The goal of ensemble regression is to combine several models in order to improve the
prediction accuracy in learning problems with a numerical target variable. The process of …

Previously, many researchers have performed analysis of various techniques for the
software fault prediction (SFP). Oddly, the majority of such studies have shown the limited …

An effective software fault prediction (SFP) model could help developers in the quick and
prompt detection of faults and thus help enhance the overall reliability and quality of the …

Time series forecasting has been applied to predict performance degradation in
Microservice-Based Applications (MBAs). The prediction enables MBA adaptation to avoid …

Determining the most appropriate learning technique (s) is vital for the accurate and effective
software fault prediction (SFP). Earlier techniques used for SFP have reported varying …

This paper is about long-term travel time prediction in public transportation. However, it can
be useful for a wider area of applications. It follows a heterogeneous ensemble approach …

We propose a procedure for the interpretation of horizons in seismic reflection data based
on a Neural Network (NN) approach, which can be at the same time fast, accurate and able …

The development of accurate forecasting systems for real-world time series modeling is a
challenging task. Due to the presence of temporal patterns that change over time, the …

Abstract Dynamic Regressor Selection (DRS) techniques aim to select the most competent
regressors from an ensemble per test pattern. So, for each test pattern, only a subset of the …

The transmission line is one of the most crucial electric power system components,
demanding special attention since they are subject to failures that can cause disruptions in …