Machine learning approach to handle data‐driven model for simulation and forecasting of the cone crusher output in the stone crushing plant
Author:
Affiliation:
1. Mechanical Engineering Department, College of Engineering University of Bisha Bisha Kingdom of Saudi Arabia
Publisher
Wiley
Subject
Artificial Intelligence,Computational Mathematics
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/coin.12338
Reference32 articles.
1. Particle size measurements and scanning electron microscopy (SEM) of cocoa particles refined/conched by conical and cylindrical roller stone melangers
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4. Repo V.Fine Grained Crushed Stone Aggregate in Concrete.Finland:Aalto University‐School of Engineering;2017.
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