple reservoirs and attention mechanism is developed and employed to predict the concentrations of Particulate Matter (PM) from a long-term dataset. We compare the performance of the multi-reservoir ESN with attention mechanism with that of standard ESN, multi-reservoir ESN, and standard ESN with attention mechanism. The results show that adding the attention mechanism can significantly improve the prediction accuracy of the standard and multi-reservoir ESN. Future work will concentrate on the improvement of training speed. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Indoor Air Quality Prediction / Attention Mechanism / Machine Learning / Artificial Neural Networks / Echo State Network |
| Paper # | NLP2022-106,NC2022-90 |
| Date of Issue | 2023-01-21 (NLP, NC) |
| Conference Information | |
| Committee | NC / NLP |
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| Conference Date | 2023/1/28(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Future University Hakodate |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | NC, NLP, etc. |
| Chair | Hiroshi Yamakawa(Univ of Tokyo) / Akio Tsuneda(Kumamoto Univ.) |
| Vice Chair | Hirokazu Tanaka(Tokyo City Univ.) / Hiroyuki Torikai(Hosei Univ.) |
| Secretary | Hirokazu Tanaka(NTT) / Hiroyuki Torikai(NICT) |
| Assistant | Yoshimasa Tawatsuji(Waseda Univ.) / Tomoki Kurikawa(KMU) / Yuichi Yokoi(Nagasaki Univ.) / Yoshikazu Yamanaka(Utsunomiya Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on Nonlinear Problems |
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| Language | ENG-JTITLE |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Indoor air quality prediction using multi-reservoir echo state network with attention mechanism |
| Sub Title (in English) | |
| Keyword(1) | Indoor Air Quality Prediction |
| Keyword(2) | Attention Mechanism |
| Keyword(3) | Machine Learning |
| Keyword(4) | Artificial Neural Networks |
| Keyword(5) | Echo State Network |
| 1st Author's Name | Wenrui Qiu |
| 1st Author's Affiliation | The University of Tokyo(UTokyo) |
| 2nd Author's Name | Gouhei Tanaka |
| 2nd Author's Affiliation | The University of Tokyo(UTokyo) |
| Date | 2023-01-29 |
| Paper # | NLP2022-106,NC2022-90 |
| Volume (vol) | vol.122 |
| Number (no) | NLP-373,NC-374 |
| Page | pp.pp.135-140(NLP), pp.135-140(NC), |
| #Pages | 6 |
| Date of Issue | 2023-01-21 (NLP, NC) |