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Tiago Alessandro Espínola Ferreira
Person information
- affiliation: Universidade Federal Rural de Pernambuco, Recife, Brazil
Other persons with the same name
- Tiago Ferreira 0001
— University College London, UK
- Tiago Ferreira 0002 — Universidad Alberto Hurtado, Santiago, Chile
- Tiago Ferreira 0003 — INESC-ID, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
- Tiago Ferreira 0004 — Polytechnic of Porto, School of Engineering, Porto, Portugal
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2020 – today
- 2023
- [j16]Jonathan H. A. de Carvalho, Luciano S. de Souza, Fernando M. de Paula Neto
On applying the lackadaisical quantum walk algorithm to search for multiple solutions on grids. Inf. Sci. 622: 873-888 (2023) - [i5]Henrique Correia Torres Santos, Luciano S. de Souza, Jonathan H. A. de Carvalho, Tiago A. E. Ferreira:
PESC - Parallel Experiment for Sequential Code. CoRR abs/2301.05770 (2023) - 2022
- [j15]Ademir Batista Santos Neto
Support decision system based on invoices data mining to estimate commercial pent-up demands. Expert Syst. Appl. 202: 117204 (2022) - [j14]Gerson R. Santos
Gravitational wave signal recognition and ring-down time estimation via Artificial Neural Networks. Expert Syst. Appl. 207: 117931 (2022) - [j13]Luciano Souza, Wilson Rosa de Oliveira
Sec-G Class of Distributions: Properties and Applications. Symmetry 14(2): 299 (2022) - [j12]Luciano S. de Souza
Classical Artificial Neural Network Training Using Quantum Walks as a Search Procedure. IEEE Trans. Computers 71(2): 378-389 (2022) - [c31]João Henrique De Medeiros Delgado, Tiago A. E. Ferreira:
Autoencoder performance analysis with adaptive and trainable activation function to compress images. LA-CCI 2022: 1-6 - 2021
- [c30]Luciano S. de Souza
Lackadaisical Quantum Walk in the Hypercube to Search for Multiple Marked Vertices. BRACIS (1) 2021: 249-263 - [i4]Tiago A. E. Ferreira, Marios Mattheakis, Pavlos Protopapas:
A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function. CoRR abs/2101.06100 (2021) - [i3]Jonathan H. A. de Carvalho, Luciano S. de Souza, Fernando M. de Paula Neto, Tiago A. E. Ferreira:
On Applying the Lackadaisical Quantum Walk Algorithm to Search for Multiple Solutions on Grids. CoRR abs/2106.06274 (2021) - 2020
- [j11]Rosilda B. de Sousa, Emeson J. S. Pereira, Marina P. Cipolletti, Tiago A. E. Ferreira
A proposal of quantum data representation to improve the discrimination power. Nat. Comput. 19(3): 577-591 (2020) - [j10]Ademir Batista Santos Neto, Tiago Alessandro Espínola Ferreira, Maria da Conceição Moraes Batista, Paulo Renato A. Firmino
Studying the Performance of Cognitive Models in Time Series Forecasting. RITA 27(1): 83-91 (2020) - [c29]Jonathan H. A. de Carvalho
Impacts of Multiple Solutions on the Lackadaisical Quantum Walk Search Algorithm. BRACIS 2020: 122-135 - [i2]Juan C. Rodriguez Gamboa, Eva Susana Albarracin E., Adenilton J. da Silva, Luciana Leite, Tiago A. E. Ferreira:
Wine quality rapid detection using a compact electronic nose system: application focused on spoilage thresholds by acetic acid. CoRR abs/2001.06323 (2020) - [i1]Gerson R. Santos
Gravitational Wave Detection and Information Extraction via Neural Networks. CoRR abs/2003.09995 (2020)
2010 – 2019
- 2019
