A Secure Federated Deep Learning-Based Approach for Heating Load Demand Forecasting in Building Environment

Moradzadeh, A.; Moayyed, H.; Mohammadi Ivatloo, B.; Aguiar, AP. ; Anvari Moghaddam, A.  IEEE Acces ID Authenticus: P-00V-ZNM DOI: 10.1109/access.2021.3139529 Abstract (EN): Recently, with the establishment of new thermal regulations, the energy efficiency of buildings has increased significantly, and various deep learning-based methods have been presented to accurately forecast the heating load demand of buildings. However, all of […]

Adaptive Sampling Using an Unsupervised Learning of GMMs Applied to a Fleet of AUVs with CTD Measurements

Khoshrou, A; Aguiar, AP; Fernando Lobo Pereira ROBOT 2015: SECOND IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 1  ID Authenticus: P-00K-2BZ DOI: 10.1007/978-3-319-27146-0_25 Abstract: This paper addresses the problem of real-time adaptive sampling using a coordinated fleet of Autonomous Underwater Vehicles (AUVs). The system setup consists of one leader AUV and one or more follower AUVs, all equipped […]

Real-Time Outlier Detection Applied to a Doppler Velocity Log Sensor Based on Hybrid Autoencoder and Recurrent Neural Network

Davari, N; Aguiar, AP IEEE JOURNAL OF OCEANIC ENGINEERING ID Authenticus: P-00T-QWZ DOI: 10.1109/joe.2021.3057909 Abstract: This article presents a real-time outlier detection deep-learning (OD-DL)-based method using a hybridized artificial neural network (ANN) approach. We propose an unsupervised ANN scheme that runs in parallel, a denoising autoencoder (DAE) and a recurrent neural network (RNN). The DAE aims to reconstruct […]

Deep Learning-Assisted Short-Term Load Forecasting Forsustainable Management of Energy in Microgrid

Arash Moradzadeh; Hamed Moayyed; Sahar Zakeri; Behnam Mohammadi-Ivatloo; António Pedro Aguiar MDPI Inventions ID Authenticus: P-00T-D3G DOI: 10.3390/inventions6010015 Abstract (EN): Nowadays, supplying demand load and maintaining sustainable energy are important issues that have created many challenges in power systems. In these types of problems, short-term load forecasting has been proposed as one of the management and energy supply […]