02342nam 22005293 450 991104402650332120250821173203.00-443-29059-8(MiAaPQ)EBC32112581(Au-PeEL)EBL32112581(CKB)38791102100041(OCoLC)1520914631(EXLCZ)993879110210004120250311d2025 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine learning tools for chemical engineering methodologies and applications /Francisco Javier López-Flores, Rogelio Ochoa-Barragán, Alma Yunuen Raya-Tapia, César Ramírez-Márquez, José Maria Ponce-Ortega1st ed.Elsevier Science [Imprint]San Diego Elsevier Science & Technology BooksSaint Louis Elsevier [Distributor]Saint Louis Elsevier [Distributor]Chantilly :Elsevier Science & Technology,2025.©2026.1 online resource (630 pages)0-443-29058-X Machine Learning Tools for Chemical Engineering: Methodologies and Applications examines how machine learning (ML) techniques are applied in the field, offering precise, fast, and flexible solutions to address specific challenges.ML techniques and methodologies offer significant advantages (such as accuracy, speed of execution, and flexibility).Chemical engineeringData processingMachine learningIndustrial applicationsGénie chimiqueInformatiqueApprentissage automatiqueApplications industriellesChemical engineeringData processing.Machine learningIndustrial applications.Génie chimiqueInformatique.Apprentissage automatiqueApplications industrielles.660.0285631López-Flores Francisco Javier1851466Raya-Tapia Alma YunuenOchoa-Barragán RogelioRamírez-Márquez CésarMiAaPQMiAaPQMiAaPQ0BOOK9911044026503321Machine learning tools for chemical engineering4460823UNINA