131
TITLE: Fair Remuneration of Energy Consumption Flexibility Using Shapley Value
AUTHORS: Faia, Ricardo; Pinto, Tiago ; Vale, Zita;
PUBLISHED: 2019, SOURCE: 19th EPIA Conference on Artificial Intelligence (EPIA) in PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2019, PT I, VOLUME: 11804
INDEXED IN: Scopus WOS CrossRef: 4
132
TITLE: Genetic Algorithms for Portfolio Optimization with Weighted Sum Approach
AUTHORS: Faia, R; Pinto, T ; Vale, Z; Corchado, JM; Soares, J; Lezama, F;
PUBLISHED: 2019, SOURCE: 8th IEEE Symposium Series on Computational Intelligence, SSCI 2018 in Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018
INDEXED IN: Scopus CrossRef: 6
133
TITLE: Genetic fuzzy rule-based system using MOGUL learning methodology for energy consumption forecasting
AUTHORS: Jozi, A; Pinto, T ; Praca, I; Silva, F; Teixeira, B; Vale, Z;
PUBLISHED: 2019, SOURCE: ADCAIJ-ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL, VOLUME: 8, ISSUE: 1
INDEXED IN: Scopus WOS CrossRef
134
TITLE: Hybrid approach based on particle swarm optimization for electricity markets participation
AUTHORS: Ricardo Faia; Tiago Pinto ; Zita Vale; Juan Manuel Corchado;
PUBLISHED: 2019, SOURCE: Energy Informatics, VOLUME: 2, ISSUE: 1
INDEXED IN: Scopus CrossRef: 13 Handle
IN MY: ORCID
135
TITLE: Hybrid approach based on particle swarm optimization for electricity markets participation
AUTHORS: Ricardo Faia; Tiago Pinto ; Zita A Vale; Juan Manuel Corchado;
PUBLISHED: 2019, SOURCE: Energy Inform., VOLUME: 2, ISSUE: 1
INDEXED IN: DBLP
IN MY: ORCID | DBLP
136
TITLE: Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning
AUTHORS: Francisco Silva; Tiago Pinto ; Isabel Praça; Zita A Vale;
PUBLISHED: 2019, SOURCE: New Knowledge in Information Systems and Technologies - Volume 1, World Conference on Information Systems and Technologies, WorldCIST 2019, Galicia, Spain, 16-19 April, 2019, VOLUME: 930
INDEXED IN: DBLP
IN MY: ORCID | DBLP
137
TITLE: Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning
AUTHORS: Silva, F; Pinto, T ; Praça, I; Vale, Z;
PUBLISHED: 2019, SOURCE: World Conference on Information Systems and Technologies, WorldCIST 2019 in NEW KNOWLEDGE IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 1, VOLUME: 930
INDEXED IN: Scopus WOS CrossRef
IN MY: ORCID
138
TITLE: Local Energy Markets: Paving the Path Toward Fully Transactive Energy Systems
AUTHORS: Lezama, F; Soares, J; Hernandez Leal, P; Kaisers, M; Pinto, T ; Vale, Z;
PUBLISHED: 2019, SOURCE: IEEE TRANSACTIONS ON POWER SYSTEMS, VOLUME: 34, ISSUE: 5
INDEXED IN: Scopus WOS CrossRef: 218
139
TITLE: Multi-agent Systems Society for Power and Energy Systems Simulation
AUTHORS: Santos, Gabriel; Pinto, Tiago ; Vale, Zita;
PUBLISHED: 2019, SOURCE: 19th International Workshop on Multi-Agent-Based Simulation (MABS) in MULTI-AGENT-BASED SIMULATION XIX, VOLUME: 11463
INDEXED IN: Scopus WOS CrossRef: 1
140
TITLE: Multi-Agent-Based CBR Recommender System for Intelligent Energy Management in Buildings
AUTHORS: Pinto, T ; Faia, R; Navarro Caceres, M; Santos, G; Corchado, JM; Vale, Z;
PUBLISHED: 2019, SOURCE: IEEE SYSTEMS JOURNAL, VOLUME: 13, ISSUE: 1
INDEXED IN: Scopus WOS DBLP CrossRef: 32
Page 14 of 37. Total results: 369.