Cargando…
Optimised neural network model for river-nitrogen prediction utilizing a new training approach
In the past few decades, there has been a rapid growth in the concentration of nitrogenous compounds such as nitrate-nitrogen and ammonia-nitrogen in rivers, primarily due to increasing agricultural and industrial activities. These nitrogenous compounds are mainly responsible for eutrophication when...
Autores principales: | Kumar, Pavitra, Lai, Sai Hin, Mohd, Nuruol Syuhadaa, Kamal, Md Rowshon, Afan, Haitham Abdulmohsin, Ahmed, Ali Najah, Sherif, Mohsen, Sefelnasr, Ahmed, El-shafie, Ahmed |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7521719/ https://www.ncbi.nlm.nih.gov/pubmed/32986717 http://dx.doi.org/10.1371/journal.pone.0239509 |
Ejemplares similares
-
Complex Extreme Sea Levels Prediction Analysis: Karachi Coast Case Study
por: Khan, Faisal Ahmed, et al.
Publicado: (2020) -
Feedforward Artificial Neural Network-Based Model for Predicting the Removal of Phenolic Compounds from Water by Using Deep Eutectic Solvent-Functionalized CNTs
por: Ibrahim, Rusul Khaleel, et al.
Publicado: (2020) -
Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting
por: Afan, Haitham Abdulmohsin, et al.
Publicado: (2020) -
An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
por: Ehteram, Mohammad, et al.
Publicado: (2019) -
Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes
por: Mijwel, Abd-Alkhaliq Salih, et al.
Publicado: (2023)