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Renato Tinós
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2020 – today
- 2024
- [j22]Douglas Donizeti de Castilho Braz, Moisés Rocha dos Santos
, Marcos Basile Saviano de Paula, Donato da Silva Filho, Ewerton Guarnier, Lucas Penido Alípio, Renato Tinós
Multi-source data ensemble for energy price trend forecasting. Eng. Appl. Artif. Intell. 133: 108125 (2024) - [j21]Renato Tinós
Iterated Local Search with Linkage Learning. ACM Trans. Evol. Learn. Optim. 4(2): 7 (2024) - [c63]Marcin Michal Komarnicki
Overlapping Cooperative Co-Evolution for Overlapping Large-Scale Global Optimization Problems. GECCO 2024 - [c62]Lukasz Tulczyjew
CANNIBAL Unveils the Hidden Gems: Hyperspectral Band Selection via Clustering of Weighted Variable Interaction Graphs. GECCO 2024 - [c61]Francisco Chicano
Generalizing and Unifying Gray-Box Combinatorial Optimization Operators. PPSN (1) 2024: 52-67 - [i7]Renato Tinós, Liang Zhao, Francisco Chicano, Darrell Whitley:
NK Hybrid Genetic Algorithm for Clustering. CoRR abs/2402.03813 (2024) - [i6]Francisco Chicano, Gabriela Ochoa, Darrell Whitley, Renato Tinós:
Dynastic Potential Crossover Operator. CoRR abs/2402.03918 (2024) - [i5]Francisco Chicano, Darrell Whitley, Gabriela Ochoa, Renato Tinós:
Generalizing and Unifying Gray-box Combinatorial Optimization Operators. CoRR abs/2407.06742 (2024) - [i4]Renato Tinós, Michal Przewozniczek, Darrell Whitley, Francisco Chicano:
Iterated Local Search with Linkage Learning. CoRR abs/2410.01583 (2024) - 2023
- [c60]Maísa de Carvalho Silva, Paulo Guilherme Pinheiro Pereira, Lariza Laura de Oliveira
Multiobjective Evolutionary Algorithms Applied to the Optimization of Expanded Genetic Codes. BRACIS (3) 2023: 3-16 - [c59]Michal Witold Przewozniczek
First Improvement Hill Climber with Linkage Learning - on Introducing Dark Gray-Box Optimization into Statistical Linkage Learning Genetic Algorithms. GECCO 2023: 946-954 - [c58]Renato Tinós
Genetic Algorithm with Linkage Learning. GECCO 2023: 981-989 - [c57]Douglas Castilho, Moisés R. Santos, Renato Tinós, André C. P. L. F. de Carvalho
Feature Selection using Complex Networks to Support Price Trend Forecast in Energy Markets. IJCNN 2023: 1-9 - [c56]Sérgio Baldo Júnior, Murillo G. Carneiro, João-Batista Destro-Filho, Liang Zhao, Renato Tinós:
Classification of coma etiology using convolutional neural networks and long-short term memory networks. IJCNN 2023: 1-8 - 2022
- [j20]Francisco Chicano, Gabriela Ochoa, L. Darrell Whitley, Renato Tinós:
Dynastic Potential Crossover Operator. Evol. Comput. 30(3): 409-446 (2022) - [j19]Rafael Silva Del Lama, Raquel Mariana Candido, Natália Santana Chiari-Correia, Marcello Henrique Nogueira-Barbosa, Paulo Mazzoncini de Azevedo Marques
Computer-Aided Diagnosis of Vertebral Compression Fractures Using Convolutional Neural Networks and Radiomics. J. Digit. Imaging 35(3): 446-458 (2022) - [c55]Michal Witold Przewozniczek, Renato Tinós, Bartosz Frej, Marcin M. Komarnicki:
On turning black - into dark gray-optimization with the direct empirical linkage discovery and partition crossover. GECCO 2022: 269-277 - [c54]Renato Tinós, Michal Witold Przewozniczek, Darrell Whitley:
Iterated local search with perturbation based on variables interaction for pseudo-boolean optimization. GECCO 2022: 296-304 - [c53]Moisés R. Santos
Machine Learning Approach for Trend Prediction to Improve Returns on Brazilian Energy Market. LA-CCI 2022: 1-6 - 2021
- [j18]Luiz Eduardo Virgilio da Silva, Henrique Turin Moreira
Prediction of echocardiographic parameters in Chagas disease using heart rate variability and machine learning. Biomed. Signal Process. Control. 67: 102513 (2021) - [c52]Giliard Almeida de Godoi
