Search Results - "Machine Learning Regression Algorithm"

Predicting specific wear rate of laser powder bed fusion AlSi10Mg parts at elevated temperatures using machine learning regression algorithm: Unveiling of microstructural morphology analysis

Authors: Vijaykumar S. Jatti R. Murali Krishnan A. Saiyathibrahim et al.

Source: Journal of Materials Research and Technology, Vol 33, Iss, Pp 3684-3695 (2024)

Subject Terms: Gaussian Process Regression algorithm, Specific Wear Rate, Mining engineering. Metallurgy, Machine Learning Regression Algorithm, Laser powder bed fusion, Specific wear rate, TN1-997, Laser Powder Bed Fusion, Machine learning regression algorithm, Prediction, MAE, RMSE

Access URL: https://doaj.org/article/3a2c2dfb50b6409594a00b9327819c0b

Mapping mangrove functional traits from Sentinel-2 imagery based on hybrid models coupled with active learning strategies

Authors: Mingming Jia Xianxian Guo Lin Zhang et al.

Source: International Journal of Applied Earth Observations and Geoinformation, Vol 130, Iss , Pp 103905- (2024)

Subject Terms: Mangrove functional traits, Active learning, Machine learning regression algorithm, Radiative transfer model, Sentinel-2, Physical geography, GB3-5030, Environmental sciences, GE1-350

File Description: electronic resource

Relation: http://www.sciencedirect.com/science/article/pii/S1569843224002590; https://doaj.org/toc/1569-8432

Access URL: https://doaj.org/article/2b944ebf01f04a6e933a15f4a19013b1

Simplifying Field Traversing Efficiency Estimation Using Machine Learning and Geometric Field Indices

Authors: Asiminari, Gavriela Benos, Lefteris Kateris, Dimitrios et al.

Contributors: Asiminari, Gavriela Benos, Lefteris Kateris, Dimitrios et al.

Subject Terms: agricultural machinery, computational time reduction, coverage path planning, farm management information system (FMIS), machine learning regression algorithm, precision agriculture, predictive modeling

Relation: info:eu-repo/semantics/altIdentifier/wos/WOS:001453474000001; volume:7; issue:3; numberofpages:18; journal:AGRIENGINEERING; https://hdl.handle.net/11583/3000491

Availability: https://hdl.handle.net/11583/3000491
https://doi.org/10.3390/agriengineering7030075

Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission

Authors: Gabriele Candiani Giulia Tagliabue Cinzia Panigada et al.

Source: Remote Sensing, Vol 14, Iss 8, p 1792 (2022)

Subject Terms: spaceborne imaging spectroscopy, radiative transfer modeling, machine learning regression algorithm, Gaussian process regression, active learning, chlorophyll content, Science

Relation: https://www.mdpi.com/2072-4292/14/8/1792; https://doaj.org/toc/2072-4292; https://doaj.org/article/64ca091a600a4b2880ff5e7c635e80da

Availability: https://doi.org/10.3390/rs14081792
https://doaj.org/article/64ca091a600a4b2880ff5e7c635e80da

Assessing maize nitrogen content from hyperspectral data through MLRA: preliminary results in a Precision Farming framework

Authors: Mirco Boschetti Gabriele Candiani Giulia Tagliabue et al.

Subject Terms: Precision Farming, Machine Learning Regression Algorithm, Nitrogen estimation

Access URL: https://hdl.handle.net/20.500.14243/370018

Physically Based, Machine Learning and Hybrid Approaches for Improved Plant Traits Retrievals from Future CHIME Hyperspectral Imagery

Authors: Gabriele Candiani Giulia Tagliabue Mirco Boschetti et al.

Subject Terms: Plant traits, CHIME, Machine Learning Regression Algorithm, Hyperspectral imagery

Access URL: https://hdl.handle.net/20.500.14243/367143

Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling

Authors: Ranghetti M. Boschetti M. Ranghetti L. et al.

Contributors: Ranghetti M. Boschetti M. Ranghetti L. et al.

Subject Terms: machine learning regression algorithm, plant nitrogen uptake estimation, Precision farming, radiative transfer model

File Description: ELETTRONICO

Relation: info:eu-repo/semantics/altIdentifier/pmid/38239331; info:eu-repo/semantics/altIdentifier/wos/WOS:000850110300001; volume:56; issue:1; journal:EUROPEAN JOURNAL OF REMOTE SENSING; https://hdl.handle.net/10281/529148

Availability: https://hdl.handle.net/10281/529148
https://doi.org/10.1080/22797254.2022.2117650

Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling

Authors: Ranghetti, M Boschetti, M Ranghetti, L et al.

Index Terms: machine learning regression algorithm, plant nitrogen uptake estimation, Precision farming, radiative transfer model, info:eu-repo/semantics/article

URL: https://hdl.handle.net/10281/529148
info:eu-repo/semantics/altIdentifier/pmid/38239331
info:eu-repo/semantics/altIdentifier/wos/WOS:000850110300001
volume:56
issue:1
journal:EUROPEAN JOURNAL OF REMOTE SENSING

Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission

Authors: Candiani, G Tagliabue, G Panigada, C et al.

Index Terms: active learning, chlorophyll content, Gaussian process regression, machine learning regression algorithm, nitrogen content, radiative transfer modeling, spaceborne imaging spectroscopy, info:eu-repo/semantics/article

URL: http://hdl.handle.net/10281/365965
info:eu-repo/semantics/altIdentifier/wos/WOS:000787404300001
volume:14
issue:8
firstpage:1
lastpage:22
numberofpages:22
journal:REMOTE SENSING