Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques
DOI10.1016/j.cam.2023.115606OpenAlexW4387373753MaRDI QIDQ6126024
No author found.
Publication date: 9 April 2024
Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.cam.2023.115606
ridgedifferential evolution (DE)microirrigationlasso and elastic-net regressionsrandom forest regression (RFR) technique
Linear regression; mixed models (62J05) Learning and adaptive systems in artificial intelligence (68T05) Other natural sciences (mathematical treatment) (92F05)
Cites Work
- Differential evolution. In search of solutions.
- Advances in differential evolution
- Differential evolution -- a simple and efficient heuristic for global optimization over continuous spaces
- Differential evolution: from theory to practice
- Cross-Validation of Regression Models
- Random Forests with R
- Mathematics for Machine Learning
- An Introduction to Statistical Learning
- Random forests
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Forecast of the outlet turbidity and filtered volume in different microirrigation filters and filtration media by using machine learning techniques