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Douglas Mota Dias
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2020 – today
- 2024
- [c37]Allan de Lima
, Samuel Carvalho
Fuzzy Pattern Trees for Classification Problems Using Genetic Programming. EuroGP 2024: 3-20 - [c36]Darian Reyes Fernández de Bulnes
Feature Encapsulation by Stages Using Grammatical Evolution. GECCO Companion 2024: 531-534 - [c35]Edicson Santiago Bonilla Diaz, Enrique Naredo, Nicolas Francisco Mateo Díaz, Douglas Mota Dias, Maria Alejandra Bonilla Diaz, Susan Harnett, Conor Ryan:
Neural Architecture Search for Bearing Fault Classification. ICAART (2) 2024: 288-300 - 2023
- [j12]Michael Kwaku Tetteh
Evolving Multi-Output Digital Circuits Using Multi-Genome Grammatical Evolution. Algorithms 16(8): 365 (2023) - [c34]Bilal Majeed
Performance Upgrade of Sequence Detector Evolution Using Grammatical Evolution and Lexicase Parent Selection Method. CCE 2023: 90-103 - [c33]Allan de Lima
Leap Mapping: Improving Grammatical Evolution for Modularity Problems. GECCO Companion 2023: 555-558 - [c32]Aidan Murphy
Error and Correlation as fitness functions for Scaled Symbolic Regression in Grammatical Evolution. GECCO Companion 2023: 607-610 - [c31]Cristiane Salgado Pereira
A Multi-Objective Decomposition Optimization Method for Refinery Crude Oil Scheduling through Genetic Programming. GECCO Companion 2023: 1972-1980 - [c30]Bilal Majeed
Evolving Behavioural Level Sequence Detectors in SystemVerilog Using Grammatical Evolution. ICAART (3) 2023: 475-483 - [c29]Allan de Lima, Samuel Carvalho, Douglas Mota Dias, Joseph P. Sullivan, Conor Ryan:
On Switching Selection Methods to Increase Parsimony Pressure. IJCCI 2023: 96-107 - [c28]Krishn Kumar Gupt, Meghana Kshirsagar, Douglas Mota Dias, Joseph P. Sullivan, Conor Ryan:
Adaptive Case Selection for Symbolic Regression in Grammatical Evolution. IJCCI 2023: 195-205 - [i1]Krishn Kumar Gupt, Meghana Kshirsagar, Douglas Mota Dias, Joseph P. Sullivan, Conor Ryan:
A Novel ML-driven Test Case Selection Approach for Enhancing the Performance of Grammatical Evolution. CoRR abs/2312.14321 (2023) - 2022
- [j11]Aidan Murphy
Human in the Loop Fuzzy Pattern Tree Evolution. SN Comput. Sci. 3(2): 163 (2022) - [j10]Michael Kwaku Tetteh
Grammatical Evolution of Complex Digital Circuits in SystemVerilog. SN Comput. Sci. 3(3): 188 (2022) - [j9]Aidan Murphy
Fuzzy Pattern Tree Evolution Using Grammatical Evolution. SN Comput. Sci. 3(6): 426 (2022) - [c27]Krishn Kumar Gupt
PreDive: preserving diversity in test cases for evolving digital circuits using grammatical evolution. GECCO Companion 2022: 719-722 - [c26]Allan de Lima
Lexi2: lexicase selection with lexicographic parsimony pressure. GECCO 2022: 929-937 - [c25]Senthil Murugan, Enrique Naredo, Douglas Mota Dias, Conor Ryan, Flaviano Godínez-Jaimes
A Hierarchical Probabilistic Divergent Search Applied to a Binary Classification. ICAART (2) 2022: 345-353 - 2021
- [j8]Mayk C. Ramos, Patrick K. Quoika
pyPolyBuilder: Automated Preparation of Molecular Topologies and Initial Configurations for Molecular Dynamics Simulations of Arbitrary Supramolecules. J. Chem. Inf. Model. 61(4): 1539-1544 (2021) - [c24]Aidan Murphy
