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Francisco Silva 0001
Person information
- affiliation: Politechnic of Porto, ISEP/IPP, GECAD, Knowledge Engineering and Decision Support Research Center, Institute of Engineering, Portugal
Other persons with the same name
- Francisco Silva — disambiguation page
- Francisco Silva 0002
— University of Porto, INESC TEC, Institute for Systems and Computer Engineering, Technology and Science, Portugal (and 1 more)
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2010 – 2019
- 2019
- [c13]Francisco Silva, Tiago Pinto, Zita A. Vale:
Decision Support System for Opponents Selection in Electricity Markets Bilateral Negotiations. AAMAS 2019: 2384-2386 - [c12]Francisco Silva, Tiago Pinto
Identifying Most Probable Negotiation Scenario in Bilateral Contracts with Reinforcement Learning. WorldCIST (1) 2019: 556-571 - 2018
- [j1]Francisco Silva, Gabriel Santos
A context-based building security alarm through power and sensors analysis. Energy Inform. 1(S1) (2018) - [c11]Francisco Silva, Ricardo Faia
Optimizing Opponents Selection in Bilateral Contracts Negotiation with Particle Swarm. PAAMS (Workshops) 2018: 116-124 - [c10]Jaime Rodriguez-Fernandez, Tiago Pinto
Reputation Computational Model to Support Electricity Market Players Energy Contracts Negotiation. PAAMS (Workshops) 2018: 125-133 - [c9]Brigida Teixeira
Demonstration of Tools Control Center for Multi-agent Energy Systems Simulation. PAAMS 2018: 353-356 - 2017
- [c8]Francisco Silva
Decision Support System for the Negotiation of Bilateral Contracts in Electricity Markets. ISAmI 2017: 159-166 - [c7]Francisco Silva
Decision Support System for the Negotiation of Bilateral Contracts in Electricity Markets. PAAMS (Special Sessions) 2017: 305-306 - [c6]Jaime Rodriguez-Fernandez, Tiago Pinto
Bilateral contract prices estimation using a Q-leaming based approach. SSCI 2017: 1-6 - 2016
- [c5]Francisco Silva
Application of a Hybrid Neural Fuzzy Inference System to Forecast Solar Intensity. DEXA Workshops 2016: 161-165 - [c4]Aria Jozi
Wang and Mendel's fuzzy rule learning method for energy consumption forecasting considering the influence of environmental temperature. GIIS 2016: 1-6 - [c3]Aria Jozi
Energy consumption forecasting based on Hybrid Neural Fuzzy Inference System. SSCI 2016: 1-5 - 2015
- [c2]Francisco Silva
Demonstration of Realistic Multi-agent Scenario Generator for Electricity Markets Simulation. PAAMS 2015: 316-319 - 2014
- [c1]Brigida Teixeira
Data mining approach to support the generation of Realistic Scenarios for multi-agent simulation of electricity markets. IEEE IA 2014: 8-15
Coauthor Index
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