标题
Machine Learning: New Ideas and Tools in Environmental Science and Engineering
作者
关键词
-
出版物
ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume -, Issue -, Pages -
出版商
American Chemical Society (ACS)
发表日期
2021-08-18
DOI
10.1021/acs.est.1c01339
参考文献
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。- Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network
- (2021) Weiqi Ji et al. JOURNAL OF PHYSICAL CHEMISTRY A
- A database framework for rapid screening of structure-function relationships in PFAS chemistry
- (2021) An Su et al. Scientific Data
- Quantitative structure activity relationships (QSARs) and machine learning models for abiotic reduction of organic compounds by an aqueous Fe(II) complex
- (2021) Yidan Gao et al. WATER RESEARCH
- ES&T in the 21st Century: A Data-Driven Analysis of Research Topics, Interconnections, And Trends in the Past 20 Years
- (2021) Jun-Jie Zhu et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- A Deep Learning Approach to Antibiotic Discovery
- (2020) Jonathan M. Stokes et al. CELL
- CoMPARA: Collaborative Modeling Project for Androgen Receptor Activity
- (2020) Kamel Mansouri et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Aggravation of reactive nitrogen flow driven by human production and consumption in Guangzhou City China
- (2020) Yue Dong et al. Nature Communications
- Inverse design of porous materials using artificial neural networks
- (2020) Baekjun Kim et al. Science Advances
- How Machine Learning Will Transform Biomedicine
- (2020) Jeremy Goecks et al. CELL
- Machine Learning for Materials Scientists: An introductory guide towards best practices
- (2020) Anthony Yu-Tung Wang et al. CHEMISTRY OF MATERIALS
- Predicting Aqueous Adsorption of Organic Compounds onto Biochars, Carbon Nanotubes, Granular Activated Carbons, and Resins with Machine Learning
- (2020) Kai Zhang et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Global threat of arsenic in groundwater
- (2020) Joel Podgorski et al. SCIENCE
- Performance evaluation and modelling of an integrated municipal wastewater treatment system using neural networks
- (2020) Habib A. Mokhtari et al. WATER AND ENVIRONMENT JOURNAL
- Opportunities and Challenges for Biosensors and Nanoscale Analytical Tools for Pandemics: COVID-19
- (2020) Nikhil Bhalla et al. ACS Nano
- Shedding Light On “Black Box” Machine Learning Models for Predicting the Reactivity of HO• Radicals toward Organic Compounds
- (2020) Shifa Zhong et al. CHEMICAL ENGINEERING JOURNAL
- Structures of Endocrine-Disrupting Chemicals Determine Binding to and Activation of the Estrogen Receptor α and Androgen Receptor
- (2020) Haoyue Tan et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- A data‐driven framework to characterize state‐level water use in the U.S.
- (2020) E. Wongso et al. WATER RESOURCES RESEARCH
- Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States
- (2020) Abolfazl Mollalo et al. International Journal of Environmental Research and Public Health
- Machine learning in experimental materials chemistry
- (2020) Balaranjan Selvaratnam et al. CATALYSIS TODAY
- Identifying domains of applicability of machine learning models for materials science
- (2020) Christopher Sutton et al. Nature Communications
- Rethinking wastewater risks and monitoring in light of the COVID-19 pandemic
- (2020) Anne Bogler et al. Nature Sustainability
- Review on the contamination of wastewater by COVID-19 virus: Impact and treatment
- (2020) S. Lahrich et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Molecular image-convolutional neural network (CNN) assisted QSAR models for predicting contaminant reactivity toward OH radicals: Transfer learning, data augmentation and model interpretation
- (2020) Shifa Zhong et al. CHEMICAL ENGINEERING JOURNAL
- Predicting carbonaceous aerosols and identifying their source contribution with advanced approaches
- (2020) Jun-Jie Zhu et al. CHEMOSPHERE
- Performance of Prediction Algorithms for Modeling Outdoor Air Pollution Spatial Surfaces
- (2019) Jules Kerckhoffs et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Advanced control of membrane fouling in filtration systems using artificial intelligence and machine learning techniques: A critical review
- (2019) Majid Bagheri et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Data-driven performance analyses of wastewater treatment plants: A review
- (2019) Kathryn B. Newhart et al. WATER RESEARCH
- Nonanimal Models for Acute Toxicity Evaluations: Applying Data-Driven Profiling and Read-Across
- (2019) Daniel P. Russo et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Applications of machine learning in drug discovery and development
- (2019) Jessica Vamathevan et al. NATURE REVIEWS DRUG DISCOVERY
- Using attribution to decode binding mechanism in neural network models for chemistry
- (2019) Kevin McCloskey et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Fusion Method Combining Ground-Level Observations with Chemical Transport Model Predictions Using an Ensemble Deep Learning Framework: Application in China to Estimate Spatiotemporally-Resolved PM2.5 Exposure Fields in 2014–2017
- (2019) Baolei Lyu et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- A review of machine learning for the optimization of production processes
