Open AccessMODELING OF PAFO SYSTEM WITH NEURAL NETWORK IN SEAWATER DESALINATION FOR AGRICULTURAL APPLICATIONS
Author(s) -
Leila Javarani,
Mohammad Malakootian,
Amir Hessam Hassani,
Amir Hossein Javid
Publication year - 2020
Publication title -
plant archives/plant archives
Language(s) - English
Resource type - Journals
eISSN - 2581-6063
pISSN - 0972-5210
DOI - 10.51470/plantarchives.2021.v21.s1.403
Subject(s) - desalination , seawater , brackish water , environmental science , artificial neural network , wastewater , environmental engineering , permeability (electromagnetism) , salinity , computer science , chemistry , geology , membrane , biochemistry , oceanography , machine learning
Brackish water, municipal and industrial wastewater is considered as a valuable source to increase agricultural production. PAFO system with the use of agricultural fertilizers as a new solution with the aim of creating hydraulic pressure less than 5 times to increase flux and water permeability compared to the system RO, FO in seawater desalination. The efficiency and performance of the system was determined by analyzing the parameters of water flux (jw), water permeability (A), permeability of dissolved matter (B), B/A ratio and finally modeling was done using MATLAB software with effective parameters in water flux based on chi model of neural network. According to the results of the model, appropriate performance of the model was determined based on the R coefficient and the distribution of the predicted points against the real data