Machine learning technology in biodiesel research: A review
M Aghbashlo, W Peng, M Tabatabaei… - Progress in Energy and …, 2021 - Elsevier
Biodiesel has the potential to significantly contribute to making transportation fuels more
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …
A review of machine learning for near-infrared spectroscopy
The analysis of infrared spectroscopy of substances is a non-invasive measurement
technique that can be used in analytics. Although the main objective of this study is to …
technique that can be used in analytics. Although the main objective of this study is to …
Machine learning algorithm validation with a limited sample size
Advances in neuroimaging, genomic, motion tracking, eye-tracking and many other
technology-based data collection methods have led to a torrent of high dimensional …
technology-based data collection methods have led to a torrent of high dimensional …
A deep learning CNN architecture applied in smart near-infrared analysis of water pollution for agricultural irrigation resources
Water is a natural resource for agricultural irrigation. Recycling use of water is important in
terms of resource conservation and is good for sustainable development of the ecological …
terms of resource conservation and is good for sustainable development of the ecological …
Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra
No single instrument can characterize all soil properties because soil is a complex material.
With the advancement of technology, laboratories have become equipped with various …
With the advancement of technology, laboratories have become equipped with various …
[图书][B] Model-based clustering and classification for data science: with applications in R
Cluster analysis finds groups in data automatically. Most methods have been heuristic and
leave open such central questions as: how many clusters are there? Which method should I …
leave open such central questions as: how many clusters are there? Which method should I …
Estimating the distribution trend of soil heavy metals in mining area from HyMap airborne hyperspectral imagery based on ensemble learning
The problem of heavy metal pollution of soils in China is severe. The traditional spectral
methods for soil heavy metal monitoring and assessment cannot meet the needs for large …
methods for soil heavy metal monitoring and assessment cannot meet the needs for large …
Parameter investigation of support vector machine classifier with kernel functions
A Tharwat - Knowledge and Information Systems, 2019 - Springer
Support vector machine (SVM) is one of the well-known learning algorithms for classification
and regression problems. SVM parameters such as kernel parameters and penalty …
and regression problems. SVM parameters such as kernel parameters and penalty …
One‐dimensional convolutional neural networks for spectroscopic signal regression
S Malek, F Melgani, Y Bazi - Journal of Chemometrics, 2018 - Wiley Online Library
This paper proposes a novel approach for driving chemometric analyses from spectroscopic
data and based on a convolutional neural network (CNN) architecture. For such purpose …
data and based on a convolutional neural network (CNN) architecture. For such purpose …
Hyperspectral imaging analysis for ripeness evaluation of strawberry with support vector machine
C Guo, F Liu, W Kong, Y He, B Lou - Journal of Food Engineering, 2016 - Elsevier
A hyperspectral imaging system covering two spectral ranges (380–1030 nm and 874–1734
nm) was applied to evaluate strawberry ripeness. The spectral data were extracted from …
nm) was applied to evaluate strawberry ripeness. The spectral data were extracted from …