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Sulfur dioxide emissions in Portugal: Prediction, estimation and air quality regulation using machine learning

https://doi.org/10.1016/j.jclepro.2021.128358

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inferredcites →https://doi.org/10.1002/2013jd021185openalex-snapshot

Transport of NOx in East Asia identified by satellite and in situ measurements and Lagrangian particle dispersion model simulations

inferredcites →https://doi.org/10.1002/2016jd025564openalex-snapshot

Potential impacts of urban land expansion on Asian airborne pollutant outflows

inferredcites →https://doi.org/10.1002/2017ea000287openalex-snapshot

Sensitivity of simulated convection‐driven stratosphere‐troposphere exchange in WRF‐Chem to the choice of physical and chemical parameterization

inferredcites →https://doi.org/10.1002/jae.1137openalex-snapshot

Large Bayesian vector auto regressions

inferredcites →https://doi.org/10.1006/jcss.1997.1504openalex-snapshot

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

inferredcites →https://doi.org/10.1007/978-0-387-84858-7openalex-snapshot

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

inferredcites →https://doi.org/10.1007/978-1-4419-9782-1openalex-snapshot

Targeted Learning: Causal Inference for Observational and Experimental Data

inferredcites →https://doi.org/10.1007/978-3-319-98282-3openalex-snapshot

Time Series Econometrics: Learning Through Replication

inferredcites →https://doi.org/10.1007/978-3-540-28650-9_4openalex-snapshot

Gaussian Processes in Machine Learning

inferredcites →https://doi.org/10.1007/bf00058655openalex-snapshot

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inferredcites →https://doi.org/10.1007/s00477-009-0361-8openalex-snapshot

ARIMA forecasting of ambient air pollutants (O3, NO, NO2 and CO)

inferredcites →https://doi.org/10.1007/s00521-019-04432-1openalex-snapshot

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inferredcites →https://doi.org/10.1007/s10661-015-4697-xopenalex-snapshot

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inferredcites →https://doi.org/10.1007/s11269-020-02704-3openalex-snapshot

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inferredcites →https://doi.org/10.1007/s11356-016-7812-9openalex-snapshot

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inferredcites →https://doi.org/10.1007/s40808-018-0493-2openalex-snapshot

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inferredcites →https://doi.org/10.1007/s40808-018-0530-1openalex-snapshot

Seasonal prediction of particulate matter over the steel city of India using neural network models

inferredcites →https://doi.org/10.1016/0031-3203(93)90115-dopenalex-snapshot

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inferredcites →https://doi.org/10.1016/0098-1354(93)80080-7openalex-snapshot

Alternatives to neural networks for inferential measurement

inferredcites →https://doi.org/10.1016/0169-2070(86)90059-2openalex-snapshot

Long-range forecasting: From crystal ball to computer

inferredcites →https://doi.org/10.1016/0169-2070(91)90016-oopenalex-snapshot

Time series: A biostatistical introduction

inferredcites →https://doi.org/10.1016/0305-0483(86)90013-7openalex-snapshot

A pragmatic view of accuracy measurement in forecasting

inferredcites →https://doi.org/10.1016/0377-2217(85)90321-2openalex-snapshot

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inferredcites →https://doi.org/10.1016/0960-1686(90)90340-sopenalex-snapshot

Numerical simulation of wet scavenging of air pollutants—II. Modeling of rain composition at the ground

inferredcites →https://doi.org/10.1016/j.apr.2016.01.004openalex-snapshot

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

inferredcites →https://doi.org/10.1016/j.apr.2020.02.022openalex-snapshot

Hourly PM2.5 concentration forecasting based on feature extraction and stacking-driven ensemble model for the winter of the Beijing-Tianjin-Hebei area

inferredcites →https://doi.org/10.1016/j.atmosenv.2005.04.027openalex-snapshot

Fully coupled “online” chemistry within the WRF model

inferredcites →https://doi.org/10.1016/j.atmosenv.2006.09.045openalex-snapshot

An integrated MM5–CMAQ modeling approach for assessing trans-boundary PM10 contribution to the host city of 2008 Olympic summer games—Beijing, China

