A comparative study of machine learning models for predicting the state of reactive mixing

Journal of Computational Physics ◽

10.1016/j.jcp.2021.110147 ◽

2021 ◽

Vol 432 ◽

pp. 110147

Author(s):

B. Ahmmed ◽

M.K. Mudunuru ◽

S. Karra ◽

S.C. James ◽

V.V. Vesselinov

Keyword(s):

Machine Learning ◽

Comparative Study ◽

The State ◽

Learning Models ◽

Reactive Mixing ◽

Machine Learning Models

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A Comparative Study of Machine Learning Models for Stock Market Rate Prediction

International Journal of Computer Sciences and Engineering ◽

10.26438/ijcse/v7i6.985990 ◽

2019 ◽

Vol 7 (6) ◽

pp. 985-990

Author(s):

reeraksha M S ◽

Bhargavi M S

Keyword(s):

Machine Learning ◽

Stock Market ◽

Comparative Study ◽

Learning Models ◽

Rate Prediction ◽

Market Rate ◽

Machine Learning Models

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A Comparative Study for Efficient Covid-19 Detecting Machine Learning Models on CT Images

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/1099/1/012056 ◽

2021 ◽

Vol 1099 (1) ◽

pp. 012056

Author(s):

Ankur Chaturvedi ◽

Divyansh Mishra ◽

Dr. Vikram Rajpoot ◽

Janvi Gupta ◽

Aditi Sharma

Keyword(s):

Machine Learning ◽

Comparative Study ◽

Ct Images ◽

Learning Models ◽

Machine Learning Models

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A Comparative Study on Machine Learning Models for Paprika Growth Prediction Model with Temperature Changes

The Journal of Korean Institute of Communications and Information Sciences ◽

10.7840/kics.2021.46.12.2393 ◽

2021 ◽

Vol 46 (12) ◽

pp. 2393-2402

Author(s):

SaravanaKumar Venkatesan ◽

Jonghyun Lim ◽

Chanagsun Shin ◽

Yongyun Cho

Keyword(s):

Machine Learning ◽

Comparative Study ◽

Prediction Model ◽

Learning Models ◽

Growth Prediction ◽

Temperature Changes ◽

Machine Learning Models

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River water quality index prediction and uncertainty analysis: A comparative study of machine learning models

Journal of Environmental Chemical Engineering ◽

10.1016/j.jece.2020.104599 ◽

2020 ◽

pp. 104599

Author(s):

Seyed Babak Haji Seyed Asadollah ◽

Ahmad Sharafati ◽

Davide Motta ◽

Zaher Mundher Yaseen

Keyword(s):

Machine Learning ◽

Water Quality ◽

Comparative Study ◽

Uncertainty Analysis ◽

River Water ◽

Water Quality Index ◽

Quality Index ◽

River Water Quality ◽

Learning Models ◽

Machine Learning Models

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A Comparative Study of Machine Learning Models in Predicting Energy Consumption

10.1007/978-3-030-90275-9_13 ◽

2021 ◽

pp. 154-161

Author(s):

Ana Isabel Perez Cano ◽

Hongrui Liu

Keyword(s):

Machine Learning ◽

Energy Consumption ◽

Comparative Study ◽

Learning Models ◽

Machine Learning Models

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Comparative Study of Different Machine Learning Models for Measurement of QoE Based on MOS in Wireless Networks

10.1007/978-981-16-5207-3_18 ◽

2021 ◽

pp. 201-213

Author(s):

Kalpana Saha Roy ◽

Soumyadeep Malakar

Keyword(s):

Machine Learning ◽

Wireless Networks ◽

Comparative Study ◽

Learning Models ◽

Machine Learning Models

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Comparative Study of Different Machine Learning Models for Breast Cancer Diagnosis

Innovations in Soft Computing and Information Technology ◽

10.1007/978-981-13-3185-5_3 ◽

2019 ◽

pp. 17-25 ◽

Author(s):

Aman Kumar ◽

M. Poonkodi

Keyword(s):

Breast Cancer ◽

Machine Learning ◽

Comparative Study ◽

Cancer Diagnosis ◽

Breast Cancer Diagnosis ◽

Learning Models ◽

Machine Learning Models

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Machine learning models for predicting ship main engine Fuel Oil Consumption: A comparative study

Ocean Engineering ◽

10.1016/j.oceaneng.2019.106282 ◽

2019 ◽

Vol 188 ◽

pp. 106282 ◽

Author(s):

Christos Gkerekos ◽

Iraklis Lazakis ◽

Gerasimos Theotokatos

Keyword(s):

Machine Learning ◽

Comparative Study ◽

Fuel Oil ◽

Engine Fuel ◽

Learning Models ◽

Oil Consumption ◽

Main Engine ◽

Machine Learning Models

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Comparative study of shallow and deep machine learning models for synthesizing in situ NMR T2 distributions

Machine Learning for Subsurface Characterization ◽

10.1016/b978-0-12-817736-5.00008-9 ◽

2020 ◽

pp. 219-241

Author(s):

Siddharth Misra ◽

Hao Li

Keyword(s):

Machine Learning ◽

Comparative Study ◽

Learning Models ◽

In Situ Nmr ◽

Machine Learning Models

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Physics-informed machine learning models for predicting the progress of reactive-mixing

Computer Methods in Applied Mechanics and Engineering ◽

10.1016/j.cma.2020.113560 ◽

2021 ◽

Vol 374 ◽

pp. 113560

Author(s):

M.K. Mudunuru ◽

S. Karra

Keyword(s):

Machine Learning ◽

Learning Models ◽

Reactive Mixing ◽

Machine Learning Models

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