- [c28]Luciano Souza, Jonathan H. A. de Carvalho, Tiago Ferreira:
Quantum Walk to Train a Classical Artificial Neural Network. BRACIS 2019: 836-841 - 2018
- [c27]Ricardo T. A. de Oliveira, Thaize Fernandes O. de Assis, Paulo Renato A. Firmino
Aggregation of Time Series Forecasts via Cacoullos Copula. IJCNN 2018: 1-7 - 2017
- [j9]Ricardo T. A. de Oliveira, Thaize Fernandes O. de Assis, Paulo Renato A. Firmino
Copulas-based time series combined forecasters. Inf. Sci. 376: 110-124 (2017) - [j8]Paulo S. G. de Mattos Neto
A perturbative approach for enhancing the performance of time series forecasting. Neural Networks 88: 114-124 (2017) - [c26]Ademir Batista Santos Neto, Maria da Conceição Moraes Batista, Paulo Renato A. Firmino, Tiago A. E. Ferreira:
Utilização de Modelos Cognitivos na Previsão de Séries Temporais. SBSI 2017: 88-95 - 2016
- [c25]Paulo S. G. de Mattos Neto
Applying a general hybrid intelligent system for ultra-high-frequency stock market forecasting. IJCNN 2016: 2104-2109 - [c24]Ricardo T. A. de Oliveira, Thaize Fernandes O. de Assis, Paulo Renato A. Firmino
Copulas-based ensemble of Artificial Neural Networks for forecasting real world time series. IJCNN 2016: 4089-4096 - 2015
- [j7]Paulo Renato A. Firmino
Error modeling approach to improve time series forecasters. Neurocomputing 153: 242-254 (2015) - 2014
- [j6]Paulo S. G. de Mattos Neto
Hybrid intelligent system for air quality forecasting using phase adjustment. Eng. Appl. Artif. Intell. 32: 185-191 (2014) - [j5]David Augusto Silva, Gabriela I. L. Alves, Paulo S. G. de Mattos Neto
Measurement of Fitness Function efficiency using Data Envelopment Analysis. Expert Syst. Appl. 41(16): 7147-7160 (2014) - [j4]Paulo Renato A. Firmino
Correcting and combining time series forecasters. Neural Networks 50: 1-11 (2014) - 2013
- [j3]Ricardo de A. Araújo, Tiago A. E. Ferreira
A Morphological-Rank-Linear evolutionary method for stock market prediction. Inf. Sci. 237: 3-17 (2013) - 2012
- [c23]Erinaldo L. Siqueira Júnior, Tiago A. E. Ferreira
Discovering the Rules of a Elementary One-Dimensional Automaton. IDEAL 2012: 312-319 - [c22]Henrique Correia Torres Santos
A System Based on Swarm Particle Optimization to Extract Knowledge from Times Series Data. SBRN 2012: 244-249 - 2011
- [c21]Paulo S. G. de Mattos Neto
A simulation environment for volatility analysis of developed and in development markets. IJCNN 2011: 2450-2456 - 2010
- [c20]Aranildo Rodrigues Lima Junior, David Augusto Silva, Paulo Salgado Gomes de Mattos Neto, Tiago A. E. Ferreira
An experimental study of fitness function and time series forecasting using artificial neural networks. GECCO (Companion) 2010: 2015-2018 - [c19]Paulo S. G. de Mattos Neto
An intelligent perturbative approach for the time series forecasting problem. IJCNN 2010: 1-8
2000 – 2009
- 2009
- [j2]Ricardo de A. Araújo, Tiago A. E. Ferreira
An intelligent hybrid morphological-rank-linear method for financial time series prediction. Neurocomputing 72(10-12): 2507-2524 (2009) - [c18]Paulo S. G. de Mattos Neto, Aranildo Rodrigues Lima Junior, Tiago A. E. Ferreira
Time series forecasting using a perturbative intelligent system. GECCO 2009: 1477-1478 - [c17]Paulo S. G. de Mattos Neto, Gustavo G. Petry, Aranildo Rodrigues Lima Junior, Tiago A. E. Ferreira