inferredcites →https://doi.org/10.1016/j.atmosenv.2006.10.053openalex-snapshot

Characterizations of chemical oxidants in Mexico City: A regional chemical dynamical model (WRF-Chem) study

inferredcites →https://doi.org/10.1016/j.atmosenv.2007.10.041openalex-snapshot

Management of air quality monitoring using principal component and cluster analysis—Part II: CO, NO2 and O3

inferredcites →https://doi.org/10.1016/j.atmosenv.2007.10.044openalex-snapshot

Management of air quality monitoring using principal component and cluster analysis—Part I: SO2 and PM10

inferredcites →https://doi.org/10.1016/j.atmosenv.2014.04.051openalex-snapshot

Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering

inferredcites →https://doi.org/10.1016/j.atmosenv.2015.02.030openalex-snapshot

Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation

inferredcites →https://doi.org/10.1016/j.atmosenv.2015.07.022openalex-snapshot

Application of WRF/Chem over East Asia: Part I. Model evaluation and intercomparison with MM5/CMAQ

inferredcites →https://doi.org/10.1016/j.atmosenv.2015.12.052openalex-snapshot

Air quality simulation of NOX over the tropical coastal city Chennai in southern India with FLEXPART-WRF

inferredcites →https://doi.org/10.1016/j.atmosenv.2018.07.058openalex-snapshot

Spatial estimation of urban air pollution with the use of artificial neural network models

inferredcites →https://doi.org/10.1016/j.chemosphere.2005.10.031openalex-snapshot

Seasonal variation of air pollution index: Hong Kong case study

inferredcites →https://doi.org/10.1016/j.chest.2018.10.041openalex-snapshot

Air Pollution and Noncommunicable Diseases

inferredcites →https://doi.org/10.1016/j.csda.2017.11.003openalex-snapshot

A note on the validity of cross-validation for evaluating autoregressive time series prediction

inferredcites →https://doi.org/10.1016/j.econlet.2015.11.017openalex-snapshot

Forecasting macroeconomic variables in data-rich environments

inferredcites →https://doi.org/10.1016/j.envint.2007.12.020openalex-snapshot

An online air pollution forecasting system using neural networks

inferredcites →https://doi.org/10.1016/j.envint.2020.105954openalex-snapshot

Air pollution, physical activity and health: A mapping review of the evidence

inferredcites →https://doi.org/10.1016/j.envpol.2017.08.114openalex-snapshot

Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation

inferredcites →https://doi.org/10.1016/j.envsci.2004.12.006openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.envsoft.2004.04.006openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.ijforecast.2006.03.001openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.ijforecast.2015.12.003openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.jaerosci.2020.105630openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.jclepro.2016.09.145openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.jclepro.2017.11.160openalex-snapshot

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Spatially and temporally explicit life cycle global warming, eutrophication, and acidification impacts from corn production in the U.S. Midwest

inferredcites →https://doi.org/10.1016/j.jeconom.2005.01.015openalex-snapshot

Evaluating latent and observed factors in macroeconomics and finance

inferredcites →https://doi.org/10.1016/j.jeconom.2005.11.014openalex-snapshot

General-to-specific or specific-to-general modelling? An opinion on current econometric terminology

inferredcites →https://doi.org/10.1016/j.jeconom.2008.08.010openalex-snapshot

Forecasting economic time series using targeted predictors

inferredcites →https://doi.org/10.1016/j.jeconom.2013.04.017openalex-snapshot

Complete subset regressions

inferredcites →https://doi.org/10.1016/j.jedc.2015.03.004openalex-snapshot

Complete subset regressions with large-dimensional sets of predictors

inferredcites →https://doi.org/10.1016/j.jhazmat.2008.05.056openalex-snapshot

Impact of nocturnal planetary boundary layer on urban air pollutants: Measurements from a 250-m tower over Tianjin, China

inferredcites →https://doi.org/10.1016/j.microc.2011.03.010openalex-snapshot

Air pollution from traffic emissions in Oporto, Portugal: Health and environmental implications

