A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

Sensitivity analysis helps predict outcomes by varying key variables in financial models. It simplifies complex models, aids in understanding variable effects, and reduces uncertainty. This analysis ...

1 School of Urban Construction, Yangtze University, Jingzhou, China. 2 Aeronautics Department, Nanchang Hangkong University, Nanchang, Jiangxi. This research investigates the problem of performing ...

Sentiment analysis, i.e., determining the emotional tone of a text, has become a crucial tool for researchers, developers, and businesses to comprehend social media trends, consumer feedback, and ...

Investors choose funds in the hopes that they align with their risk preferences and long-term goals. If funds drift from their stated intentions, investors could end up lost at sea. Funds need to ...

Abstract: Sensitivity is one of the most important properties of a microphone. The commonly used methods to analyze microphone sensitivity include lumped parameter method (LPM) and finite element ...

ABSTRACT: This work presents the “nth-Order Feature Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (abbreviated as “nth-FASAM-N”), which will be shown to be the most efficient ...

This README document provides an overview of the code and its functionalities for conducting financial analysis related to a company's income statement, profitability ratios, break-even analysis, ...