Combining Artificial Neural Network and Particle Swarm System for time series forecasting. IJCNN 2009: 2230-2237 - [c16]L. J. Aranildo Rodrigues, Paulo S. G. de Mattos Neto
A prime step in the time series forecasting with hybrid methods: The fitness function choice. IJCNN 2009: 2703-2710 - 2008
- [j1]Tiago A. E. Ferreira
A New Intelligent System Methodology for Time Series Forecasting with Artificial Neural Networks. Neural Process. Lett. 28(2): 113-129 (2008) - [c15]Carlos R. B. Azevedo, Tiago A. E. Ferreira
Improving Image Vector Quantization with a Genetic Accelerated K-Means Algorithm. ACIVS 2008: 67-76 - [c14]Ricardo de A. Araújo, Aranildo Rodrigues Lima Junior, Tiago Alessandro Espínola Ferreira
Morphological-Rank-Linear Time-lag Added Evolutionary Forecasting method for financial time series forecasting. IEEE Congress on Evolutionary Computation 2008: 1340-1347 - [c13]Ricardo de A. Araújo, Aranildo Rodrigues Lima Junior, Tiago Alessandro Espínola Ferreira
A Quantum-Inspired Intelligent Hybrid method for stock market forecasting. IEEE Congress on Evolutionary Computation 2008: 1348-1355 - [c12]Aranildo Rodrigues Lima Junior, Tiago Alessandro Espínola Ferreira
An experimental study with a Hybrid method for tuning neural network for time series prediction. IEEE Congress on Evolutionary Computation 2008: 3435-3442 - [c11]Aranildo Rodrigues Lima Junior, Tiago Alessandro Espínola Ferreira:
A hybrid method for tuning neural network for time series forecasting. GECCO 2008: 531-532 - [c10]Carlos R. B. Azevedo, Esdras L. Bispo Jr.
An Evolutionary Approach for Vector Quantization Codebook Optimization. ISNN (1) 2008: 452-461 - 2007
- [c9]Ricardo de A. Araújo, Germano C. Vasconcelos
An evolutionary Morphological-Rank-Linear approach for time series prediction. IEEE Congress on Evolutionary Computation 2007: 4321-4328 - [c8]Ricardo de A. Araújo, Germano C. Vasconcelos
Hybrid differential evolutionary system for financial time series forecasting. IEEE Congress on Evolutionary Computation 2007: 4329-4336 - [c7]Tiago A. E. Ferreira
A New Evolutionary Approach for Time Series Forecasting. CIDM 2007: 616-623 - [c6]Ricardo de A. Araújo, Robson P. de Sousa, Tiago A. E. Ferreira
An Intelligent Hybrid Approach for Designing Increasing Translation Invariant Morphological Operators for Time Series Forecasting. ISNN (2) 2007: 602-611 - 2006
- [c5]Ricardo de A. Araújo, Francisco Madeiro, Robson Pequeno de Sousa, Lúcio Flavio Cavalcanti Pessoa, Tiago Alessandro Espínola Ferreira
An Evolutionary Morphological Approach for Financial Time Series Forecasting. IEEE Congress on Evolutionary Computation 2006: 2467-2474 - [c4]Ricardo de A. Araújo, Francisco Madeiro
Improved Evolutionary Hybrid Method for Designing Morphological Operators. ICIP 2006: 2417-2420 - [c3]Ricardo de A. Araújo, Robson P. de Sousa, Tiago A. E. Ferreira
Designing Translation Invariant Operators for Financial Time Series Forecasting. SBRN 2006: 30-35 - 2005
- [c2]Tiago A. E. Ferreira
A new evolutionary method for time series forecasting. GECCO 2005: 2221-2222 - 2004
- [c1]Tiago A. E. Ferreira, Germano C. Vasconcelos, Paulo J. L. Adeodato:
A hybrid intelligent system approach for improving the prediction of real world time series. IEEE Congress on Evolutionary Computation 2004: 736-743
Coauthor Index
aka: Paulo Salgado Gomes de Mattos Neto
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