David Casillas-Pérez

Assistant professor

Universidad Rey Juan Carlos - Campus de Fuenlabrada

Spain

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David Casillas-Pérez is an Assistant Professor at Universidad Rey Juan Carlos - Campus de Fuenlabrada in Spain. His research areas include electricity price prediction, deep learning hybrid models, and forecasting electricity demand using advanced neural network techniques. Recent publications highlight his work on predictive models for electricity pricing and environmental data, showcasing innovative approaches such as convolutional neural networks and temporal convolution models.

David Casillas-Pérez

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Articles (23)

Novel deep hybrid model for electricity price prediction based on dual decomposition

Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach

Explainable deep learning hybrid modeling framework for total suspended particles concentrations prediction

Electricity demand uncertainty modeling with Temporal Convolution Neural Network models

Generating High Spatial and Temporal Surface Albedo with Multispectral-Wavemix and Temporal-Shift Heatmaps

Very short-term solar ultraviolet-A radiation forecasting system with cloud cover images and a Bayesian optimized interpretable artificial intelligence model

Point-based and probabilistic electricity demand prediction with a Neural Facebook Prophet and Kernel Density Estimation model

Probabilistic-based electricity demand forecasting with hybrid convolutional neural network-extreme learning machine model

Half-hourly electricity price prediction with a hybrid convolution neural network-random vector functional link deep learning approach

Wavelet-fusion image super-resolution model with deep learning for downscaling remotely-sensed, multi-band spectral albedo imagery

Short-term wind speed forecasting using an optimized three-phase convolutional neural network fused with bidirectional long short-term memory network model

A multi-algorithm approach for operational human resources workload balancing in a last mile urban delivery system

Electricity demand error corrections with attention bi-directional neural networks

Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting

Cloud cover bias correction in numerical weather models for solar energy monitoring and forecasting systems with kernel ridge regression

Inertial Sensors for Human Motion Analysis: A Comprehensive Review

Enhanced joint hybrid deep neural network explainable artificial intelligence model for 1-hr ahead solar ultraviolet index prediction

A novel approach based on integration of convolutional neural networks and echo state network for daily electricity demand prediction

Collaboration and competition spatial complex networks in regional science

Hybrid Convolutional Neural Network-Multilayer Perceptron Model for Solar Radiation Prediction

A Flexible Architecture Using Temporal, Spatial and Semantic Correlation-Based Algorithms for Story Segmentation of Broadcast News

Downscaling Surface Albedo to Higher Spatial Resolutions With an Image Super-Resolution Approach and PROBA-V Satellite Images

Deep Shape-from-Template: Single-image quasi-isometric deformable registration and reconstruction

Collaborators (9)

Sancho Salcedo-Sanz

Thong Nguyen-Huy

Seyyed Ali Pourmousavi Kani

J. Antonio Portilla-Figueras

Juan Jesús García Domínguez

Toan Dinh

Ravinesh Deo

Ana Jiménez Martín

Sara García de Villa

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