A comparison of machine learning algorithms for regional wheat yield prediction using NDVI time series of SPOT-VGT

2016 Fifth International Conference on Agro-Geoinformatics (Agro-Geoinformatics) ◽

10.1109/agro-geoinformatics.2016.7577625 ◽

2016 ◽

Author(s):

Michiel Stas ◽

Jos Van Orshoven ◽

Qinghan Dong ◽

Stien Heremans ◽

Beier Zhang

Keyword(s):

Machine Learning ◽

Time Series ◽

Learning Algorithms ◽

Wheat Yield ◽

Machine Learning Algorithms ◽

Yield Prediction ◽

Ndvi Time Series

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Discriminating the Mediterranean Pinus spp. using the land surface phenology extracted from the whole MODIS NDVI time series and machine learning algorithms

Earth Resources and Environmental Remote Sensing/GIS Applications VIII ◽

10.1117/12.2278557 ◽

2017 ◽

Author(s):

Victor F. Rodriguez-Galiano ◽

David Aragones ◽

Jose A. Caparros-Santiago ◽

Rafael M. Navarro-Cerrillo

Keyword(s):

Machine Learning ◽

Time Series ◽

Land Surface ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Land Surface Phenology ◽

Ndvi Time Series ◽

The Mediterranean ◽

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Exploitation of time series Sentinel-2 data and different machine learning algorithms for detailed tree species classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing ◽

10.1109/jstars.2021.3098817 ◽

2021 ◽

pp. 1-1

Author(s):

Yanbiao Xi ◽

Chunying Ren ◽

Qingjiu Tian ◽

Yongxing Ren ◽

Xinyu Dong ◽

...

Keyword(s):

Machine Learning ◽

Time Series ◽

Tree Species ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Species Classification ◽

Tree Species Classification ◽

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Comparative assessment of environmental variables and machine learning algorithms for maize yield prediction in the US Midwest

Environmental Research Letters ◽

10.1088/1748-9326/ab7df9 ◽

2020 ◽

Vol 15 (6) ◽

pp. 064005

Author(s):

Yanghui Kang ◽

Mutlu Ozdogan ◽

Xiaojin Zhu ◽

Zhiwei Ye ◽

Christopher Hain ◽

...

Keyword(s):

Machine Learning ◽

Environmental Variables ◽

Learning Algorithms ◽

Maize Yield ◽

Comparative Assessment ◽

Machine Learning Algorithms ◽

Yield Prediction ◽

The Us ◽

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Benchmarking Machine Learning Algorithms on Blood Glucose Prediction for Type I Diabetes in Comparison With Classical Time-Series Models

IEEE Transactions on Biomedical Engineering ◽

10.1109/tbme.2020.2975959 ◽

2020 ◽

Vol 67 (11) ◽

pp. 3101-3124 ◽

Author(s):

Jinyu Xie ◽

Qian Wang

Keyword(s):

Machine Learning ◽

Time Series ◽

Blood Glucose ◽

Type I Diabetes ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Time Series Models ◽

Type I ◽

Glucose Prediction

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Wild blueberry yield prediction using a combination of computer simulation and machine learning algorithms

Computers and Electronics in Agriculture ◽

10.1016/j.compag.2020.105778 ◽

2020 ◽

Vol 178 ◽

pp. 105778 ◽

Author(s):

Efrem Yohannes Obsie ◽

Hongchun Qu ◽

Francis Drummond

Keyword(s):

Machine Learning ◽

Computer Simulation ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Yield Prediction ◽

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Research on machine learning algorithms and feature extraction for time series

2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) ◽

10.1109/pimrc.2017.8292668 ◽

2017 ◽

Author(s):

Lei Li ◽

Yabin Wu ◽

Yihang Ou ◽

Qi Li ◽

Yanquan Zhou ◽

...

Keyword(s):

Machine Learning ◽

Time Series ◽

Feature Extraction ◽

Learning Algorithms ◽

Machine Learning Algorithms

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Jump detection in financial time series using machine learning algorithms

Soft Computing ◽

10.1007/s00500-019-04006-2 ◽

2019 ◽

Vol 24 (3) ◽

pp. 1789-1801 ◽

Author(s):

Jay F. K. Au Yeung ◽

Zi-kai Wei ◽

Kit Yan Chan ◽

Henry Y. K. Lau ◽

Ka-Fai Cedric Yiu

Keyword(s):

Machine Learning ◽

Time Series ◽

Financial Time Series ◽

Learning Algorithms ◽

Machine Learning Algorithms ◽

Jump Detection ◽

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Time-Series Data Classification and Analysis Associated With Machine Learning Algorithms for Cognitive Perception and Phenomenon

IEEE Access ◽

10.1109/access.2020.3018477 ◽

2020 ◽

Vol 8 ◽

pp. 222417-222428

Author(s):

Taikyeong Jeong

Keyword(s):

Machine Learning ◽

Time Series ◽

Time Series Data ◽

Learning Algorithms ◽

Data Classification ◽

Machine Learning Algorithms ◽

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Rainfall prediction: A comparative analysis of modern machine learning algorithms for time-series forecasting

Machine Learning with Applications ◽

10.1016/j.mlwa.2021.100204 ◽

2021 ◽

pp. 100204

Author(s):

Ari Yair Barrera-Animas ◽

Lukumon Oladayo Oyedele ◽

Muhammad Bilal ◽

Taofeek Dolapo Akinosho ◽

Juan Manuel Davila Delgado ◽

...

Keyword(s):

Machine Learning ◽

Time Series ◽

Comparative Analysis ◽

Learning Algorithms ◽

Time Series Forecasting ◽

Machine Learning Algorithms ◽

Rainfall Prediction ◽

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Eagle View: An Abstract Evaluation of Machine Learning Algorithms based on Data Properties

10.36227/techrxiv.14459361.v1 ◽

2021 ◽

Author(s):

Dhairya Vyas

Keyword(s):

Machine Learning ◽

Time Series ◽

Time Series Data ◽

Learning Algorithms ◽

Numerical Data ◽

Machine Learning Algorithms ◽

Series Data ◽

Learning Methods ◽

Machine Learning Methods ◽

In terms of Machine Learning, the majority of the data can be grouped into four categories: numerical data, category data, time-series data, and text. We use different classifiers for different data properties, such as the Supervised; Unsupervised; and Reinforcement. Each Categorises has classifier we have tested almost all machine learning methods and make analysis among them.

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