91
TÍTULO: MARTINE: Multi-Agent based Real-Time INfrastructure for Energy PDF
AUTORES: Tiago Pinto ; Luis Gomes; Pedro Faria; Filipe Sousa; Zita A Vale;
PUBLICAÇÃO: 2020, FONTE: Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, AAMAS '20, Auckland, New Zealand, May 9-13, 2020
INDEXADO EM: DBLP
92
TÍTULO: Solar Thermal Collector Output Temperature Prediction by Hybrid Intelligent Model for Smartgrid and Smartbuildings Applications and Optimization  Full Text
AUTORES: José-Luis Casteleiro-Roca; Pablo Chamoso; Esteban Jove; Alfonso González-Briones; Héctor Quintián; María-Isabel Fernández-Ibáñez; Rafael Alejandro Vega Vega; Andrés-José Piñón Pazos; José Antonio López Vázquez; Santiago Torres-Álvarez; Tiago Pinto ; Jose Luis Calvo-Rolle;
PUBLICAÇÃO: 2020, FONTE: Applied Sciences, VOLUME: 10, NÚMERO: 13
INDEXADO EM: CrossRef: 7
93
TÍTULO: Trust Model for a Multi-agent Based Simulation of Local Energy Markets
AUTORES: Rui Andrade; Tiago Pinto ; Isabel Praça;
PUBLICAÇÃO: 2020, FONTE: Highlights in Practical Applications of Agents, Multi-Agent Systems, and Trust-worthiness. The PAAMS Collection - International Workshops of PAAMS 2020, L'Aquila, Italy, October 7-9, 2020, Proceedings, VOLUME: 1233
INDEXADO EM: DBLP
94
TÍTULO: Trust model for a multi-agent based simulation of local energy markets
AUTORES: Andrade, R; Pinto, T ; Praça, I;
PUBLICAÇÃO: 2020, FONTE: 18th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2020 in Communications in Computer and Information Science, VOLUME: 1233 CCIS
INDEXADO EM: Scopus CrossRef: 2
95
TÍTULO: y Adjacent Markets Influence Over Electricity Trading-Iberian Benchmark Study  Full Text
AUTORES: Morais, H; Pinto, T ; Vale, Z;
PUBLICAÇÃO: 2020, FONTE: ENERGIES, VOLUME: 13, NÚMERO: 11
INDEXADO EM: Scopus WOS CrossRef: 3
96
TÍTULO: A Local Electricity Market Model for DSO Flexibility Trading
AUTORES: Faia, R; Pinto, T ; Vale, Z; Corchado, JM;
PUBLICAÇÃO: 2019, FONTE: 16th International Conference on the European Energy Market, EEM 2019 in International Conference on the European Energy Market, EEM, VOLUME: 2019-September
INDEXADO EM: Scopus CrossRef: 12
98
TÍTULO: A Review of the main machine learning methods for predicting residential energy consumption
AUTORES: Gonzalez Briones, A; Hernandez, G; Pinto, T ; Vale, Z; Corchado, JM;
PUBLICAÇÃO: 2019, FONTE: 16th International Conference on the European Energy Market, EEM 2019 in International Conference on the European Energy Market, EEM, VOLUME: 2019-September
INDEXADO EM: Scopus
99
TÍTULO: A Review of the Main Machine Learning Methods for Predicting Residential Energy Consumption
AUTORES: Alfonso Gonzalez-Briones; Guillermo Hernandez; Tiago Pinto ; Zita Vale; Juan M Corchado;
PUBLICAÇÃO: 2019, FONTE: 2019 16th International Conference on the European Energy Market (EEM)
INDEXADO EM: CrossRef: 10
100
TÍTULO: Adaptive entropy-based learning with dynamic artificial neural network
AUTORES: Pinto, T ; Morais, H; Corchado, JM;
PUBLICAÇÃO: 2019, FONTE: NEUROCOMPUTING, VOLUME: 338
INDEXADO EM: Scopus WOS CrossRef: 7
NO MEU: ORCID
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