- (2019) Dorina Weichert et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- APOE and cortical superficial siderosis in CAA
- (2019) Andreas Charidimou et al. NEUROLOGY
- Artificial intelligence could revolutionize medical care. But don’t trust it to read your x-ray just yet
- (2019) Jennifer Couzin-Frankel SCIENCE
- Deep learning-based PM2.5 prediction considering the spatiotemporal correlations: A case study of Beijing, China
- (2019) Unjin Pak et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Evaluating Chemicals for Thyroid Disruption: Opportunities and Challenges with in Vitro Testing and Adverse Outcome Pathway Approaches
- (2019) Pamela D. Noyes et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- A Deep Neural Network Combined with Molecular Fingerprints (DNN-MF) to Develop Predictive Models for Hydroxyl Radical Rate Constants of Water Contaminants
- (2019) Shifa Zhong et al. JOURNAL OF HAZARDOUS MATERIALS
- Performance evaluation of the ISMLR package for predicting the next day's influent wastewater flowrate at Kirie WRP
- (2019) Jun-Jie Zhu et al. WATER SCIENCE AND TECHNOLOGY
- A Machine Learning Approach for Predicting Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) for Their Efficient Treatment and Removal
- (2019) Akber Raza et al. Environmental Science & Technology Letters
- Improving air quality prediction accuracy at larger temporal resolutions using deep learning and transfer learning techniques
- (2019) Jun Ma et al. ATMOSPHERIC ENVIRONMENT
- Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers
- (2019) Ghanshyam Pilania et al. Journal of Chemical Information and Modeling
- Combination of LEDs and cognitive modeling to quantify sheep cheese whey in watercourses
- (2019) Miguel Lastra-Mejias et al. TALANTA
- Deep learning approach for sustainable WWTP operation: A case study on data-driven influent conditions monitoring
- (2019) Abdelkader Dairi et al. Sustainable Cities and Society
- Examining plant uptake and translocation of emerging contaminants using machine learning: Implications to food security
- (2019) Majid Bagheri et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Improving the identification of the source of faecal pollution in water using a modelling approach: From multi-source to aged and diluted samples
- (2019) Elisenda Ballesté et al. WATER RESEARCH
- Deep learning identifies accurate burst locations in water distribution networks
- (2019) Xiao Zhou et al. WATER RESEARCH
- Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
- (2019) Alejandro Barredo Arrieta et al. Information Fusion
- Revealing Biotic and Abiotic Controls of Harmful Algal Blooms in a Shallow Subtropical Lake through Statistical Machine Learning
- (2018) Natalie G. Nelson et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Statistical monitoring of a wastewater treatment plant: A case study
- (2018) Fouzi Harrou et al. JOURNAL OF ENVIRONMENTAL MANAGEMENT
- Statistical regression modeling for energy consumption in wastewater treatment
- (2018) Yang Yu et al. JOURNAL OF ENVIRONMENTAL SCIENCES
- Points of Significance: Statistics versus machine learning
- (2018) Danilo Bzdok et al. NATURE METHODS
- A Deep Spatial-Temporal Ensemble Model for Air Quality Prediction
- (2018) Junshan Wang et al. NEUROCOMPUTING
- Machine learning & artificial intelligence in the quantum domain: a review of recent progress
- (2018) Vedran Dunjko et al. REPORTS ON PROGRESS IN PHYSICS
- Predicting influent biochemical oxygen demand: Balancing energy demand and risk management
- (2018) Jun-Jie Zhu et al. WATER RESEARCH
- Deep convolution neural network for image recognition
- (2018) Boukaye Boubacar Traore et al. Ecological Informatics
- An Ensemble Machine-Learning Model To Predict Historical PM2.5 Concentrations in China from Satellite Data
- (2018) Qingyang Xiao et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Modelling the effects of multiple stressors on respiration and microbial biomass in the hyporheic zone using decision trees
- (2018) Nataša Mori et al. WATER RESEARCH
- A deeper look at plant uptake of environmental contaminants using intelligent approaches
- (2018) Majid Bagheri et al. SCIENCE OF THE TOTAL ENVIRONMENT
- Using artificial neural network to investigate physiological changes and cerium oxide nanoparticles and cadmium uptake by Brassica napus plants
- (2018) Lorenzo Rossi et al. ENVIRONMENTAL POLLUTION
- Estimating PM2.5 Concentrations in the Conterminous United States Using the Random Forest Approach
- (2017) Xuefei Hu et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Rapid Life-Cycle Impact Screening Using Artificial Neural Networks
- (2017) Runsheng Song et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Machine learning methods for wastewater hydraulics
- (2017) Francesco Granata et al. FLOW MEASUREMENT AND INSTRUMENTATION
- Statistical monitoring and dynamic simulation of a wastewater treatment plant: A combined approach to achieve model predictive control
- (2017) Xiaodong Wang et al. JOURNAL OF ENVIRONMENTAL MANAGEMENT
- A high-throughput, computational system to predict if environmental contaminants can bind to human nuclear receptors
- (2017) Xiaoxiang Wang et al. SCIENCE OF THE TOTAL ENVIRONMENT
- A note on using the F-measure for evaluating record linkage algorithms
- (2017) David Hand et al. STATISTICS AND COMPUTING
