BIOENGINEER

Interpretable Quantum Regression Algorithm Encodes Classical Data Tables Directly into States

Researchers have formulated an inherently interpretable quantum regression algorithm that directly encodes classical data ...
BIOENGINEER

Regression Data Augmentation Boosts Neural Network Prediction for Composite Joint Failure Loads

A hybrid modeling framework uses multiple linear regression data augmentation to enhance neural network predictions of ...
europesays

Optimizing net-zero energy strategies in airports through a hybrid multi-method framework

This section reviews the current literature on multi-criteria decision-making (MCDM) methods in sustainable energy planning, ...
eLife

Dual reinforcement-learning network modules for modeling decision-making with multiple strategies

Laboratory of Neural Computation, Institute for Quantitative Biosciences, the University of Tokyo, Tokyo, Japan Department of Life Sciences, Graduate School of Arts and Sciences, the University of ...
GitHub

README.md

This resource is devoted to studies and research on global sugar price prediction. It functions as a complete resource, ...
eLife

Extinction risk in terrestrial vertebrates is associated with niche limits that reflect climatic vulnerability

This important study examines the relationship between climatic niche limits and extinction risk across more than 23,000 terrestrial vertebrate species. The large comparative dataset and phylogenetic ...
casrai.org

Multiple Regression in SPSS: Entry Methods, Diagnostics, and Reporting

SPSS runs multiple linear regression through Analyze > Regression > Linear, and the single most consequential choice in that dialog is the one researchers skip past fastest: the Method dropdown. Enter ...
PNAS

Comparing variable selection and model averaging methods for logistic regression

Logistic regression is a statistical method used to model binary outcome variables, such as whether a patient recovers or not, using a set of predictors. There are many competing methods for ...
learn

Demand forecasting algorithms

In addition, Demand planning provides a best fit model algorithm, which automatically selects the best of the available algorithms for each product and dimension combination. Demand planning also lets ...
IEEE

Soil Moisture Estimation From Spire GNSS-Reflectometry Reflectivity: Semi-Empirical and Linear Regression Methods

Abstract: This study develops semi-empirical and linear regression algorithms to estimate near-surface soil moisture (SM) using reflectivity observations of Global Navigation Satellite System ...
Frontiers

A prediction method for older adult care service demand combining improved RF algorithm and logistic regression

With the acceleration of global aging, the accurate prediction of care service demand for older adults is of significant importance for optimizing resource allocation. Traditional prediction methods ...
Scientific Research Publishing

Coulibaly, O. and Ouedraogo, A. (2016) Correlation of Global Solar Radiation of Eight Synoptic Stations in Burkina Faso Based on Linear and Multiple Linear Regression Methods ...

ABSTRACT: The solar data used to size installations for energy needs are most often oversized. The data used are either old or suffer from the effects of climate change or from data extrapolated to a ...