Predictive Neural Network Modeling for Almond Harvest Dust Control

Predictive Neural Network Modeling for Almond Harvest Dust Control

This study introduces a neural network-based approach to predict dust emissions, specifically PM2.5 particles, during almond harvesting in California. Using a feedforward neural network (FNN), this research predicted PM2.5 emissions by analyzing key operational parameters of an advanced almond harve...

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Bibliographic Details
Main Authors: Reza Serajian, Jian-Qiao Sun, Jeanette Cobian-Iñiguez, Reza Ehsani
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Sensors
Subjects:
almond harvesting
dust emissions
predictive modeling
neural networks
PM2.5 particles
Online Access:https://www.mdpi.com/1424-8220/24/7/2136

Internet

https://www.mdpi.com/1424-8220/24/7/2136

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