Results 21 to 30 of about 890,584 (243)

Spatial prediction of soil properties in two contrasting physiographic regions in Brazil

open access: yesScientia Agricola, 2016
This study compared the performance of ordinary kriging (OK) and regression kriging (RK) to predict soil physical-chemical properties in topsoil (0-15 cm).
Michele Duarte de Menezes   +4 more
doaj   +1 more source

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

open access: yesThe Scientific World Journal, 2012
Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as ...
Jaber Almedeij
doaj   +1 more source

A Comparison of Four Spatial Interpolation Methods for Modeling Fine-Scale Surface Fuel Load in a Mixed Conifer Forest with Complex Terrain

open access: yesFire, 2023
Patterns of spatial heterogeneity in forests and other fire-prone ecosystems are increasingly recognized as critical for predicting fire behavior and subsequent fire effects.
Chad M. Hoffman   +4 more
doaj   +1 more source

Integration of Regression Analysis and Spatial Interpolation in Multi-Sensor Soil Calibration Optimization Based on RS485 to Support Precision Agriculture

open access: yesJurnal Keteknikan Pertanian Tropis dan Biosistem
Technological developments provide significant opportunities to utilisemeasurement equipment to enhance the effectiveness and efficiency of agricultural production. Accurate soil content measurement is very important for
Budi Priyonggo   +6 more
doaj   +1 more source

REMEDY OF EFFECTS OF MULTICOLLINEARITY IN MULTIPLE LINEAR REGRESSION MODEL [PDF]

open access: yesFayoum Journal of Agricultural Research and Development, 2019
Assuming that there is no complete linear relationship between theindependent variables in the multiple linear regression models leads to themulticollinearity problem.
M. A. Gad, H. F. M. Hussein
doaj   +1 more source

Regression analyses of the data sets for the analysis of decomposition error in discrete-time open tandem queues

open access: yesData in Brief, 2022
The data sets and regression models presented here are related to the article “Point and interval estimation of decomposition error in discrete-time open tandem queues” [1]. The data sets are the first to analyze the approximation quality of the discrete-
Christoph Jacobi, Kai Furmans
doaj   +1 more source

PERBANDINGAN METODE MULTIPLE LINEAR REGRESSION (MLR) DAN REGRESSION KRIGING (RK) DALAM PEMETAAN KETEBALAN TANAH DIGITAL

open access: yesJTSL (Jurnal Tanah dan Sumberdaya Lahan), 2023
Soil thickness has a significant influence on many of earth surface processes, and it can be mapped using various methods. Digital soil mapping can be used to estimate the spatial distribution of soil thickness and can estimate the uncertainty of the ...
Muhammad Fauzan Ramadhan   +3 more
doaj   +1 more source

Guidelines for Pediatric Radiotherapy Simulation: A Report From the Children's Oncology Group Radiation Oncology Discipline

open access: yesPediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric radiation therapy presents unique challenges compared to adult treatments, including those of immobilization, potential need for sedation, and the critical importance of accurate, reproducible positioning. Additionally, heightened attention to imaging doses is necessary to minimize long‐term toxicity in survivors.
Parham Alaei   +17 more
wiley   +1 more source

Overparameterized multiple linear regression as hyper-curve fitting

open access: yesMachine Learning: Science and Technology
This work demonstrates that applying a fixed-effect multiple linear regression model to an overparameterized dataset is mathematically equivalent to fitting a hyper-curve parameterized by a single scalar.
Elisa Atza, Neil Budko
doaj   +1 more source

A learning system-based soft multiple linear regression model

open access: yesIntelligent Systems with Applications
Machine learning applied to regression models offers powerful mathematical tools for predicting responses based on one or more predictor variables.
Gholamreza Hesamian   +3 more
doaj   +1 more source

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