Towards Incorporating Human Knowledge in Fuzzy Pattern Tree Evolution. EuroGP 2021: 66-81 - [c23]Michael Kwaku Tetteh
Evolution of Complex Combinational Logic Circuits Using Grammatical Evolution with SystemVerilog. EuroGP 2021: 146-161 - [c22]Samuel Carvalho, Joe Sullivan
Using grammatical evolution for modelling energy consumption on a computer numerical control machine. GECCO Companion 2021: 1557-1563 - [c21]Yassir Houreh, Mahsa Mahdinejad, Enrique Naredo, Douglas Mota Dias, Conor Ryan:
HNAS: Hyper Neural Architecture Search for Image Segmentation. ICAART (2) 2021: 246-256 - [c20]Vijay Sambhe, Shanmukha Rajesh, Enrique Naredo, Douglas Mota Dias, Meghana Kshirsagar, Conor Ryan:
Multi-objective Classification and Feature Selection of Covid-19 Proteins Sequences using NSGA-II and MAP-Elites. ICAART (2) 2021: 1241-1248 - 2020
- [j7]Rogerio C. B. L. Povoa
Unimodal optimization using a genetic-programming-based method with periodic boundary conditions. Genet. Program. Evolvable Mach. 21(3): 503-523 (2020) - [j6]Cristiane Salgado Pereira
Quantum-Inspired Genetic Programming Algorithm for the Crude Oil Scheduling of a Real-World Refinery. IEEE Syst. J. 14(3): 3926-3937 (2020) - [c19]Conor Ryan, Michael Kwaku Tetteh, Douglas Mota Dias:
Behavioural Modelling of Digital Circuits in System Verilog using Grammatical Evolution. IJCCI 2020: 28-39 - [c18]Aidan Murphy
Grammar-based Fuzzy Pattern Trees for Classification Problems. IJCCI 2020: 71-80
2010 – 2019
- 2018
- [j5]Waldir Jesus de Araujo Lobão, Marco Aurélio Cavalcanti Pacheco, Douglas Mota Dias, Ana Carolina Alves Abreu:
Solving stochastic differential equations through genetic programming and automatic differentiation. Eng. Appl. Artif. Intell. 68: 110-120 (2018) - [c17]Rogerio C. B. L. Povoa, Adriano S. Koshiyama, Douglas Mota Dias, Patricia L. Souza, Bruno A. C. Horta:
Multi-Modal Optimization by Multi-Gene Genetic Programming. CEC 2018: 1-8 - [c16]Cristiane Salgado Pereira, Douglas Mota Dias, Marley M. B. R. Vellasco, Francisco Henrique F. Viana, Luis Martí:
Crude oil refinery scheduling: addressing a real-world multiobjective problem through genetic programming and dominance-based approaches. GECCO (Companion) 2018: 1821-1828 - 2017
- [c15]André Luiz Farias Novaes, Ricardo Tanscheit
Econometric Genetic Programming in Binary Classification: Evolving Logistic Regressions Through Genetic Programming. EPIA 2017: 382-394 - [c14]André Luiz Farias Novaes, Ricardo Tanscheit
Econometric genetic programming outperforms traditional econometric algorithms for regression tasks. GECCO (Companion) 2017: 1427-1430 - 2016
- [c13]Waldir Jesus de Araujo Lobão, Douglas Mota Dias, Marco Aurélio Cavalcanti Pacheco:
Genetic programming and automatic differentiation algorithms applied to the solution of ordinary and partial differential equations. CEC 2016: 5286-5292 - [c12]Valentina Sessa
A single-phase active filter with cascaded multilevel inverter modelled as a complementarity problem. IECON 2016: 1075-1080 - 2015
- [j4]Cleomar Pereira da Silva, Douglas Mota Dias, Cristiana Bentes, Marco Aurélio Cavalcanti Pacheco:
Use of graphics processing units for automatic synthesis of programs. Comput. Electr. Eng. 46: 112-122 (2015) - [j3]Cleomar Pereira da Silva, Douglas Mota Dias, Cristiana Bentes, Marco Aurélio Cavalcanti Pacheco, Leandro Fontoura Cupertino:
Evolving GPU machine code. J. Mach. Learn. Res. 16: 673-712 (2015) - 2014
- [c11]Guilherme Cesário Strachan, Adriano S. Koshiyama, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti Pacheco:
Quantum-Inspired Multi-gene Linear Genetic Programming Model for Regression Problems. BRACIS 2014: 152-157 - [c10]Guilherme Cesário Strachan, Adriano Soares Koshiyama, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti Pacheco:
Towards a quantum-inspired multi-gene linear genetic programming model. GECCO (Companion) 2014: 149-150 - [c9]Eric da Silva Praxedes, Adriano S. Koshiyama, Elita Selmara Abreu, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti Pacheco:
Lithology discrimination using seismic elastic attributes: a genetic fuzzy classifier approach. GECCO 2014: 1151-1158 - 2013
- [j2]Douglas Mota Dias, Marco Aurélio Cavalcanti Pacheco:
Quantum-Inspired Linear Genetic Programming as a Knowledge Management System. Comput. J. 56(9): 1043-1062 (2013) - [c8]Adriano S. Koshiyama, Tatiana Escovedo, Douglas Mota Dias, Marley M. B. R. Vellasco, Ricardo Tanscheit
GPF-CLASS: A Genetic Fuzzy model for classification. IEEE Congress on Evolutionary Computation 2013: 3275-3282 - [c7]Adriano Soares Koshiyama, Douglas Mota Dias, André Vargas Abs da Cruz, Marco Aurélio Cavalcanti Pacheco:
Numerical optimization by multi-gene genetic programming. GECCO (Companion) 2013: 145-146 - 2012
- [j1]Adriano S. Koshiyama, Tatiana Escovedo, Douglas Mota Dias, Marley Maria Bernardes Rebuzzi Vellasco, Marco Aurélio Cavalcanti Pacheco:
Combining Forecasts: A Genetic Programming Approach. Int. J. Nat. Comput. Res. 3(3): 41-58 (2012) - [c6]Douglas Mota Dias
Describing Quantum-Inspired Linear Genetic Programming from symbolic regression problems. IEEE Congress on Evolutionary Computation 2012: 1-8 - 2011
- [c5]Douglas Mota Dias
Self-assembly quantum dots growth prediction by quantum-inspired linear genetic programming. IEEE Congress on Evolutionary Computation 2011: 2075-2082 - [c4]Leandro F. Cupertino, Cleomar Pereira da Silva, Douglas Mota Dias
Evolving CUDA PTX programs by quantum inspired linear genetic programming. GECCO (Companion) 2011: 399-406
2000 – 2009
- 2009
- [c3]Douglas Mota Dias
Toward a Quantum-Inspired Linear Genetic Programming model. IEEE Congress on Evolutionary Computation 2009: 1691-1698 - 2007
- [c2]Leonard M. Sim, Douglas Mota Dias
Refinery Scheduling Optimization using Genetic Algorithms and Cooperative Coevolution. CISched 2007: 151-158 - 2006
- [c1]Douglas Mota Dias, Marco Aurélio Cavalcanti Pacheco, José Franco Machado do Amaral
Genetic Programming of a Microcontrolled Water Bath Plant. KES (3) 2006: 307-314 - [p1]Douglas Mota Dias, Marco Aurélio Cavalcanti Pacheco, José F. M. do Amaral:
Automatic Synthesis of Microcontroller Assembly Code Through Linear Genetic Programming. Genetic Systems Programming 2006: 193-227
Coauthor Index
aka: Marco Aurélio Cavalcanti Pacheco
aka: Marley Maria Bernardes Rebuzzi Vellasco
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