inferredcites →https://doi.org/10.1016/j.neucom.2012.06.003openalex-snapshot

Identification of significant factors for air pollution levels using a neural network based knowledge discovery system

inferredcites →https://doi.org/10.1016/j.partic.2017.10.005openalex-snapshot

Comparative evaluation of the impact of GRAPES and MM5 meteorology on CMAQ prediction over Pearl River Delta, China

inferredcites →https://doi.org/10.1016/j.petrol.2018.11.076openalex-snapshot

Insights to fracture stimulation design in unconventional reservoirs based on machine learning modeling

inferredcites →https://doi.org/10.1016/j.rser.2019.01.049openalex-snapshot

Air pollution terrain nexus: A review considering energy generation and consumption

inferredcites →https://doi.org/10.1016/j.scitotenv.2005.01.037openalex-snapshot

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inferredcites →https://doi.org/10.1016/j.scitotenv.2006.10.014openalex-snapshot

Air quality assessment for Portugal

inferredcites →https://doi.org/10.1016/j.scitotenv.2018.06.281openalex-snapshot

Air pollution: A public health approach for Portugal

inferredcites →https://doi.org/10.1016/j.scitotenv.2018.10.024openalex-snapshot

Removal of PM2.5 and secondary inorganic aerosols in the North China Plain by dry deposition

inferredcites →https://doi.org/10.1016/j.scitotenv.2020.141618openalex-snapshot

Assessment and management of lake eutrophication: A case study in Lake Erhai, China

inferredcites →https://doi.org/10.1016/j.snb.2009.08.041openalex-snapshot

CO, NO2 and NOx urban pollution monitoring with on-field calibrated electronic nose by automatic bayesian regularization

inferredcites →https://doi.org/10.1016/s0074-6142(08)x6003-6openalex-snapshot

The Upper Atmosphere Meteorology and Physics

inferredcites →https://doi.org/10.1016/s0169-2070(03)00068-2openalex-snapshot

How costly is it to ignore breaks when forecasting the direction of a time series?

inferredcites →https://doi.org/10.1016/s1352-2310(03)00047-5openalex-snapshot

Year-long, high-resolution, urban airshed modelling: verification of TAPM predictions of smog and particles in Melbourne, Australia

inferredcites →https://doi.org/10.1016/s1352-2310(98)00184-8openalex-snapshot

Validation of the lagrangian particle dispersion model FLEXPART against large-scale tracer experiment data

inferredcites →https://doi.org/10.1017/cbo9781107049994openalex-snapshot

Forecasting, Structural Time Series Models and the Kalman Filter

inferredcites →https://doi.org/10.1021/es020793kopenalex-snapshot

Environmental Costs of Freshwater Eutrophication in England and Wales

inferredcites →https://doi.org/10.1023/a:1007617005950openalex-snapshot

Unsupervised Learning by Probabilistic Latent Semantic Analysis

inferredcites →https://doi.org/10.1023/a:1010933404324openalex-snapshot

Random Forests

inferredcites →https://doi.org/10.1023/a:1018054314350openalex-snapshot

Bagging Predictors

inferredcites →https://doi.org/10.1038/s41569-020-0371-2openalex-snapshot

Environmental determinants of cardiovascular disease: lessons learned from air pollution

inferredcites →https://doi.org/10.1057/jors.2014.103openalex-snapshot

A better measure of relative prediction accuracy for model selection and model estimation

inferredcites →https://doi.org/10.1057/jors.2014.124openalex-snapshot

Erratum: A better measure of relative prediction accuracy for model selection and model estimation

