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pub:projects:xpm:start2022 [2022/07/01 09:20] gjnpub:projects:xpm:start2022 [2022/07/01 09:24] (current) gjn
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 ==== Dependencies ==== ==== Dependencies ====
 The dependencies between the Work Packages in the project are presented below. The dependencies between the Work Packages in the project are presented below.
 +{{ :pub:projects:xpm:xpm-wps.png?600 |}}
  
 ===== Project team ===== ===== Project team =====
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 ===== Papers ===== ===== Papers =====
   - Davari, N., Veloso, B., Costa, G.D.A., Pereira, P.M., Ribeiro, R.P. and Gama, J., 2021. A Survey on Data-Driven Predictive Maintenance for the Railway Industry. Sensors, 21(17), p.5739., https://doi.org/10.3390/s21175739, https://www.mdpi.com/1424-8220/21/17/5739    - Davari, N., Veloso, B., Costa, G.D.A., Pereira, P.M., Ribeiro, R.P. and Gama, J., 2021. A Survey on Data-Driven Predictive Maintenance for the Railway Industry. Sensors, 21(17), p.5739., https://doi.org/10.3390/s21175739, https://www.mdpi.com/1424-8220/21/17/5739 
-  - Davari, N., Veloso, B., Ribeiro, R.P., Pereira, P.M. and Gama, J., 2021, October. Predictive maintenance based on anomaly detection using deep learning for air production units in the railway industry. In 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-10). +  - Davari, N., Veloso, B., Ribeiro, R.P., Pereira, P.M. and Gama, J., 2021, October. Predictive maintenance based on anomaly detection using deep learning for air production units in the railway industry. In 2021 IEEE 8th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 1-10). [[https://doi.org/10.1109/DSAA53316.2021.9564181]] [[https://www.researchgate.net/publication/355463810_Predictive_maintenance_based_on_anomaly_detection_using_deep_learning_for_air_production_unit_in_the_railway_industry]]
-[[https://doi.org/10.1109/DSAA53316.2021.9564181]] +
-[[https://www.researchgate.net/publication/355463810_Predictive_maintenance_based_on_anomaly_detection_using_deep_learning_for_air_production_unit_in_the_railway_industry]]+
   - Davari, N., Pashami, S., Veloso, B., Nowaczyk, S., Fan, Y., Pereira, P.M., Ribeiro, R.P. and Gama, J., 2022, A fault detection framework based on LSTM autoencoder: a case study for Volvo bus data set. IDA2022. [[https://doi.org/10.1007/978-3-031-01333-1_4]] [[https://www.researchgate.net/publication/359939634_A_fault_detection_framework_based_on_LSTM_autoencoder_a_case_study_for_Volvo_bus_data_set]]   - Davari, N., Pashami, S., Veloso, B., Nowaczyk, S., Fan, Y., Pereira, P.M., Ribeiro, R.P. and Gama, J., 2022, A fault detection framework based on LSTM autoencoder: a case study for Volvo bus data set. IDA2022. [[https://doi.org/10.1007/978-3-031-01333-1_4]] [[https://www.researchgate.net/publication/359939634_A_fault_detection_framework_based_on_LSTM_autoencoder_a_case_study_for_Volvo_bus_data_set]]
   - Sant’Ana, B., Veloso, B., and Gama, J., 2022, Predictive maintenance for wind turbines, 5th International Conference on Energy and Environment: bringing together Engineering and Economics, accepted, waiting for publication   - Sant’Ana, B., Veloso, B., and Gama, J., 2022, Predictive maintenance for wind turbines, 5th International Conference on Energy and Environment: bringing together Engineering and Economics, accepted, waiting for publication
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 ===== Tools and Datasets ===== ===== Tools and Datasets =====
- +  * Open-source implementation of Local Uncertain Explanations was created and made accessible at: [[https://github.com/sbobek/lux]] 
-open-source implementation of Local Uncertain Explanations was created and made accessible at: [[https://github.com/sbobek/lux]] +  As a result of work on the metrics of XAI, an InXAI prototype software was created and made available as an open-source tool at: [[https://github.com/sbobek/inxai]]
- +
-As a result of work on the metrics of XAI, an InXAI prototype software was created and made available as an open-source tool at: [[https://github.com/sbobek/inxai]]+
  
 Go back to -> [[pub:projects:start|projects]] Go back to -> [[pub:projects:start|projects]]
pub/projects/xpm/start2022.txt · Last modified: 2022/07/01 09:24 by gjn

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