Hybrid DE optimised kernel SVR–relied techniques to forecast the outlet turbidity and outlet dissolved oxygen in distinct filtration media and micro-irrigation filters-Reference-Cited by-同舟云学术

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Hybrid DE optimised kernel SVR–relied techniques to forecast the outlet turbidity and outlet dissolved oxygen in distinct filtration media and micro-irrigation filters

Published:2024-07 Issue: Volume:243 Page:42-56
ISSN:1537-5110
Container-title:Biosystems Engineering
language:en
Short-container-title:Biosystems Engineering

Author:

García–Nieto Paulino José^ORCID,García–Gonzalo Esperanza^ORCID,Arbat Gerard^ORCID,Duran–Ros Miquel,Pujol Toni^ORCID,Puig–Bargués Jaume^ORCID

Publisher

Elsevier BV

Reference55 articles.

1. Foundations of statistics for data scientists: with R and Python;Agresti,2021

2. Introduction;Ayars,2007

3. Pattern recognition and machine learning;Bishop,2006

4. Reducing energy requirements for sand filtration in microirrigation: Improving the underdrain and packing;Bové;Biosystems Engineering,2015

5. Pressure drop across sand and recycled glass media used in micro irrigation filters;Bové;Biosystems Engineering,2015

Cited by 1 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. Bi-Directional Prediction Model for Hot Pressing Production Parameters and Quality of High-Performance Bamboo-Based Fiber Composites Based on cHGWOSCA-SVR;Applied Sciences;2024-07-31

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