inferredcites →https://doi.org/10.1061/9780784479162.095openalex-snapshot

Comparison of Performance on Watershed-Scale Precipitation between WRF and MM5

inferredcites →https://doi.org/10.1080/00401706.1970.10488634openalex-snapshot

Ridge Regression: Biased Estimation for Nonorthogonal Problems

inferredcites →https://doi.org/10.1080/00401706.1989.10488562openalex-snapshot

TIMESLAB: A Time Series Analysis Laboratory

inferredcites →https://doi.org/10.1080/07350015.1986.10509491openalex-snapshot

Forecasting With Bayesian Vector Autoregressions—Five Years of Experience

inferredcites →https://doi.org/10.1080/07474938408800053openalex-snapshot

Forecasting and conditional projection using realistic prior distributions

inferredcites →https://doi.org/10.1080/10473289.2005.10464632openalex-snapshot

Evaluation of Compliance with National Legislation on Emissions in Portugal

inferredcites →https://doi.org/10.1080/10807039.2017.1410427openalex-snapshot

The modeling and health risk assessment of PM2.5 from Tema Oil Refinery

inferredcites →https://doi.org/10.1080/10962247.2017.1292968openalex-snapshot

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan, China

inferredcites →https://doi.org/10.1080/15287390600884990openalex-snapshot

Air Quality Improvements Using European Environment Policies: A Case Study of SO2in a Coastal Region in Portugal

inferredcites →https://doi.org/10.1093/biomet/64.1.29openalex-snapshot

Asymptotics For and Against Cross-Validation

inferredcites →https://doi.org/10.1093/biomet/75.2.335openalex-snapshot

Testing for a Unit Root in Time Series Regression

inferredcites →https://doi.org/10.1093/biomet/asr043openalex-snapshot

Square-Root Lasso: Pivotal Recovery of Sparse Signals via Conic Programming

inferredcites →https://doi.org/10.1093/eurheartj/ehu458openalex-snapshot

Expert position paper on air pollution and cardiovascular disease

inferredcites →https://doi.org/10.1093/oso/9780195301649.003.0004openalex-snapshot

Univariate Time-Series Analysis

inferredcites →https://doi.org/10.1109/access.2019.2944755openalex-snapshot

The Forecasting of PM2.5 Using a Hybrid Model Based on Wavelet Transform and an Improved Deep Learning Algorithm

inferredcites →https://doi.org/10.1109/cvpr.2016.110openalex-snapshot

Social LSTM: Human Trajectory Prediction in Crowded Spaces

inferredcites →https://doi.org/10.1109/iceeot.2016.7755040openalex-snapshot

Stroke in-patients' transfer to the ICU using ensemble based model

inferredcites →https://doi.org/10.1109/soli.2015.7367615openalex-snapshot

A comprehensive evaluation of air pollution prediction improvement by a machine learning method

inferredcites →https://doi.org/10.1109/tsmc.1976.5408784openalex-snapshot

The Distance-Weighted k-Nearest-Neighbor Rule

inferredcites →https://doi.org/10.1109/tsmc.1978.4309958openalex-snapshot

A Note on Distance-Weighted k-Nearest Neighbor Rules

inferredcites →https://doi.org/10.1111/1468-0262.00273openalex-snapshot

Determining the Number of Factors in Approximate Factor Models

inferredcites →https://doi.org/10.1111/ectj.12097openalex-snapshot

Double/debiased machine learning for treatment and structural parameters

inferredcites →https://doi.org/10.1111/gcb.14893openalex-snapshot

Global change biology: A primer

inferredcites →https://doi.org/10.1111/j.1467-985x.2010.00646_6.xopenalex-snapshot

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

inferredcites →https://doi.org/10.1111/j.1467-9868.2005.00503.xopenalex-snapshot

Regularization and Variable Selection Via the Elastic Net

inferredcites →https://doi.org/10.1111/j.1467-9892.1982.tb00349.xopenalex-snapshot

AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM

inferredcites →https://doi.org/10.1111/j.1538-4616.2007.00014.xopenalex-snapshot

Why Has U.S. Inflation Become Harder to Forecast?

inferredcites →https://doi.org/10.1111/j.1600-0587.2008.05742.xopenalex-snapshot

BIOMOD – a platform for ensemble forecasting of species distributions

inferredcites →https://doi.org/10.1111/j.2517-6161.1996.tb02080.xopenalex-snapshot

