4.7 Article

Multi-objective evolutionary spatio-temporal forecasting of air pollution

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。
Article Computer Science, Artificial Intelligence

A time series forecasting based multi-criteria methodology for air quality prediction

Raquel Espinosa et al.

Summary: This study explores the design and testing of environmental pollution models, focusing on forecasting performance. By analyzing data from three years, deep learning and regression models are used to reliably predict pollutant concentrations in the air 24 hours in advance, allowing for interventions to mitigate effects on the population.

APPLIED SOFT COMPUTING (2021)

Article Automation & Control Systems

Deep Spatio-temporal Learning Model for Air Quality Forecasting

L. Zhang et al.

Summary: This paper studies deep spatio-temporal learning method for global air quality prediction, proposes two novel forecasting models STOR-cube and ST-DA, and experimental results demonstrate the effectiveness of this approach.

INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL (2021)

Article Pediatrics

Ambient Air Pollution: Health Hazards to Children

Heather L. Brumberg et al.

Summary: Ambient air pollution, caused by various sources such as vehicular traffic and coal-fired power plants, leads to climate change which in turn worsens the health effects of air pollution. Infants and children are especially vulnerable to its impacts, which include respiratory diseases, reduced lung function, and increased asthma incidence. Efforts to improve air quality, such as increasing public transportation use and implementing regulations, have shown positive effects on community health.

PEDIATRICS (2021)

Article Environmental Sciences

Ensemble multifeatured deep learning models for air quality forecasting

Chi-Yeh Lin et al.

Summary: As air pollution worsens, accurate air quality forecasting has become increasingly important. Many studies using machine learning and deep learning methods have been proposed to predict air quality, with deep learning showing better performance than traditional methods, and ensemble learning improving classification efficacy. This paper introduces the MLEGRU model, an ensemble learning forecasting model based on GRU and multiple linear regression techniques, which outperforms other ensemble methods in air quality forecasting accuracy.

ATMOSPHERIC POLLUTION RESEARCH (2021)

Article Engineering, Multidisciplinary

Spatiotemporal prediction of air quality based on LSTM neural network

Dewen Seng et al.

Summary: By utilizing deep learning and supervised learning techniques, a comprehensive prediction model based on LSTM was developed for air quality indicators like PM2.5, CO, NO2, O-3, and SO2. Normalized and transformed environmental data were used to predict overall air quality in Beijing.

ALEXANDRIA ENGINEERING JOURNAL (2021)

Article Computer Science, Artificial Intelligence

Spatio-attention embedded recurrent neural network for air quality prediction

Yu Huang et al.

Summary: Predicting the air quality index (AQI) requires considering complex spatio-temporal interactions and leveraging dynamic spatiotemporal correlations among monitoring stations. The proposed model, SpAttRNN, incorporates geospatial topological structures into the prediction model by utilizing graph-based attention cells to learn relationships among monitoring stations. Experimental results show significant improvement in PM2.5 prediction accuracy compared to existing methods.

KNOWLEDGE-BASED SYSTEMS (2021)

Review Nuclear Science & Technology

A survey of multi-objective optimization methods and their applications for nuclear scientists and engineers

Ryan H. Stewart et al.

Summary: Problems in nuclear engineering, such as reactor core design, require careful consideration of multiple design variables and constraints. Multi-objective optimization algorithms can help engineers reduce design space and find optimal solutions.

PROGRESS IN NUCLEAR ENERGY (2021)

Article Multidisciplinary Sciences

PM10 and PM2.5 real-time prediction models using an interpolated convolutional neural network

Sangwon Chae et al.

Summary: The paper introduces a real-time prediction model that uses interpolation and Convolutional Neural Network to predict PM10 and PM2.5 concentrations, achieving effective prediction performance with high reliability.

SCIENTIFIC REPORTS (2021)

Article Chemistry, Multidisciplinary

A Spatial-Temporal Approach for Air Quality Forecast in Urban Areas

Eric Hsueh-Chan Lu et al.

Summary: This paper introduces the characteristics of PM2.5 particles and their impact on human health, and discusses the research on predicting PM2.5 through a spatial-temporal approach. The study found a correlation between AQI, weather similarity, and PM2.5 values.

APPLIED SCIENCES-BASEL (2021)

Article Computer Science, Artificial Intelligence

Feature selection based multivariate time series forecasting: An application to antibiotic resistance outbreaks prediction

Fernando Jimenez et al.

ARTIFICIAL INTELLIGENCE IN MEDICINE (2020)

Article Computer Science, Artificial Intelligence

IGD Indicator-Based Evolutionary Algorithm for Many-Objective Optimization Problems

Yanan Sun et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2019)

Article Multidisciplinary Sciences

Effects of fossil fuel and total anthropogenic emission removal on public health and climate

J. Lelieveld et al.

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA (2019)

Article Construction & Building Technology

A methodology for energy multivariate time series forecasting in smart buildings based on feature selection

Aurora Gonzalez-Vidal et al.

ENERGY AND BUILDINGS (2019)

Article Statistics & Probability

SPATIO-TEMPORAL MODELS WITH SPACE-TIME INTERACTION AND THEIR APPLICATIONS TO AIR POLLUTION DATA

Soudeep Deb et al.

STATISTICA SINICA (2019)

Article Computer Science, Information Systems

Regional Spatiotemporal Collaborative Prediction Model for Air Quality

Guyu Zhao et al.

IEEE ACCESS (2019)

Article Computer Science, Artificial Intelligence

Comparison of multi-objective evolutionary algorithms in hybrid Kansei engineering system for product form design

Meng-Dar Shieh et al.

ADVANCED ENGINEERING INFORMATICS (2018)

Article Computer Science, Information Systems

An evolutionary system for ozone concentration forecasting

Mauro Castelli et al.

INFORMATION SYSTEMS FRONTIERS (2017)

Article Computer Science, Artificial Intelligence

An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints

Kalyanmoy Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2014)

Article Engineering, Environmental

Indoor air pollution and respiratory health in the elderly

Malek Bentayeb et al.

JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH PART A-TOXIC/HAZARDOUS SUBSTANCES & ENVIRONMENTAL ENGINEERING (2013)

Article Computer Science, Artificial Intelligence

Multiobjective Evolutionary Algorithms in Aeronautical and Aerospace Engineering

Alfredo Arias-Montano et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2012)

Article Computer Science, Interdisciplinary Applications

A multi-objective evolutionary algorithm for protein structure prediction with immune operators

M. V. Judy et al.

COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING (2009)

Article Computer Science, Interdisciplinary Applications

An efficient multiobjective differential evolution algorithm for engineering design

Wenyin Gong et al.

STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION (2009)

Article Computer Science, Artificial Intelligence

MOEA/D: A multiobjective evolutionary algorithm based on decomposition

Qingfu Zhang et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2007)

Article Computer Science, Artificial Intelligence

Multiobjective evolutionary algorithms for electric power dispatch problem

M. A. Abido

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2006)

Review Computer Science, Artificial Intelligence

Performance assessment of multiobjective optimizers: An analysis and review

E Zitzler et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2003)

Article Computer Science, Artificial Intelligence

A fast and elitist multiobjective genetic algorithm: NSGA-II

K Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2002)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)

Article Computer Science, Artificial Intelligence

Improvements to the SMO algorithm for SVM regression

SK Shevade et al.

IEEE TRANSACTIONS ON NEURAL NETWORKS (2000)