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Comparative study of surrogate approaches while optimizing computationally expensive reaction networks

Chemical engineering science, 2016-02, Vol.140, p.44-61

2016

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Identification of unstructured model for subtilin production through Bacillus subtilis using hybrid genetic algorithm

Process biochemistry (1991), 2017-09, Vol.60, p.1-12

2017

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In search of flexible and robust wind farm layouts considering wind state uncertainty

Journal of cleaner production, 2020-03, Vol.248, p.119195, Article 119195

2020

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Multiobjective optimization of an industrial grinding operation under uncertainty

Chemical engineering science, 2009-12, Vol.64 (23), p.5043-5056

Mitra, Kishalay

2009

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Deep learning based system identification of industrial integrated grinding circuits

Powder technology, 2020-01, Vol.360, p.921-936

2020

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Optimal surrogate building using SVR for an industrial grinding process

Materials and manufacturing processes, 2022-11, Vol.37 (15), p.1701-1707

2022

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Determining layout of a wind farm with optimal number of turbines: A decomposition based approach

Journal of cleaner production, 2018-11, Vol.202, p.342-359

2018

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Multi-objective optimization of iron ore induration process using optimal neural networks

Materials and manufacturing processes, 2020-04, Vol.35 (5), p.537-544

2020

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Robust optimization of cascaded MSMPR crystallization unit using unsupervised machine learning

Canadian journal of chemical engineering, 2024-07

2024

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Micrositing under practical constraints addressing the energy‐noise‐cost trade‐off

Wind energy (Chichester, England), 2020-10, Vol.23 (10), p.1905-1918

2020

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A novel hybrid optimization methodology to optimize the total number and placement of wind turbines

Renewable energy, 2016-02, Vol.86, p.133-147

2016

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Deep learning based dynamic behavior modelling and prediction of particulate matter in air

Chemical engineering journal (Lausanne, Switzerland : 1996), 2021-12, Vol.426, p.131221, Article 131221

2021

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TRANSFORM-ANN for online optimization of complex industrial processes: Casting process as case study

European journal of operational research, 2018-01, Vol.264 (1), p.294-309

2018

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Assessing optimal growth of desired species in epoxy polymerization under uncertainty

Chemical engineering journal (Lausanne, Switzerland : 1996), 2010-08, Vol.162 (1), p.322-330

Mitra, Kishalay

2010

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Intuitionistic Fuzzy Chance Constrained Programming for Handling Parametric Uncertainty: An Industrial Grinding Case Study

Industrial & engineering chemistry research, 2015-06, Vol.54 (24), p.6291-6304

2015

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Multi-objective optimization through a novel Bayesian approach for industrial manufacturing of Polyvinyl Acetate

Materials and manufacturing processes, 2023-11, Vol.38 (15), p.1955-1963

2023

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Toward Faster Operational Optimization of Cascaded MSMPR Crystallizers Using Multiobjective Support Vector Regression

Industrial & engineering chemistry research, 2022-08, Vol.61 (31), p.11518-11533

2022

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Recurrent neural networks based modelling of industrial grinding operation

Chemical engineering science, 2020-06, Vol.219, p.115585, Article 115585

2020

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Better wind forecasting using Evolutionary Neural Architecture search driven Green Deep Learning

Expert systems with applications, 2023-03, Vol.214, p.119063, Article 119063

2023

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Fuzzy Expected Value Analysis of an Industrial Grinding Process

Powder technology, 2014-12, Vol.268, p.9-18

2014

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Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach

Energy conversion and management, 2017-01, Vol.132, p.147-160

2017

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Towards Efficient Robust Optimization using Data based Optimal Segmentation of Uncertain Space

Reliability engineering & system safety, 2020-05, Vol.197, p.106821-13, Article 106821

2020

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A data-driven approach towards finding closer estimates of optimal solutions under uncertainty for an energy efficient steel casting process

Energy (Oxford), 2019-12, Vol.189, p.116253, Article 116253

2019

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Towards Faster Multi-Objective Surrogate Optimization using SVR: A Casting Case Study

Transactions of the Indian Institute of Metals, 2023-08

2023

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A novel data-driven sampling strategy for optimizing industrial grinding operation under uncertainty using chance constrained programming

Powder technology, 2021-01, Vol.377, p.913-923

2021

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Comparative study of surrogate approaches while optimizing computationally expensive reaction networks

Identification of unstructured model for subtilin production through Bacillus subtilis using hybrid genetic algorithm

In search of flexible and robust wind farm layouts considering wind state uncertainty

Multiobjective optimization of an industrial grinding operation under uncertainty

Deep learning based system identification of industrial integrated grinding circuits

Optimal surrogate building using SVR for an industrial grinding process

Determining layout of a wind farm with optimal number of turbines: A decomposition based approach

Multi-objective optimization of iron ore induration process using optimal neural networks

Robust optimization of cascaded MSMPR crystallization unit using unsupervised machine learning

Micrositing under practical constraints addressing the energy‐noise‐cost trade‐off

A novel hybrid optimization methodology to optimize the total number and placement of wind turbines

Deep learning based dynamic behavior modelling and prediction of particulate matter in air

TRANSFORM-ANN for online optimization of complex industrial processes: Casting process as case study

Assessing optimal growth of desired species in epoxy polymerization under uncertainty

Intuitionistic Fuzzy Chance Constrained Programming for Handling Parametric Uncertainty: An Industrial Grinding Case Study

Multi-objective optimization through a novel Bayesian approach for industrial manufacturing of Polyvinyl Acetate

Toward Faster Operational Optimization of Cascaded MSMPR Crystallizers Using Multiobjective Support Vector Regression

Recurrent neural networks based modelling of industrial grinding operation

Better wind forecasting using Evolutionary Neural Architecture search driven Green Deep Learning

Fuzzy Expected Value Analysis of an Industrial Grinding Process

Optimizing the number and locations of turbines in a wind farm addressing energy-noise trade-off: A hybrid approach

Towards Efficient Robust Optimization using Data based Optimal Segmentation of Uncertain Space

A data-driven approach towards finding closer estimates of optimal solutions under uncertainty for an energy efficient steel casting process

Towards Faster Multi-Objective Surrogate Optimization using SVR: A Casting Case Study

A novel data-driven sampling strategy for optimizing industrial grinding operation under uncertainty using chance constrained programming

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