Regression Shrinkage and Selection Via the Lasso

inferredcites →https://doi.org/10.1115/1.3662552openalex-snapshot

A New Approach to Linear Filtering and Prediction Problems

inferredcites →https://doi.org/10.1126/science.1176985openalex-snapshot

Nitrous Oxide (N 2 O): The Dominant Ozone-Depleting Substance Emitted in the 21st Century

inferredcites →https://doi.org/10.1142/s0129065795000251openalex-snapshot

NONLINEAR GATED EXPERTS FOR TIME SERIES: DISCOVERING REGIMES AND AVOIDING OVERFITTING

inferredcites →https://doi.org/10.1145/1015330.1015432openalex-snapshot

Ensemble selection from libraries of models

inferredcites →https://doi.org/10.1145/3209978.3210006openalex-snapshot

Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

inferredcites →https://doi.org/10.1155/2017/3514743openalex-snapshot

Recognizing Dew as an Indicator and an Improver of Near-Surface Air Quality

inferredcites →https://doi.org/10.1161/cir.0b013e3181dbece1openalex-snapshot

Particulate Matter Air Pollution and Cardiovascular Disease

inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot

Long Short-Term Memory

inferredcites →https://doi.org/10.1175/1520-0450(1995)034<2149:ieiwfa>2.0.co;2openalex-snapshot

Interpolation Errors in Wind Fields as a Function of Spatial and Temporal Resolution and Their Impact on Different Types of Kinematic Trajectories

inferredcites →https://doi.org/10.1175/1520-0450(2002)041<0971:smtifg>2.0.co;2openalex-snapshot

Simple Modifications to Improve Fifth-Generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model Performance for the Phoenix, Arizona, Metropolitan Area

inferredcites →https://doi.org/10.1175/2007jamc1624.1openalex-snapshot

Urbanization Impacts on the Climate in Europe: Numerical Experiments by the PSU–NCAR Mesoscale Model (MM5)

inferredcites →https://doi.org/10.1175/2011jcli3674.1openalex-snapshot

Parameterization-Induced Error Characteristics of MM5 and WRF Operated in Climate Mode over the Alpine Region: An Ensemble-Based Analysis

inferredcites →https://doi.org/10.1175/jcli-d-13-00517.1openalex-snapshot

Moisture Sources of Semiarid Grassland in China Using the Lagrangian Particle Model FLEXPART

inferredcites →https://doi.org/10.1177/2047487316653709openalex-snapshot

2016 European Guidelines on cardiovascular disease prevention in clinical practice

inferredcites →https://doi.org/10.1186/s12889-017-4914-3openalex-snapshot

A systematic review of data mining and machine learning for air pollution epidemiology

inferredcites →https://doi.org/10.1186/s12889-017-4938-8openalex-snapshot

Success and failure in narrowing the disability employment gap: comparing levels and trends across Europe 2002–2014

inferredcites →https://doi.org/10.1198/016214506000000735openalex-snapshot

The Adaptive Lasso and Its Oracle Properties

inferredcites →https://doi.org/10.1201/b19138-6openalex-snapshot

Life Cycle Impact Assessment

inferredcites →https://doi.org/10.1214/009053604000000067openalex-snapshot

Least angle regression

inferredcites →https://doi.org/10.1214/07-aos582openalex-snapshot

Lasso-type recovery of sparse representations for high-dimensional data

inferredcites →https://doi.org/10.1214/08-aos625openalex-snapshot

On the adaptive elastic-net with a diverging number of parameters

inferredcites →https://doi.org/10.1214/09-ss054openalex-snapshot

A survey of cross-validation procedures for model selection

inferredcites →https://doi.org/10.1214/17-aos1549openalex-snapshot

High-dimensional asymptotics of prediction: Ridge regression and classification

inferredcites →https://doi.org/10.1257/jep.31.2.87openalex-snapshot

Machine Learning: An Applied Econometric Approach

inferredcites →https://doi.org/10.14505//jemt.10.7(39).16openalex-snapshot

Analyzing the Performance Criteria of ARMA Model for Air Quality Forecasting in Jakarta

inferredcites →https://doi.org/10.1641/0006-3568(2003)053[0357:npitnu]2.0.co;2openalex-snapshot

