Comparing the performance of machine learning algorithms for remote and in situ estimations of chlorophyll‐a content: a case study in the Tri An Reservoir, Vietnam

Chlorophyll A Content

2020 International Conference on Advances in Computing, Communication & Materials (ICACCM) ◽

Twitter Sentiment Analysis Using Machine Learning Algorithms: A Case Study

10.1109/icaccm50413.2020.9213011 ◽

2020 ◽

Author(s):

Sheresh Zahoor ◽

Rajesh Rohilla

Keyword(s):

Machine Learning ◽

Sentiment Analysis ◽

Learning Algorithms ◽

Estimating Lead Time Using Machine Learning Algorithms: A Case Study by a Textile Company

10.1109/asyu52992.2021.9599012 ◽

2021 ◽

Author(s):

Ceren Atik ◽

Recen Alp Kut ◽

Safak Birol

Keyword(s):

Machine Learning ◽

Lead Time ◽

Learning Algorithms ◽

Proceedings of International Exchange and Innovation Conference on Engineering & Sciences (IEICES) ◽

Detection of Slums from Very High-Resolution Satellite Images Using Machine Learning Algorithms: A Case Study of Fustat Area in Cairo, Egypt

10.5109/4102491 ◽

2020 ◽

Vol 6 ◽

pp. 219-224

Author(s):

Muhammad Salem ◽

Naoki Tsurusaki ◽

Ahmed Eissa ◽

Taher Osman

Keyword(s):

Machine Learning ◽

High Resolution ◽

Satellite Images ◽

Learning Algorithms ◽

High Resolution Satellite Images ◽

Very High

In situ investigation and detection of opto-mechanical properties of polymeric fibres from their digital distorted microinterferograms using machine learning algorithms

Optics & Laser Technology ◽

10.1016/j.optlastec.2020.106295 ◽

2020 ◽

Vol 129 ◽

pp. 106295

Author(s):

E.Z. Omar ◽

T.Z.N. Sokkar ◽

A.A. Hamza

Keyword(s):

Machine Learning ◽

Mechanical Properties ◽

Learning Algorithms ◽

In Situ Investigation

Identification of multi-element geochemical anomalies using unsupervised machine learning algorithms: A case study from Ag–Pb–Zn deposits in north-western Zhejiang, China

Applied Geochemistry ◽

10.1016/j.apgeochem.2020.104679 ◽

2020 ◽

Vol 120 ◽

pp. 104679 ◽

Cited By ~ 2

Author(s):

Jun Wang ◽

Yongzhang Zhou ◽

Fan Xiao

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Unsupervised Machine Learning ◽

Geochemical Anomalies ◽

North Western

A Comparison Framework of Machine Learning Algorithms for Mixed-Type Variables Datasets: A Case Study on Tire-Performances Prediction

IEEE Access ◽

10.1109/access.2020.3041367 ◽

2020 ◽

Vol 8 ◽

pp. 214902-214914

Author(s):

Leonardo Gutierrez-Gomez ◽

Frank Petry ◽

Djamel Khadraoui

Keyword(s):

Machine Learning ◽

Mixed Type ◽

Learning Algorithms ◽

Coupling In Situ Microstructure Observation with Machine Learning Algorithms for Damage Diagnostics and Prognostics

Structural Health Monitoring 2017 ◽

10.12783/shm2017/14007 ◽

2017 ◽

Author(s):

BRIAN J. WISNER ◽

ANTONIOS KONTSOS

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Microstructure Observation ◽

Damage Diagnostics

Proceedings of the 5th International Conference on Information Systems Security and Privacy ◽

Predicting CyberSecurity Incidents using Machine Learning Algorithms: A Case Study of Korean SMEs

10.5220/0007309302300237 ◽

2019 ◽

Cited By ~ 1

Author(s):

Alaa Mohasseb ◽

Benjamin Aziz ◽

Jeyong Jung ◽

Julak Lee

Keyword(s):

Machine Learning ◽

Learning Algorithms ◽

Assessment of GIS-Based Machine Learning Algorithms for Spatial Modeling of Landslide Susceptibility: Case Study in Iran

Comprehensive Geographic Information Systems ◽

10.1016/b978-0-12-409548-9.10461-0 ◽

2018 ◽

pp. 258-280 ◽

Cited By ~ 4

Author(s):

Alireza Motevalli ◽

Hamid Reza Pourghasemi ◽

Mohsen Zabihi

Keyword(s):

Machine Learning ◽

Spatial Modeling ◽

Landslide Susceptibility ◽

Learning Algorithms ◽

Lead time prediction using machine learning algorithms: A case study by a semiconductor manufacturer

Procedia CIRP ◽

10.1016/j.procir.2018.03.148 ◽

2018 ◽

Vol 72 ◽

pp. 1051-1056 ◽

Cited By ~ 20

Author(s):

Lukas Lingitz ◽

Viola Gallina ◽

Fazel Ansari ◽

Dávid Gyulai ◽

András Pfeiffer ◽

...

Keyword(s):

Machine Learning ◽

Lead Time ◽

Learning Algorithms ◽

Time Prediction ◽

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