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Machine Learning Approach to Predict Physical Properties of Polypropylene Composites: Application of MLR, DNN, and Random Forest to Industrial Data

Polymers, 2022-08, Vol.14 (17), p.3500

2022

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One-Pot Transformation of Technical Lignins into Humic-Like Plant Stimulants through Fenton-Based Advanced Oxidation: Accelerating Natural Fungus-Driven Humification

ACS omega, 2018-07, Vol.3 (7), p.7441-7453

2018

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Soft magnetic properties of conetic co-sputtered with aluminum

Metals and Materials International, 2014, 20(3), , pp.551-554

2014

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Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

International journal of intelligent systems, 2022-06, Vol.37 (6), p.3625-3653

2022

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Machine learning-based heat deflection temperature prediction and effect analysis in polypropylene composites using catboost and shapley additive explanations

Engineering applications of artificial intelligence, 2023-11, Vol.126, p.106873, Article 106873

2023

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Novel natural gradient boosting-based probabilistic prediction of physical properties for polypropylene-based composite data

Engineering applications of artificial intelligence, 2024-09, Vol.135, p.108864, Article 108864

2024

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A Study on the Sensitivity of a Spin Valve with Conetic-Based Free Layers

Japanese Journal of Applied Physics, 2012-03, Vol.51 (3), p.033002-033002-3

2012

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A novel graph-based missing values imputation method for industrial lubricant data

Computers in industry, 2023-09, Vol.150, p.103937, Article 103937

2023

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Dual attention-based multi-step ahead prediction enhancement for monitoring systems in industrial processes

Applied soft computing, 2023-11, Vol.147, p.110763, Article 110763

2023

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Cover: International Journal of Intelligent Systems, Volume 37 Issue 6 June 2022

International journal of intelligent systems, 2022-06, Vol.37 (6), p.i-i

2022

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Data-driven modeling of multimode chemical process: Validation with a real-world distillation column

Chemical engineering journal (Lausanne, Switzerland : 1996), 2023-02, Vol.457, p.141025, Article 141025

2023

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Enhancement of mass transport in fuel cells using three-dimensional graphene foam as flow field

Electrochimica acta, 2018-03, Vol.265, p.488-496

2018

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Time-series clustering approach for training data selection of a data-driven predictive model: Application to an industrial bio 2,3-butanediol distillation process

Computers & chemical engineering, 2022-05, Vol.161, p.107758, Article 107758

2022

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Machine Learning-Based Adaptive Regression to Identify Nonlinear Dynamics of Biochemical Systems: A Case Study on Bio 2,3-Butanediol Distillation Process

ACS sustainable chemistry & engineering, 2024-07, Vol.12 (29), p.10869-10879

2024

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Gas diffusion layer/flow-field unified membrane-electrode assembly in fuel cell using graphene foam

Electrochimica acta, 2019-11, Vol.323, p.134808, Article 134808

2019

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Dynamic Modeling of Acetone–Butanol–Ethanol Fermentation with ex Situ Butanol Recovery using Glucose/Xylose Mixtures

Industrial & engineering chemistry research, 2020-02, Vol.59 (6), p.2581-2592

2020

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Multi-objective optimization of operation of lignocellulosic acetone-butanol-ethanol fermentation with ex situ butanol recovery (ESBR)

Computers & chemical engineering, 2020-09, Vol.140, p.106915, Article 106915

2020

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Correction to: A dynamic soft sensor based on hybrid neural networks to improve early off-spec detection

Engineering with computers, 2023-10, Vol.39 (5), p.3155-3155

2023

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Mathematical Modeling of Acetone–Butanol–Ethanol Fermentation with Simultaneous Utilization of Glucose and Xylose by Recombinant Clostridium acetobutylicum

Energy & fuels, 2019-09, Vol.33 (9), p.8620-8631

2019

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바이오 기반 2,3-butanediol 증류 공정의 제어 및 동적 최적화

Korean Chemical Engineering Research(HWAHAK KONGHAK), 2023, 61(2), 331, pp.217-225

2023

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Effect of serpentine flow-field designs on performance of PEMFC stacks for micro-CHP systems

Renewable energy, 2013-06, Vol.54, p.180-188

2013

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Three-dimensional, two-phase, CFD model for the design of a direct methanol fuel cell

Journal of power sources, 2006-11, Vol.162 (2), p.992-1002

2006

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A Data-based Predictive Model for Distillation Column of Bio-based 2,3-Butanediol

Computer Aided Chemical Engineering, 2021, Vol.50, p.1005-1011

2021

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A Study on the Sensitivity of a Spin Valve with Conetic-Based Free Layers

Japanese Journal of Applied Physics, 2012-03, Vol.51 (3R), p.33002

2012

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Gas management in flow field design using 3D direct methanol fuel cell model under high stoichiometric feed

The Korean journal of chemical engineering, 2006-09, Vol.23 (5), p.753-760

2006

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Machine Learning Approach to Predict Physical Properties of Polypropylene Composites: Application of MLR, DNN, and Random Forest to Industrial Data

One-Pot Transformation of Technical Lignins into Humic-Like Plant Stimulants through Fenton-Based Advanced Oxidation: Accelerating Natural Fungus-Driven Humification

Soft magnetic properties of conetic co-sputtered with aluminum

Development of physical property prediction models for polypropylene composites with optimizing random forest hyperparameters

Machine learning-based heat deflection temperature prediction and effect analysis in polypropylene composites using catboost and shapley additive explanations

Novel natural gradient boosting-based probabilistic prediction of physical properties for polypropylene-based composite data

A Study on the Sensitivity of a Spin Valve with Conetic-Based Free Layers

A novel graph-based missing values imputation method for industrial lubricant data

Dual attention-based multi-step ahead prediction enhancement for monitoring systems in industrial processes

Cover: International Journal of Intelligent Systems, Volume 37 Issue 6 June 2022

Data-driven modeling of multimode chemical process: Validation with a real-world distillation column

Enhancement of mass transport in fuel cells using three-dimensional graphene foam as flow field

Time-series clustering approach for training data selection of a data-driven predictive model: Application to an industrial bio 2,3-butanediol distillation process

Machine Learning-Based Adaptive Regression to Identify Nonlinear Dynamics of Biochemical Systems: A Case Study on Bio 2,3-Butanediol Distillation Process

Gas diffusion layer/flow-field unified membrane-electrode assembly in fuel cell using graphene foam

Dynamic Modeling of Acetone–Butanol–Ethanol Fermentation with ex Situ Butanol Recovery using Glucose/Xylose Mixtures

Multi-objective optimization of operation of lignocellulosic acetone-butanol-ethanol fermentation with ex situ butanol recovery (ESBR)

Correction to: A dynamic soft sensor based on hybrid neural networks to improve early off-spec detection

Mathematical Modeling of Acetone–Butanol–Ethanol Fermentation with Simultaneous Utilization of Glucose and Xylose by Recombinant Clostridium acetobutylicum

바이오 기반 2,3-butanediol 증류 공정의 제어 및 동적 최적화

Effect of serpentine flow-field designs on performance of PEMFC stacks for micro-CHP systems

Three-dimensional, two-phase, CFD model for the design of a direct methanol fuel cell

A Data-based Predictive Model for Distillation Column of Bio-based 2,3-Butanediol

A Study on the Sensitivity of a Spin Valve with Conetic-Based Free Layers

Gas management in flow field design using 3D direct methanol fuel cell model under high stoichiometric feed

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