相关参考文献
注意：仅列出部分参考文献，下载原文获取全部文献信息。Ambient air pollutant monitoring and analysis protocol for low and middle income countries: An element of comprehensive urban air quality management framework
Sunil Gulia et al.
ATMOSPHERIC ENVIRONMENT (2020)
Artificial intelligence based ensemble model for prediction of vehicular traffic noise
Vahid Nourani et al.
ENVIRONMENTAL RESEARCH (2020)
Estimating Daily PM2.5 and PM10 over Italy Using an Ensemble Model
Alexandra Shtein et al.
ENVIRONMENTAL SCIENCE & TECHNOLOGY (2020)
An emotional artificial neural network for prediction of vehicular traffic noise
Vahid Nourani et al.
SCIENCE OF THE TOTAL ENVIRONMENT (2020)
Hourly PM2.5 concentration forecasting based on feature extraction and stacking-driven ensemble model for the winter of the Beijing-Tianjin-Hebei area
Wei Sun et al.
ATMOSPHERIC POLLUTION RESEARCH (2020)
Predicting Fine Particulate Matter (PM2.5) in the Greater London Area: An Ensemble Approach using Machine Learning Methods
Mahdieh Danesh Yazdi et al.
REMOTE SENSING (2020)
Applying machine learning methods in managing urban concentrations of traffic-related particulate matter (PM10 and PM2.5)
A. Suleiman et al.
ATMOSPHERIC POLLUTION RESEARCH (2019)
Vehicular traffic noise prediction and propagation modelling using neural networks and geospatial information system
Ahmed Abdulkareem Ahmed et al.
ENVIRONMENTAL MONITORING AND ASSESSMENT (2019)
Neural network predictions of pollutant emissions from open burning of crop residues: Application to air quality forecasts in southern China
Xu Feng et al.
ATMOSPHERIC ENVIRONMENT (2019)
Air quality modelling using long short-term memory (LSTM) over NCT-Delhi, India
Mrigank Krishan et al.
AIR QUALITY ATMOSPHERE AND HEALTH (2019)
Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area
Piotr S. Maciag et al.
ENVIRONMENTAL MODELLING & SOFTWARE (2019)
Multi-station artificial intelligence based ensemble modeling of reference evapotranspiration using pan evaporation measurements
Vahid Nourani et al.
JOURNAL OF HYDROLOGY (2019)
A comparison between the application of empirical and ANN methods for estimation of daily global solar radiation in Iran
Babak Jahani et al.
THEORETICAL AND APPLIED CLIMATOLOGY (2019)
Modeling of CO Emissions from Traffic Vehicles Using Artificial Neural Networks
Omer Saud Azeez et al.
APPLIED SCIENCES-BASEL (2019)
Predicting compressive strength of lightweight foamed concrete using extreme learning machine model
Zaher Mundher Yaseen et al.
ADVANCES IN ENGINEERING SOFTWARE (2018)
Earthfill dam seepage analysis using ensemble artificial intelligence based modeling
Elnaz Sharghi et al.
JOURNAL OF HYDROINFORMATICS (2018)
Evaluation of SVM, ELM and four tree-based ensemble models for predicting daily reference evapotranspiration using limited meteorological data in different climates of China
Junliang Fan et al.
AGRICULTURAL AND FOREST METEOROLOGY (2018)
Comparing different methods for statistical modeling of particulate matter in Tehran, Iran
Vahid Mehdipour et al.
AIR QUALITY ATMOSPHERE AND HEALTH (2018)
Wastewater treatment plant performance analysis using artificial intelligence - an ensemble approach
Vahid Nourani et al.
WATER SCIENCE AND TECHNOLOGY (2018)
A satellite-based model for estimating PM2.5 concentration in a sparsely populated environment using soft computing techniques
Bijan Yeganeh et al.
ENVIRONMENTAL MODELLING & SOFTWARE (2017)
Development of ANFIS models for air quality forecasting and input optimization for reducing the computational cost and time
Kanchan Prasad et al.
ATMOSPHERIC ENVIRONMENT (2016)
Hybrid Neural Networks and Boosted Regression Tree Models for Predicting Roadside Particulate Matter
A. Suleiman et al.
ENVIRONMENTAL MODELING & ASSESSMENT (2016)
Prediction models for performance and emissions of a dual fuel CI engine using ANFIS
A. Adarsh Rai et al.
SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES (2015)
Modeling daily soil temperature using data-driven models and spatial distribution
Sungwon Kim et al.
THEORETICAL AND APPLIED CLIMATOLOGY (2014)
Vehicular traffic noise modeling using artificial neural network approach
Paras Kumar et al.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2014)
Predicting hourly air pollutant levels using artificial neural networks coupled with uncertainty analysis by Monte Carlo simulations
Mohammad Arhami et al.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2013)
Improved annual rainfall-runoff forecasting using PSO-SVM model based on EEMD
Wen-chuan Wang et al.
JOURNAL OF HYDROINFORMATICS (2013)
Forecasting highway casualties under the effect of railway development policy in Turkey using artificial neural networks
Erdem Dogan et al.
NEURAL COMPUTING & APPLICATIONS (2013)
Sensitivity analysis of the artificial neural network outputs in simulation of the evaporation process at different climatologic regimes
Vahid Nourani et al.
ADVANCES IN ENGINEERING SOFTWARE (2012)
Forecasting hourly PM10 concentration in Cyprus through artificial neural networks and multiple regression models: implications to local environmental management
Anastasia K. Paschalidou et al.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2011)
An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM
Ulas Caydas et al.
EXPERT SYSTEMS WITH APPLICATIONS (2009)
Prediction of hourly air pollutant concentrations near urban arterials using artificial neural network approach
Ming Cai et al.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT (2009)
Software reliability prediction by soft computing techniques
N. Raj Kiran et al.
JOURNAL OF SYSTEMS AND SOFTWARE (2008)
Performance comparison of neural network training algorithms in modeling of bimodal drug delivery
A. Ghaffari et al.
INTERNATIONAL JOURNAL OF PHARMACEUTICS (2006)
Estimating ground-level PM2.5 using aerosol optical depth determined from satellite remote sensing
Aaron van Donkelaar et al.
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2006)
Interpretation of particulate elemental and organic carbon concentrations at rural, urban and kerbside sites
AM Jones et al.
ATMOSPHERIC ENVIRONMENT (2005)
Summarizing multiple aspects of model performance in a single diagram.
KE Taylor
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES (2001)
分享论文
