A research team has developed a new hybrid artificial intelligence framework that can accurately estimate leaf nitrogen content without relying on labor-intensive field measurements.

This study aims to develop a comprehensive parametric model for quantifying and predicting political conflicts through mathematical analysis. It addresses the need for objective tools to assess the ...

Abstract: The polarimetric synthetic aperture radar tomography (TomoSAR) technique has proven to be a highly promising cutting-edge microwave remote sensing technique for obtaining forest vertical ...

The terms Agile and estimations don't align perfectly. Agile is all about responding to change rather than following a plan, while accurate estimations require a fixed plan that doesn't change. It's a ...

ABSTRACT: Singh, Gewali, and Khatiwada proposed a skewness measure for probability distributions called Area Skewness (AS), which has desirable properties but has not been widely applied in practice.

Linear multiplicative models are popular tools for analyzing data with positive responses. However, the linear structure of models is too restrictive on the regression relation, which may lead to a ...

Abstract: The reliability of satellites determines the service capability of the system. In this paper, a non-parametric estimation method is used to analyze the in-orbit reliability of satellites.

Introduction: Machine learning (ML) methods are promising and scalable alternatives for propensity score (PS) estimation, but their comparative performance in disease risk score (DRS) estimation ...