Results 1 to 10 of about 25,590 (247)

A PLSR model to predict soil salinity using Sentinel-2 MSI data

Open Geosciences, 2021
Salinization is one of the most widespread environmental threats in arid and semi-arid regions that occur either naturally or artificially within the soil. When exceeding the thresholds, salinity becomes a severe danger, damaging agricultural production,
Sahbeni Ghada
doaj   +2 more sources

Dynamic monitoring oxidation process of nut oils through Raman technology combined with PLSR and RF-PLSR model

LWT, 2021
Abstract During preservation of nuts, nut oils are easily oxidized; hence, peroxide value (PV) is an important evaluation index. In this study, a novel method for the determination of the PV of nuts based on partial-least-square regression (PLSR) and Forest random PLSR (RF-PLSR) model was established. Meanwhile, the Raman spectrum was processed by 24
Cheng Wang, Yingying Sun, Yanyu Zhou, Yiwen Cui, Weirong Yao, Hang Yu, Yahui Guo, Yunfei Xie   +7 more
openaire   +2 more sources

An Modified PLSR Method in Prediction

Journal of Data Science, 2021
Among many statistical methods for linear models with the mul- ticollinearity problem, partial least squares regression (PLSR) has become, in recent years, increasingly popular and, very often, the best choice. How- ever, while dealing with the predicting problem from automobile market, we noticed that the results from PLSR appear unstable though it is
Bo Cheng, Xizhi Wu
openaire   +2 more sources

Rapid detection method of soybean seed germination potential based on the PLSR-MLP fusion model [PDF]

Frontiers in Plant Science
In order to realize the rapid detection of soybean seed germination potential, this study designed a fusion model to solve the problem that the single model was insufficient in spectral feature analysis and the prediction performance was limited.
Shuo Liu, Zhengguang Chen
doaj   +2 more sources

A novel robust PLS regression method inspired from boosting principles: RoBoost-PLSR

Analytica Chimica Acta, 2021
The calibration of Partial Least Square regression (PLSR) models can be disturbed by outlying samples in the data. In these cases the models can be unstable and their predictive potential can be depreciated. To address this problem, some robust versions of the PLSR Algorithm were proposed.
Metz, Maxime, Abdelghafour, Florent, Roger, Jean-Michel, Lesnoff, Matthieu   +3 more
openaire   +6 more sources

PENERAPAN METODE PARTIAL LEAST SQUARE REGRESSION (PLSR) PADA KASUS SKIZOFRENIA

E-Jurnal Matematika, 2021
Partial Least Square Regression (PLSR) is a method that combines principal component analysis and multiple linear regression, which aims to predict or analyze the dependent variable and more than one independent variable.
NI WAYAN ARI SUNDARI, I GUSTI AYU MADE SRINADI, MADE SUSILAWATI   +2 more
doaj   +3 more sources

مدل‌سازی رقومی جزء شن خاک با داده‌های ابرطیفی [PDF]

پژوهش‌های حفاظت آب و خاک, 2021
سابقه و هدف: جزء شن از مهمترین اجزای بافت خاک بوده که برای عملیات مدل‌سازی زیست‌محیطی و پهنه‌بندی رقومی خاک، باید مورد توجه واقع شود. از طرفی، بدلیل تغییرپذیری مکانی این جزء؛ تشخیص، پهنه‌بندی و پایش آن، در مقیاس‌های وسیع، با استفاده از شیوه‌های سنتی رایج
مجید دانش, حسینعلی بهرامی   +1 more
doaj   +1 more source

Detection of encapsulant addition in butterfly-pea (Clitoria ternatea L.) extract powder using visible–near-infrared spectroscopy and chemometrics analysis

Open Agriculture, 2022
Butterfly-pea (Clitoria ternatea L.) extract powder is a functional product with numerous benefits obtained by extraction followed by the drying process.
Rahmawati Laila, Pahlawan Muhammad Fahri Reza, Hariadi Hari, Masithoh Rudiati Evi   +3 more
doaj   +1 more source

Predicting Models for Plant Metabolites Based on PLSR, AdaBoost, XGBoost, and LightGBM Algorithms Using Hyperspectral Imaging of Brassica juncea

Agriculture, 2023
The integration of hyperspectral imaging with machine learning algorithms has presented a promising strategy for the non-invasive and rapid detection of plant metabolites.
Hyo-In Yoon, Hyein Lee, Jung-Seok Yang, Jae-Hyeong Choi, D. Jung, Y. Park, Jai-Eok Park, Sang Min Kim, S. Park   +8 more
semanticscholar   +1 more source

Averaging a local PLSR pipeline to predict chemical compositions and nutritive values of forages and feed from spectral near infrared data

bioRxiv, 2023
Partial least squares regression (PLSR) is a reference method in chemometrics. In agronomy, it is used for instance to predict components of chemical composition (response variables y) of vegetal materials from spectral near infrared (NIR) data X ...
M. Lesnoff
semanticscholar   +1 more source