首页|Researchers from Henan Finance University Describe Findings in Artificial Intell igence (Development of a Novel Model To Estimate the Separation of Organic Compo unds Via Porous Membranes Through Artificial Intelligence Technique)

Researchers from Henan Finance University Describe Findings in Artificial Intell igence (Development of a Novel Model To Estimate the Separation of Organic Compo unds Via Porous Membranes Through Artificial Intelligence Technique)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ar tificial Intelligence. According to news reporting from Zhengzhou, People’s Repu blic of China, by NewsRx editors, the research stated, “We have carried out mode ling and computation of mass transfer in a membrane contactor for removal of org anic compounds from aqueous solutions. Both computational fluid dynamics (CFD) a nd Artificial Intelligence (AI) methods were utilized for modeling separation pr ocess.” The news correspondents obtained a quote from the research from Henan Finance Un iversity, “For the AI, we explored the application of three distinct regression models, namely Kernel Ridge Regression, Gaussian Process Regression, and Poisson Regression to predict the concentration of a component, C, based on r and z. To enhance the performance of these models, the hyper-parameter tuning process emp loys Glowworm Swarm Optimization (GSO). The findings illustrate the effectivenes s of the utilized models. Gaussian Process Regression achieves a noteworthy R2 s core of 0.99791, with a RMSE of 3.9666 x 101(mol/m3) and an AARD% of 4.52000 x 10-1. Kernel Ridge Regression, while slightly less accurate, achiev es a commendable R2 value of 0.97865, with an RMSE of 1.2446 x 102(mol/m3) and a n AARD% of 2.63808. Poisson Regression offers a respectable perfor mance, yielding an R2 score of 0.95509, along with an RMSE of 1.8011 x 102(mol/m 3) and an AARD% of 4.28969.”

ZhengzhouPeople’s Republic of ChinaA siaArtificial IntelligenceEmerging TechnologiesGaussian ProcessesMachine LearningHenan Finance University

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Jun.28)