A Graph-Based Crossover and Soft-Repair Operators for the Steiner Tree Problem. BRACIS (1) 2021: 111-125 - [c51]Anirban Mukhopadhyay, L. Darrell Whitley, Renato Tinós
An efficient implementation of iterative partial transcription for the traveling salesman problem. GECCO 2021: 252-260 - [c50]Renato Tinós
Partition crossover for continuous optimization: ePX. GECCO 2021: 627-635 - [c49]Daniel A. Santos, José Augusto Baranauskas, Renato Tinós:
Use of Fitness Sharing in the Local Rule-Based Explanations Method. LA-CCI 2021: 1-6 - 2020
- [j17]Renato Tinós
Artificial neural network based crossover for evolutionary algorithms. Appl. Soft Comput. 95: 106512 (2020) - [j16]Renato Tinós
A New Generalized Partition Crossover for the Traveling Salesman Problem: Tunneling between Local Optima. Evol. Comput. 28(2): 255-288 (2020)
2010 – 2019
- 2019
- [j15]Renato Tinós
A framework for inducing artificial changes in optimization problems. Inf. Sci. 485: 486-504 (2019) - [c48]Ozeas Quevedo de Carvalho
A New Method for Identification of Recombining Components in the Generalized Partition Crossover. BRACIS 2019: 36-41 - [c47]Renato Tinós
An RBF Network Based Crossover for Pseudo-Boolean Optimization. BRACIS 2019: 174-179 - [c46]Renato Tinós
Using Hyperplanes to Create Neutral Networks in Pseudo-Boolean Optimization. BRACIS 2019: 353-358 - [c45]Francisco Chicano
Quasi-Optimal Recombination Operator. EvoCOP 2019: 131-146 - [c44]L. Darrell Whitley, Francisco Chicano, Gabriela Ochoa, Andrew M. Sutton, Renato Tinós:
Next generation genetic algorithms. GECCO (Companion) 2019: 1113-1136 - 2018
- [j14]Lariza Laura de Oliveira, Alex Alves Freitas, Renato Tinós
Multi-objective genetic algorithms in the study of the genetic code's adaptability. Inf. Sci. 425: 48-61 (2018) - [j13]Renato Tinós
NK Hybrid Genetic Algorithm for Clustering. IEEE Trans. Evol. Comput. 22(5): 748-761 (2018) - [c43]Renato Tinós
A Fusion Mechanism for the Generalized Asymmetric Partition Crossover. CEC 2018: 1-8 - [c42]Filipe Alves Neto Verri
Feature Learning in Feature-Sample Networks Using Multi-Objective Optimization. CEC 2018: 1-6 - [c41]Francisco Chicano, Gabriela Ochoa, L. Darrell Whitley, Renato Tinós
Enhancing partition crossover with articulation points analysis. GECCO 2018: 269-276 - [c40]Wenxiang Chen, L. Darrell Whitley, Renato Tinós
Tunneling between plateaus: improving on a state-of-the-art MAXSAT solver using partition crossover. GECCO 2018: 921-928 - [c39]L. Darrell Whitley, Francisco Chicano, Gabriela Ochoa, Andrew M. Sutton, Renato Tinós:
Next generation genetic algorithms. GECCO (Companion) 2018: 1039-1059 - [c38]Renato Tinós
Efficient Recombination in the Lin-Kernighan-Helsgaun Traveling Salesman Heuristic. PPSN (1) 2018: 95-107 - [c37]L. Darrell Whitley, Renato Tinós
Optimal Neuron Selection and Generalization: NK Ensemble Neural Networks. PPSN (2) 2018: 449-460 - 2017
- [c36]Danilo Sipoli Sanches, L. Darrell Whitley, Renato Tinós
Building a better heuristic for the traveling salesman problem: combining edge assembly crossover and partition crossover. GECCO 2017: 329-336 - [c35]Danilo Sipoli Sanches, L. Darrell Whitley, Renato Tinós
Improving an exact solver for the traveling salesman problem using partition crossover. GECCO 2017: 337-344 - [c34]Francisco Chicano, L. Darrell Whitley, Gabriela Ochoa, Renato Tinós
Optimizing one million variable NK landscapes by hybridizing deterministic recombination and local search. GECCO 2017: 753-760 - [i3]Filipe Alves Neto Verri, Renato Tinós, Liang Zhao:
Feature learning in feature-sample networks using multi-objective optimization. CoRR abs/1710.09300 (2017) - 2016
- [c33]Francisco Chicano, L. Darrell Whitley, Renato Tinós
Efficient Hill Climber for Multi-Objective Pseudo-Boolean Optimization. EvoCOP 2016: 88-103 - [c32]Francisco Chicano, L. Darrell Whitley, Renato Tinós
