Impact of Sampling Technique on the Performance of Surrogate Models Generated with Artificial Neural Network (ANN): A Case Study for a Natural Gas Stabilization Unit

<div><p>Data-driven models are essential tools for the development of surrogate models that can be used for the design, operation, and optimization of industrial processes. One approach of developing surrogate models is through the use of input–output data obtained from a process simulat...

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Bibliographic Details
Main Author: Mohamed Ibrahim (3465677) (author)
Other Authors: Saad Al-Sobhi (18153811) (author), Rajib Mukherjee (532424) (author), Ahmed AlNouss (9872265) (author)
Published: 2019
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