- Machine Learning With Big Data: Challenges and Approaches
- (2017) Alexandra L'Heureux et al. IEEE Access
- Development and Validation of a Computational Model for Androgen Receptor Activity
- (2016) Nicole C. Kleinstreuer et al. CHEMICAL RESEARCH IN TOXICOLOGY
- CERAPP: Collaborative Estrogen Receptor Activity Prediction Project
- (2016) Kamel Mansouri et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Identification of Thyroid Hormone Disruptors among HO-PBDEs: In Vitro Investigations and Coregulator Involved Simulations
- (2016) Qinchang Chen et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Machine-learning-assisted materials discovery using failed experiments
- (2016) Paul Raccuglia et al. NATURE
- Utility of Machine-Learning Approaches to Identify Behavioral Markers for Substance Use Disorders: Impulsivity Dimensions as Predictors of Current Cocaine Dependence
- (2016) Woo-Young Ahn et al. Frontiers in Psychiatry
- Analysis of variables affecting mixed liquor volatile suspended solids and prediction of effluent quality parameters in a real wastewater treatment plant
- (2015) Majid Bagheri et al. Desalination and Water Treatment
- Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data
- (2015) Marlene Thai Kim et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Prediction of effluent concentration in a wastewater treatment plant using machine learning models
- (2015) Hong Guo et al. JOURNAL OF ENVIRONMENTAL SCIENCES
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Evaluation and prediction of membrane fouling in a submerged membrane bioreactor with simultaneous upward and downward aeration using artificial neural network-genetic algorithm
- (2015) Seyed Ahmad Mirbagheri et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Modeling and optimization of activated sludge bulking for a real wastewater treatment plant using hybrid artificial neural networks-genetic algorithm approach
- (2015) Majid Bagheri et al. PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
- Comparison of Cramer classification between Toxtree, the OECD QSAR Toolbox and expert judgment
- (2015) Sneha Bhatia et al. REGULATORY TOXICOLOGY AND PHARMACOLOGY
- An integrated logit model for contamination event detection in water distribution systems
- (2015) Mashor Housh et al. WATER RESEARCH
- Performance evaluation and modeling of a submerged membrane bioreactor treating combined municipal and industrial wastewater using radial basis function artificial neural networks
- (2015) Seyed Ahmad Mirbagheri et al. Journal of Environmental Health Science and Engineering
- Predictive Endocrine Testing in the 21st Century Using in Vitro Assays of Estrogen Receptor Signaling Responses
- (2014) Daniel M. Rotroff et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Endocrine Disruptome—An Open Source Prediction Tool for Assessing Endocrine Disruption Potential through Nuclear Receptor Binding
- (2014) Katra Kolšek et al. Journal of Chemical Information and Modeling
- Read-across approaches - misconceptions, promises and challenges ahead
- (2014) Grace Patlewicz ALTEX-Alternatives to Animal Experimentation
- Data-derived soft-sensors for biological wastewater treatment plants: An overview
- (2013) Henri Haimi et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Leakage in data mining
- (2013) Shachar Kaufman et al. ACM Transactions on Knowledge Discovery from Data
- Using in Vitro High Throughput Screening Assays to Identify Potential Endocrine-Disrupting Chemicals
- (2012) Daniel M. Rotroff et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Analyzing High Dimensional Toxicogenomic Data Using Consensus Clustering
- (2012) Ce Gao et al. ENVIRONMENTAL SCIENCE & TECHNOLOGY
- Application of computational toxicological approaches in human health risk assessment. I. A tiered surrogate approach
- (2012) Nina Ching Yi Wang et al. REGULATORY TOXICOLOGY AND PHARMACOLOGY
- Uncertainty assessment of a model for biological nitrogen and phosphorus removal: Application to a large wastewater treatment plant
- (2011) Giorgio Mannina et al. PHYSICS AND CHEMISTRY OF THE EARTH
- CAESAR models for developmental toxicity
- (2010) Antonio Cassano et al. Chemistry Central Journal
- Evaluation of Computational Docking to Identify Pregnane X Receptor Agonists in the ToxCast Database
- (2010) Sandhya Kortagere et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Endocrine Profiling and Prioritization of Environmental Chemicals Using ToxCast Data
- (2010) David M. Reif et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- A Novel Two-Step Hierarchical Quantitative Structure–Activity Relationship Modeling Work Flow for Predicting Acute Toxicity of Chemicals in Rodents
- (2009) Hao Zhu et al. ENVIRONMENTAL HEALTH PERSPECTIVES
- Particulate matter air quality assessment using integrated surface, satellite, and meteorological products: 2. A neural network approach
- (2009) Pawan Gupta et al. JOURNAL OF GEOPHYSICAL RESEARCH
- Chemical regulators have overreached
- (2009) Thomas Hartung et al. NATURE
- Use of Cell Viability Assay Data Improves the Prediction Accuracy of Conventional Quantitative Structure–Activity Relationship Models of Animal Carcinogenicity
- (2008) Hao Zhu et al. ENVIRONMENTAL HEALTH PERSPECTIVES
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search