A review of deep learning approach to predicting the state of health and state of charge of lithium-ion batteries

K Luo, X Chen, H Zheng, Z Shi - Journal of Energy Chemistry, 2022 - Elsevier
In the field of energy storage, it is very important to predict the state of charge and the state of
health of lithium-ion batteries. In this paper, we review the current widely used equivalent …

Artificial intelligence in food safety: A decade review and bibliometric analysis

Z Liu, S Wang, Y Zhang, Y Feng, J Liu, H Zhu - Foods, 2023 - mdpi.com
Artificial Intelligence (AI) technologies have been powerful solutions used to improve food
yield, quality, and nutrition, increase safety and traceability while decreasing resource …

Agricultural technology in Africa

T Suri, C Udry - Journal of Economic Perspectives, 2022 - aeaweb.org
We discuss recent trends in agricultural productivity in Africa and highlight how
technological progress in agriculture has stagnated on the continent. We briefly review the …

Spatial cross-validation is not the right way to evaluate map accuracy

AMJC Wadoux, GBM Heuvelink, S De Bruin… - Ecological Modelling, 2021 - Elsevier
For decades scientists have produced maps of biological, ecological and environmental
variables. These studies commonly evaluate the map accuracy through cross-validation with …

[HTML][HTML] Progress in research on site-specific nutrient management for smallholder farmers in sub-Saharan Africa

P Chivenge, S Zingore, KS Ezui, S Njoroge… - Field crops …, 2022 - Elsevier
Increasing fertilizer access and use is an essential component for improving crop production
and food security in sub-Saharan Africa (SSA). However, given the heterogeneous nature of …

[HTML][HTML] Comparing the prediction performance, uncertainty quantification and extrapolation potential of regression kriging and random forest while accounting for soil …

B Takoutsing, GBM Heuvelink - Geoderma, 2022 - Elsevier
Geostatistics and machine learning have been extensively applied for modelling and
predicting the spatial distribution of continuous soil variables. In addition to providing …

The role of remote sensing data and methods in a modern approach to fertilization in precision agriculture

D Radočaj, M Jurišić, M Gašparović - Remote Sensing, 2022 - mdpi.com
The precision fertilization system is the basis for upgrading conventional intensive
agricultural production, while achieving both high and quality yields and minimizing the …

Predictive performance of machine learning model with varying sampling designs, sample sizes, and spatial extents

A Bouasria, Y Bouslihim, S Gupta… - Ecological …, 2023 - Elsevier
Using machine learning and earth observation data to capture real-world variability in
spatial predictive mapping depends on sample size, design, and spatial extent …

Assessing machine learning-based prediction under different agricultural practices for digital mapping of soil organic carbon and available phosphorus

F Kaya, A Keshavarzi, R Francaviglia, G Kaplan… - Agriculture, 2022 - mdpi.com
Predicting soil chemical properties such as soil organic carbon (SOC) and available
phosphorus (Ava-P) content is critical in areas where different land uses exist. The …

Uncertainty quantification for probabilistic machine learning in earth observation using conformal prediction

G Singh, G Moncrieff, Z Venter, K Cawse-Nicholson… - Scientific Reports, 2024 - nature.com
Abstract Machine learning is increasingly applied to Earth Observation (EO) data to obtain
datasets that contribute towards international accords. However, these datasets contain …