A time series forecasting based multi-criteria methodology for air quality prediction
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Guido Sciavicco | Estrella Lucena-Sánchez | Joanna Kamińska | Raquel Espinosa | José Palma | Fernando Jiménez | G. Sciavicco | J. Kamińska | E. Lucena-Sánchez | J. Palma | Raquel Espinosa | Fernando Jiménez | José Palma
[1] Majid Ahmadi,et al. Efficient hardware implementation of the hyperbolic tangent sigmoid function , 2009, 2009 IEEE International Symposium on Circuits and Systems.
[2] Ola M. Surakhi,et al. On the Ensemble of Recurrent Neural Network for Air Pollution Forecasting: Issues and Challenges , 2020 .
[3] A. Masih,et al. Machine learning algorithms in air quality modeling , 2019 .
[4] Claudio Moraga,et al. The Influence of the Sigmoid Function Parameters on the Speed of Backpropagation Learning , 1995, IWANN.
[5] Suat Özdemir,et al. A deep learning model for air quality prediction in smart cities , 2017, 2017 IEEE International Conference on Big Data (Big Data).
[6] Javier Del Ser,et al. The role of local urban traffic and meteorological conditions in air pollution: A data-based case study in Madrid, Spain , 2016 .
[7] Vladimir Vapnik,et al. Support-vector networks , 2004, Machine Learning.
[8] Carsten Maple,et al. Comparative Analysis of Machine Learning Techniques for Predicting Air Quality in Smart Cities , 2019, IEEE Access.
[9] Shikha Gupta,et al. Linear and nonlinear modeling approaches for urban air quality prediction. , 2012, The Science of the total environment.
[10] Chih-Hung Wu,et al. Air quality prediction by neuro-fuzzy modeling approach , 2020, Appl. Soft Comput..
[11] Baowei Wang,et al. An air quality forecasting model based on improved convnet and RNN , 2021, Soft Computing.
[12] Derya Soydaner,et al. A Comparison of Optimization Algorithms for Deep Learning , 2020, Int. J. Pattern Recognit. Artif. Intell..
[13] Enrico Marzano,et al. Assessing the Role of Temporal Information in Modelling Short-Term Air Pollution Effects Based on Traffic and Meteorological Conditions: A Case Study in Wrocław , 2019, ADBIS.
[14] Fang Liu,et al. Air Pollution Forecasting Using a Deep Learning Model Based on 1D Convnets and Bidirectional GRU , 2019, IEEE Access.
[15] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[16] J. Kamińska,et al. A random forest partition model for predicting NO2 concentrations from traffic flow and meteorological conditions. , 2019, The Science of the total environment.
[17] Yoshua Bengio,et al. Deep Sparse Rectifier Neural Networks , 2011, AISTATS.
[18] Szymon Szewrański,et al. Decision Support System in Public Transport Planning for Promoting Urban Adaptation to Climate Change , 2019, IOP Conference Series: Materials Science and Engineering.
[19] Mohamed Elwekeil,et al. Development of an Optimized Regression Model to Predict Blast-Driven Ground Vibrations , 2021, IEEE Access.
[20] R. Vinayakumar,et al. DeepAirNet: Applying Recurrent Networks for Air Quality Prediction , 2018 .
[21] C. Tan,et al. Monitoring of heat-induced carcinogenic compounds (3-monochloropropane-1,2-diol esters and glycidyl esters) in fries , 2020, Scientific Reports.
[22] Saeid Baroutian,et al. Forecasting Extreme PM10 Concentrations Using Artificial Neural Networks , 2012 .
[23] Yue-Shan Chang,et al. Ensemble multifeatured deep learning models for air quality forecasting , 2021 .
[24] Wei Xu,et al. Spatial-temporal prediction of air quality based on recurrent neural networks , 2019, HICSS.
[25] Arnaud Doucet,et al. On the Impact of the Activation Function on Deep Neural Networks Training , 2019, ICML.
[26] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[27] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[28] Kıymet Kaya,et al. Deep Flexible Sequential (DFS) Model for Air Pollution Forecasting , 2020, Scientific Reports.
[29] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[30] Zhongfei Zhang,et al. Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-Grained Air Quality , 2017, IEEE Transactions on Knowledge and Data Engineering.
[31] Graham W. Taylor,et al. Forecasting air quality time series using deep learning , 2018, Journal of the Air & Waste Management Association.
[32] Cyrus Shahabi,et al. Exploiting spatiotemporal patterns for accurate air quality forecasting using deep learning , 2018, SIGSPATIAL/GIS.
[33] H. Jaap van den Herik,et al. Air Quality Forecast through Integrated Data Assimilation and Machine Learning , 2019, ICAART.
[34] Qi Li,et al. A Spatiotemporal Prediction Framework for Air Pollution Based on Deep RNN , 2017 .
[36] Weidong Zhang,et al. Prediction of 24-hour-average PM(2.5) concentrations using a hidden Markov model with different emission distributions in Northern California. , 2013, The Science of the total environment.
[37] Shi-Jinn Horng,et al. Deep Air Quality Forecasting Using Hybrid Deep Learning Framework , 2018, IEEE Transactions on Knowledge and Data Engineering.
[38] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[39] Fernando Jiménez,et al. Simple Versus Composed Temporal Lag Regression with Feature Selection, with an Application to Air Quality Modeling , 2020, 2020 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS).
[40] Deep Learning Techniques for Air Pollution , 2021, 2021 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS).
[41] Anirban Mitra,et al. Estimation of Air Quality Index from Seasonal Trends Using Deep Neural Network , 2018, ICANN.
[42] Xianfeng Zhang,et al. Evaluation of Different Machine Learning Approaches to Forecasting PM2.5 Mass Concentrations , 2019, Aerosol and Air Quality Research.
[43] Roy M. Harrison,et al. Regression modelling of hourly NOx and NO2 concentrations in urban air in London , 1997 .
[44] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[45] Sarbani Roy,et al. Long-term time-series pollution forecast using statistical and deep learning methods , 2021, Neural Comput. Appl..
[46] Jinchang Ren,et al. Urban PM2.5 Concentration Prediction via Attention-Based CNN–LSTM , 2020, Applied Sciences.
[47] Mehmet Taştan,et al. Real-Time Monitoring of Indoor Air Quality with Internet of Things-Based E-Nose , 2019, Applied Sciences.
[48] Onur Avci,et al. 1D Convolutional Neural Networks and Applications: A Survey , 2019, Mechanical Systems and Signal Processing.