Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

Objectives Delays in cancer diagnosis for patients with non-specific symptoms (NSSs) lead to poorer outcomes. Rapid ...

An ANN model offers the most accurate and reliable prediction of bubble-point pressure for Rmelan crude oils. For practical ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Abstract: Strength system optimization is a challenging trouble, because it entails a couple of objectives, constraints, records, and variables. Historically, linear regression fashions including ...

Objective To develop and validate a 10-year predictive model for cardiovascular and metabolic disease (CVMD) risk using ...

Abstract: Traditional multivariate statistical process monitoring algorithms focus on whether measurements are significantly shifted compared with the training data, but lack further analysis of the ...

This paper investigates the presence of nonlinear mechanisms of pass-through from the exchange rate to inflation in Brazil. In particular, it estimates a Phillips curve with a threshold for the ...

This project implements a quadratic nonlinear regression model to estimate the real-world distance between a hand and a camera based on the relative positions of hand landmarks in 2D images. The ...

Introduction: Chinese fir (Cunninghamia lanceolata) is a crucial afforestation and timber species in southern China. Accurate estimation of its stand biomass is vital for forest resource assessment, ...