Efficient Hill Climber for Constrained Pseudo-Boolean Optimization Problems. GECCO 2016: 309-316 - [c31]Renato Tinós
A New Evaluation Function for Clustering: The NK Internal Validation Criterion. GECCO 2016: 509-516 - [c30]Renato Tinós
Artificially Inducing Environmental Changes in Evolutionary Dynamic Optimization. PPSN 2016: 225-236 - [c29]Nadarajen Veerapen
Tunnelling Crossover Networks for the Asymmetric TSP. PPSN 2016: 994-1003 - [i2]Francisco Chicano, L. Darrell Whitley, Renato Tinós:
Efficient Hill-Climber for Multi-Objective Pseudo-Boolean Optimization. CoRR abs/1601.07596 (2016) - 2015
- [j12]Lariza Laura de Oliveira, Paulo de Oliveira, Renato Tinós
A multiobjective approach to the genetic code adaptability problem. BMC Bioinform. 16: 52:1-52:20 (2015) - [c28]Renato Tinós
Partition Crossover for Pseudo-Boolean Optimization. FOGA 2015: 137-149 - [c27]Gabriela Ochoa
Tunnelling Crossover Networks. GECCO 2015: 449-456 - [i1]L. Darrell Whitley, Renato Tinós, Francisco Chicano:
Optimal Neuron Selection: NK Echo State Networks for Reinforcement Learning. CoRR abs/1505.01887 (2015) - 2014
- [j11]Renato Tinós
Analysis of fitness landscape modifications in evolutionary dynamic optimization. Inf. Sci. 282: 214-236 (2014) - [j10]Lariza Laura de Oliveira, Renato Tinós
Entropy-based evaluation function in a multi-objective approach for the investigation of the genetic code robustness. Memetic Comput. 6(3): 157-170 (2014) - [c26]Ariadne de Andrade Costa, Renato Tinós
An Evolving Artificial Neural Network for the Investigation of Rat Exploratory Behavior. BRACIS 2014: 103-108 - [c25]Renato Tinós
Generalized asymmetric partition crossover (GAPX) for the asymmetric TSP. GECCO 2014: 501-508 - [c24]Renato Tinós
Use of explicit memory in the dynamic traveling salesman problem. GECCO 2014: 999-1006 - 2013
- [j9]Helder K. Shimo, Renato Tinós
Use of self-organizing suppression and q-Gaussian mutation in artificial immune systems. Int. J. Intell. Comput. Cybern. 6(3): 296-322 (2013) - [c23]Ariadne A. Costa
Using explicit averaging fitness for studying the behaviour of rats in a maze. ECAL 2013: 940-946 - [c22]Lariza Laura de Oliveira, Renato Tinós
Using Base Position Errors in an Entropy-Based Evaluation Function for the Study of Genetic Code Adaptability. NICSO 2013: 99-111 - 2012
- [j8]Juliana Tarossi Pollettini, Sylvia R. G. Panico, Julio C. Daneluzzi, Renato Tinós
Using Machine Learning Classifiers to Assist Healthcare-Related Decisions: Classification of Electronic Patient Records. J. Medical Syst. 36(6): 3861-3874 (2012) - [c21]Lariza Laura de Oliveira, Renato Tinós
Entropy-based evaluation function for the investigation of genetic code adaptability. BCB 2012: 558-560 - [c20]Renato Tinós
Analysing fitness landscape changes in evolutionary robots. GECCO (Companion) 2012: 385-392 - [c19]Ariadne A. Costa
A Model Based on Genetic Algorithm for Investigation of the Behavior of Rats in the Elevated Plus-Maze. IDEAL 2012: 151-158 - 2011
- [j7]Renato Tinós, Shengxiang Yang:
Self-adaptation of mutation distribution in evolution strategies for dynamic optimization problems. Int. J. Hybrid Intell. Syst. 8(3): 155-168 (2011) - [j6]Renato Tinós
Use of the q-Gaussian mutation in evolutionary algorithms. Soft Comput. 15(8): 1523-1549 (2011) - 2010
- [c18]Renato Tinós
An Analysis of the XOR Dynamic Problem Generator Based on the Dynamical System. PPSN (1) 2010: 274-283 - [c17]Helder K. Shimo, Antônio Carlos Roque-da-Silva, Renato Tinós
Use of Evolutionary Robots as an Auxiliary Tool for Developing Behavioral Models of Rats in an Elevated Plus-Maze. SBRN 2010: 217-222 - [c16]Renato Tinós
Evolution Strategies with q-Gaussian Mutation for Dynamic Optimization Problems. SBRN 2010: 223-228
2000 – 2009
- 2009
- [c15]Juliana Tarossi Pollettini, Flávia P. Nicolas, Sylvia R. G. Panico, Julio C. Daneluzzi, Renato Tinós