Nitrogen Pollution in the Northeastern United States: Sources, Effects, and Management Options

inferredcites →https://doi.org/10.17159/2410-972x/2016/v26n2a4openalex-snapshot

Ambient air pollution: a global assessment of exposure and burden of disease

inferredcites →https://doi.org/10.18653/v1/d15-1166openalex-snapshot

Effective Approaches to Attention-based Neural Machine Translation

inferredcites →https://doi.org/10.1920/wp.cem.2017.2817openalex-snapshot

Double/debiased machine learning for treatment and structural parameters

inferredcites →https://doi.org/10.2202/1544-6115.1260openalex-snapshot

Supervised Detection of Conserved Motifs in DNA Sequences with Cosmo

inferredcites →https://doi.org/10.2202/1544-6115.1309openalex-snapshot

Super Learner

inferredcites →https://doi.org/10.2202/1557-4679.1127openalex-snapshot

Why Match? Investigating Matched Case-Control Study Designs with Causal Effect Estimation

inferredcites →https://doi.org/10.2307/1271436openalex-snapshot

Ridge Regression: Biased Estimation for Nonorthogonal Problems

inferredcites →https://doi.org/10.2307/1912517openalex-snapshot

Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root

inferredcites →https://doi.org/10.2307/1912791openalex-snapshot

Investigating Causal Relations by Econometric Models and Cross-spectral Methods

inferredcites →https://doi.org/10.2307/2288003openalex-snapshot

Classification and Regression Trees.

inferredcites →https://doi.org/10.2307/2346997openalex-snapshot

Some Recent Advances in Forecasting and Control

inferredcites →https://doi.org/10.2307/2583225openalex-snapshot

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inferredcites →https://doi.org/10.2307/2985674openalex-snapshot

Some Recent Advances in Forecasting and Control

inferredcites →https://doi.org/10.2307/2988075openalex-snapshot

Long Range Forecasting (From Crystal Ball to Computer).

inferredcites →https://doi.org/10.24963/ijcai.2017/366openalex-snapshot

A Dual-Stage Attention-Based Recurrent Neural Network for Time Series Prediction

inferredcites →https://doi.org/10.3150/11-bej410openalex-snapshot

Least Squares After Model Selection in High-Dimensional Sparse Models

inferredcites →https://doi.org/10.3150/14-bej609openalex-snapshot

Ridge regression and asymptotic minimax estimation over spheres of growing dimension

inferredcites →https://doi.org/10.3155/1047-3289.57.9.1032openalex-snapshot

Development of a Local Carbon Dioxide Emissions Inventory Based on Energy Demand and Waste Production

inferredcites →https://doi.org/10.3386/w1202openalex-snapshot

Forecasting and Conditional Projection Using Realistic Prior Distributions

inferredcites →https://doi.org/10.3390/app10010014openalex-snapshot

Prediction of Ambient PM2.5 Concentrations Using a Correlation Filtered Spatial-Temporal Long Short-Term Memory Model

inferredcites →https://doi.org/10.3390/atmos11030253openalex-snapshot

Characteristics of Air Pollution and Their Relationship with Meteorological Parameters: Northern Versus Southern Cities of China

inferredcites →https://doi.org/10.3390/en13246601openalex-snapshot

Prediction of Sorption Processes Using the Deep Learning Methods (Long Short-Term Memory)

inferredcites →https://doi.org/10.3390/math8101799openalex-snapshot

Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods

inferredcites →https://doi.org/10.3850/978-981-09-5247-1_017openalex-snapshot

Methods to Avoid Over-Fitting and Under-Fitting in Supervised Machine Learning (Comparative Study)

inferredcites →https://doi.org/10.4225/08/58615bcfb87dbopenalex-snapshot

The air pollution model (TAPM) version 3. Part 1. Technical description

inferredcites →https://doi.org/10.48550/arxiv.1402.1128openalex-snapshot

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