Electricity load forecasting has been attracting research and industry attention because of its
importance for energy management, infrastructure planning, and budgeting. In recent years …

This research work presents a detailed survey about Computational Intelligence (CI) applied
to various Hotel and Travel Industry areas. Currently, the hospitality industry's interest in data …

Rapid expansion of smart metering technologies has enabled large-scale collection of
electricity consumption data and created the foundation for sensor-based load forecasting …

Smart Grid (SG) is a digitally enabled power grid with an automatic capability to control
electricity and information between utility and consumer. SG data streams are heterogenous …

The literature on machine learning in the context of data streams is vast and growing.
However, many of the defining assumptions regarding data-stream learning tasks are too …

Simultaneous and proportional estimation of human finger kinematics using muscle
interface has gained significant attention for human-robot interaction. Most existing …

Accurate short-term small-area meteorological forecasts are essential to ensure the safety of
operations and equipment operations in the Antarctic interior. This study proposes a deep …

This paper describes an exhaustive bibliographic review, which searches for and analyzes
the latest trends in the use of techniques and algorithms of a Data Mining (DM) process …

This paper tackles the challenge of concept drift (CD), where data patterns evolve over time,
hindering the accuracy of traditional forecasting models in smart grids. The study proposes a …

Electricity load forecasting has been attracting increasing attention because of its
importance for energy management, infrastructure planning, and budgeting. In recent years …