A Software Architecture-Based Framework Supporting Suggestion of Medical Surveillance Level from Classification of Electronic Patient Records. CSE (1) 2009: 166-173 - [c14]Vinicius Tragante do Ó
Control of the number of random imigrants in genetic algorithms for protein structure prediction. GECCO 2009: 1795-1796 - [p2]Renato Tinós
Use of the q-Gaussian Function in Radial Basis Function Networks. Foundations of Computational Intelligence (5) 2009: 127-145 - 2008
- [c13]Renato Tinós
Evolutionary programming with q-Gaussian mutation for dynamic optimization problems. IEEE Congress on Evolutionary Computation 2008: 1823-1830 - [c12]Shengxiang Yang
Hyper-selection in dynamic environments. IEEE Congress on Evolutionary Computation 2008: 3185-3192 - [c11]Renato Tinós
Selection of Radial Basis Functions via Genetic Algorithms in Pattern Recognition Problems. SBRN 2008: 171-176 - 2007
- [j5]Renato Tinós
A self-organizing random immigrants genetic algorithm for dynamic optimization problems. Genet. Program. Evolvable Mach. 8(3): 255-286 (2007) - [j4]Shengxiang Yang
A hybrid immigrants scheme for genetic algorithms in dynamic environments. Int. J. Autom. Comput. 4(3): 243-254 (2007) - [c10]Renato Tinós
Self-adaptation of mutation distribution in evolutionary algorithms. IEEE Congress on Evolutionary Computation 2007: 79-86 - [c9]Renato Tinós
Continuous dynamic problem generators for evolutionary algorithms. IEEE Congress on Evolutionary Computation 2007: 236-243 - [p1]Renato Tinós
Genetic Algorithms with Self-Organizing Behaviour in Dynamic Environments. Evolutionary Computation in Dynamic and Uncertain Environments 2007: 105-127 - 2006
- [j3]Renato Tinós
Use of gene dependent mutation probability in evolutionary neural networks for non-stationary problems. Neurocomputing 70(1-3): 44-54 (2006) - [j2]Renato Tinós
Motion and force control of cooperative robotic manipulators with passive joints. IEEE Trans. Control. Syst. Technol. 14(4): 725-734 (2006) - 2005
- [c8]Renato Tinós, Shengxiang Yang:
Genetic algorithms with self-organized criticality for dynamic optimization problems. Congress on Evolutionary Computation 2005: 2816-2823 - 2004
- [c7]Renato Tinós, André Carlos Ponce de Leon Ferreira de Carvalho
A genetic algorithm with gene dependent mutation probability for non-stationary optimization problems. IEEE Congress on Evolutionary Computation 2004: 1278-1285 - 2002
- [c6]Renato Tinós, Marco Henrique Terra
Control of cooperative manipulators with passive joints. ACC 2002: 1129-1134 - [c5]Renato Tinós, Marco H. Terra:
Free-swinging and locked joint fault detection and isolation in cooperative manipulators. ESANN 2002: 513-518 - [c4]Renato Tinós, Marco H. Terra, Marcel Bergerman:
Fault Tolerance in Cooperative Manipulators. ICRA 2002: 470-475 - 2001
- [j1]Marco Henrique Terra
Fault detection and isolation in robotic manipulators via neural networks: A comparison among three architectures for residual analysis. J. Field Robotics 18(7): 357-374 (2001) - [c3]Renato Tinós
Fault tolerant localization for teams of distributed robots. IROS 2001: 1061-1066
1990 – 1999
- 1998
- [c2]Renato Tinós
Fault Detection and Isolation in Robotic Manipulators and the Radial Basis Function Network Trained by the Kohonen's Self-Organizing Map. SBRN 1998: 85-90 - [c1]Marco Henrique Terra, Renato Tinós:
Fault detection and isolation for robotic systems using a multilayer perceptron and a radial basis function network. SMC 1998: 1880-1885
Coauthor Index
André C. P. L. F. de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
aka: André Carlos Ponce de Leon Ferreira de Carvalho
Michal Przewozniczek
aka: Michal Witold Przewozniczek
aka: Michal Witold Przewozniczek
L. Darrell Whitley
aka: Darrell Whitley
aka: Darrell Whitley
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