Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data-Reference-Cited by-同舟云学术

Classification of catchments for nitrogen using Artificial Neural Network Pattern Recognition and spatial data

Published:2022-02 Issue: Volume:809 Page:151139
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

O'Sullivan Cherie M.,Ghahramani Afshin,Deo Ravinesh C.,Pembleton Keith,Khan Urooj,Tuteja Narendra

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference97 articles.

1. The Australian Land Use and Management Classification Version 8;ABARES,2016

2. (Qld) (Austl.);Planning Act,2016

3. A comparison of similarity indices for catchment classification using a cross-regional dataset;Ali;Adv. Water Resour.,2012

4. Short-term electricity demand forecasting using machine learning methods enriched with ground-based climate and ECMWF reanalysis atmospheric predictors in Southeast QueenslandAustralia;Al-Musaylh,2019

5. The budyko hypothesis before budyko: the hydrological legacy of evald oldekop;Andréassian;J. Hydrol.,2016

Cited by 8 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A target intention recognition method based on information classification processing and information fusion;Engineering Applications of Artificial Intelligence;2024-01

2. A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing;Processes;2023-11-07

3. Explainable AI approach with original vegetation data classifies spatio-temporal nitrogen in flows from ungauged catchments to the Great Barrier Reef;Scientific Reports;2023-10-24

4. River reach-level machine learning estimation of nutrient concentrations in Great Britain;Frontiers in Water;2023-09-19

5. Cuproptosis-related risk score based on machine learning algorithm predicts prognosis and characterizes tumor microenvironment in head and neck squamous carcinomas;Scientific Reports;2023-07-22