Search Results for author: Manel Martínez-Ramón

Found 17 papers, 4 papers with code

Review of Kernel Learning for Intra-Hour Solar Forecasting with Infrared Sky Images and Cloud Dynamic Feature Extraction

no code implementations11 Oct 2021 Guillermo Terrén-Serrano, Manel Martínez-Ramón

The uncertainty of the energy generated by photovoltaic systems incurs an additional cost for a guaranteed, reliable supply of energy (i. e., energy storage).

Probabilistic analysis of solar cell optical performance using Gaussian processes

no code implementations26 Jun 2021 Rahul Jaiswal, Manel Martínez-Ramón, Tito Busani

This work investigates application of different machine learning based prediction methodologies to estimate the performance of silicon based textured cells.

Gaussian Processes

Detection of Clouds in Multiple Wind Velocity Fields using Ground-based Infrared Sky Images

no code implementations7 May 2021 Guillermo Terrén-Serrano, Manel Martínez-Ramón

The optimal decision criterion to find the number of clusters in the mixture models is analyzed and compared between different Bayesian metrics and a sequential hidden Markov model.

Wind Flow Estimation in Thermal Sky Images for Sun Occlusion Prediction

no code implementations3 Mar 2021 Guillermo Terrén-Serrano, Manel Martínez-Ramón

Moving clouds affect the global solar irradiance that reaches the surface of the Earth.

Segmentation Algorithms for Ground-Based Infrared Cloud Images

1 code implementation19 Feb 2021 Guillermo Terrén-Serrano, Manel Martínez-Ramón

The increasing number of Photovoltaic (PV) systems connected to the power grid are vulnerable to the projection of shadows from moving clouds.

Girasol, a Sky Imaging and Global Solar Irradiance Dataset

no code implementations15 Feb 2021 Guillermo Terrén-Serrano, Adnan Bashir, Trilce Estrada, Manel Martínez-Ramón

The energy available in Micro Grid (MG) that is powered by solar energy is tightly related to the weather conditions in the moment of generation.

Explicit Basis Function Kernel Methods for Cloud Segmentation in Infrared Sky Images

1 code implementation12 Feb 2021 Guillermo Terrén-Serrano, Manel Martínez-Ramón

Photovoltaic systems are sensitive to cloud shadow projection, which needs to be forecasted to reduce the noise impacting the intra-hour forecast of global solar irradiance.

Cloud Detection

Processing of Global Solar Irradiance and Ground-Based Infrared Sky Images for Solar Nowcasting and Intra-Hour Forecasting Applications

no code implementations21 Jan 2021 Guillermo Terrén-Serrano, Manel Martínez-Ramón

We explain how to remove cyclostationary biases in global solar irradiance measurements.

Time Series Instrumentation and Methods for Astrophysics Image and Video Processing

Comparative Analysis of Methods for Cloud Segmentation in Ground-Based Infrared Images

1 code implementation13 Dec 2020 Guillermo Terrén-Serrano, Manel Martínez-Ramón

The performances of supervised and unsupervised learning methods in cloud segmentation are evaluated.

A conditional one-output likelihood formulation for multitask Gaussian processes

1 code implementation5 Jun 2020 Óscar García-Hinde, Vanessa Gómez-Verdejo, Manel Martínez-Ramón

At the same time, by extending this approach with both a hierarchical and an approximate model, the proposed extensions are capable of recovering the multitask covariance and noise matrices after learning only $2T$ parameters, avoiding the validation of any model hyperparameter and reducing the overall complexity of the model as well as the risk of overfitting.

Gaussian Processes

Application of Gaussian Process Regression to Koopman Mode Decomposition for Noisy Dynamic Data

no code implementations4 Nov 2019 Akitoshi Masuda, Yoshihiko Susuki, Manel Martínez-Ramón, Andrea Mammoli, Atsushi Ishigame

Koopman Mode Decomposition (KMD) is a technique of nonlinear time-series analysis that originates from point spectrum of the Koopman operator defined for an underlying nonlinear dynamical system.

Time Series Time Series Analysis

A Deep Learning Framework for Detection of Targets in Thermal Images to Improve Firefighting

no code implementations8 Oct 2019 Manish Bhattarai, Manel Martínez-Ramón

Intelligent detection and processing capabilities can be instrumental to improving the safety, efficiency, and successful completion of rescue missions conducted by firefighters in emergency first response settings.

Decision Making Real-Time Object Detection

Unsupervised Segmentation of Fire and Smoke from Infra-Red Videos

no code implementations18 Sep 2019 Meenu Ajith, Manel Martínez-Ramón

This paper proposes a vision-based fire and smoke segmentation system which use spatial, temporal and motion information to extract the desired regions from the video frames.

Optical Flow Estimation

Data Selection for Short Term load forecasting

no code implementations2 Sep 2019 Nestor Pereira, Miguel Angel Hombrados Herrera, Vanesssa Gómez-Verdejo, Andrea A. Mammoli, Manel Martínez-Ramón

Power load forecast with Machine Learning is a fairly mature application of artificial intelligence and it is indispensable in operation, control and planning.

Load Forecasting

A Unified SVM Framework for Signal Estimation

no code implementations21 Nov 2013 José Luis Rojo-Álvarez, Manel Martínez-Ramón, Jordi Muñoz-Marí, Gustavo Camps-Valls

On the one hand, the signal model equation is written in reproducing kernel Hilbert spaces (RKHS) using the well-known RKHS Signal Model formulation, and Mercer's kernels are readily used in SVM non-linear algorithms.

Time Series

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