Building energy consumption modeling and forecasting is essential to address buildings
energy efficiency problems and take up current challenges of human comfort, urbanization …

This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …

This paper provides an extensive review of learning-based short-term forecasting models for
smart grid applications. In addition to this, the paper also explores forecasting models …

Abstract In a future Smart Grid context, increasing challenges in managing the stochastic
local energy supply and demand are expected. This increased the need of more accurate …

In this paper, a novel successive approximation framework, named hybrid iteration (HI), is
proposed to fill up the performance gap between two well-known dynamic programming …

Dialogue policy is a crucial component in task-oriented Spoken Dialogue Systems (SDSs).
As a decision function, it takes the current dialogue state as input and generates appropriate …

This paper proposes a combined Virtual Reference Feedback Tuning–Q-learning model-
free control approach, which tunes nonlinear static state feedback controllers to achieve …

This brief proposes a novel solution to problems related to the measurement feedback
adaptive optimal output regulation of discrete-time linear systems with input time-delay …

In this paper, we develop an intelligent overtaking decision-making method for highway
autonomous driving. The key idea is to use reinforcement learning algorithms to learn an …

Different drivers are nowadays leading spacecraft toward an increased level of on-board
autonomy. In this paper, we survey model-based techniques as a vehicle to implement …