Autoencoder-based deep belief regression network for air particulate matter concentration forecasting

Application of decomposition-ensemble learning paradigm with phase space reconstruction for day-ahead PM 2.5 concentration forecasting

(2017) Mingfei Niu et al.   JOURNAL OF ENVIRONMENTAL MANAGEMENT

Deep learning architecture for air quality predictions

(2016) Xiang Li et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Deep learning approach for active classification of electrocardiogram signals

(2016) M.M. Al Rahhal et al.   INFORMATION SCIENCES

Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models

(2016) Yun Bai et al.   JOURNAL OF HYDROLOGY

Fuzzy determination of informative frequency band for bearing fault detection

(2016) Chuan Li et al.   JOURNAL OF INTELLIGENT & FUZZY SYSTEMS

Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions

(2016) Yun Bai et al.   Atmospheric Pollution Research

PM2.5 analog forecast and Kalman filter post-processing for the Community Multiscale Air Quality (CMAQ) model

(2015) Irina Djalalova et al.   ATMOSPHERIC ENVIRONMENT

Using wavelet–feedforward neural networks to improve air pollution forecasting in urban environments

(2015) Daniel Dunea et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Spatiotemporal Prediction of Fine Particulate Matter During the 2008 Northern California Wildfires Using Machine Learning

(2015) Colleen E. Reid et al.   ENVIRONMENTAL SCIENCE & TECHNOLOGY

Spatial modeling of PM2.5 concentrations with a multifactoral radial basis function neural network

(2015) Bin Zou et al.   ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

Dynamic Forecast of Daily Urban Water Consumption Using a Variable-Structure Support Vector Regression Model

(2015) Yun Bai et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM2.5

(2015) Bun Theang Ong et al.   NEURAL COMPUTING & APPLICATIONS

Prediction of particular matter concentrations by developed feed-forward neural network with rolling mechanism and gray model

(2015) Minglei Fu et al.   NEURAL COMPUTING & APPLICATIONS

Neural network forecast of daily pollution concentration using optimal meteorological data at synoptic and local scales

(2015) Ana Russo et al.   Atmospheric Pollution Research

Dynamic Forecast of Daily Urban Water Consumption Using a Variable-Structure Support Vector Regression Model

(2015) Yun Bai et al.   JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT

A review of unsupervised feature learning and deep learning for time-series modeling

(2014) Martin Längkvist et al.   PATTERN RECOGNITION LETTERS

A Multisite-Multipollutant Air Quality Index

(2013) A. Plaia et al.   ATMOSPHERIC ENVIRONMENT

Forecasting Hourly Roadside Particulate Matter in Taipei County of Taiwan Based on First-Order and One-Variable Grey Model

(2013) Tzu-Yi Pai et al.   CLEAN-Soil Air Water

One year intensive PM2.5 bound polycyclic aromatic hydrocarbons monitoring in the area of Tuscany, Italy. Concentrations, source understanding and implications

(2012) Tania Martellini et al.   ENVIRONMENTAL POLLUTION

Application of fuzzy time series models for forecasting pollution concentrations

(2012) D. Domańska et al.   EXPERT SYSTEMS WITH APPLICATIONS

An application of ARIMA model to predict submicron particle concentrations from meteorological factors at a busy roadside in Hangzhou, China

(2012) Le Jian et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Forecasting urban PM10 and PM2.5 pollution episodes in very stable nocturnal conditions and complex terrain using WRF–Chem CO tracer model

(2011) Pablo E. Saide et al.   ATMOSPHERIC ENVIRONMENT

An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations

(2010) W. Geoffrey Cobourn   ATMOSPHERIC ENVIRONMENT