Theo dõi
Daniel Molina Cabrera
Daniel Molina Cabrera
Computer Science, Granada University
Email được xác minh tại decsai.ugr.es
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
AB Arrieta, N Díaz-Rodríguez, J Del Ser, A Bennetot, S Tabik, A Barbado, ...
Information fusion 58, 82-115, 2020
67422020
A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
J Derrac, S García, D Molina, F Herrera
Swarm and Evolutionary Computation 1 (1), 3-18, 2011
49482011
A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 special session on real parameter optimization
S García, D Molina, M Lozano, F Herrera
Journal of Heuristics 15, 617-644, 2009
18622009
Bio-inspired computation: Where we stand and what's next
J Del Ser, E Osaba, D Molina, XS Yang, S Salcedo-Sanz, D Camacho, ...
Swarm and Evolutionary Computation 48, 220-250, 2019
5382019
Real-coded memetic algorithms with crossover hill-climbing
M Lozano, F Herrera, N Krasnogor, D Molina
Evolutionary computation 12 (3), 273-302, 2004
4312004
Global and local real-coded genetic algorithms based on parent-centric crossover operators
C García-Martínez, M Lozano, F Herrera, D Molina, AM Sánchez
European journal of operational research 185 (3), 1088-1113, 2008
2982008
A tutorial on the design, experimentation and application of metaheuristic algorithms to real-world optimization problems
E Osaba, E Villar-Rodriguez, J Del Ser, AJ Nebro, D Molina, A LaTorre, ...
Swarm and Evolutionary Computation 64, 100888, 2021
2122021
Memetic algorithms for continuous optimisation based on local search chains
D Molina, M Lozano, C Garcia-Martinez, F Herrera
Evolutionary computation 18 (1), 27-63, 2010
2072010
Comprehensive taxonomies of nature-and bio-inspired optimization: Inspiration versus algorithmic behavior, critical analysis recommendations
D Molina, J Poyatos, JD Ser, S García, A Hussain, F Herrera
Cognitive Computation 12, 897-939, 2020
1972020
MA-SW-Chains: Memetic algorithm based on local search chains for large scale continuous global optimization
D Molina, M Lozano, F Herrera
IEEE congress on evolutionary computation, 1-8, 2010
1952010
Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems
M Lozano, D Molina, F Herrera
Soft computing 15, 2085-2087, 2011
1662011
A panoramic view and swot analysis of artificial intelligence for achieving the sustainable development goals by 2030: Progress and prospects
I Palomares, E Martínez-Cámara, R Montes, P García-Moral, M Chiachio, ...
Applied Intelligence 51, 6497-6527, 2021
1442021
Adaptive local search parameters for real-coded memetic algorithms
D Molina, F Herrera, M Lozano
2005 IEEE Congress on Evolutionary Computation 1, 888-895, 2005
1412005
Test suite for the special issue of soft computing on scalability of evolutionary algorithms and other metaheuristics for large scale continuous optimization problems
F Herrera, M Lozano, D Molina
Last accessed: July, 2010
1262010
Continuous scatter search: an analysis of the integration of some combination methods and improvement strategies
F Herrera, M Lozano, D Molina
European Journal of Operational Research 169 (2), 450-476, 2006
1192006
Memetic algorithms based on local search chains for large scale continuous optimisation problems: MA-SSW-Chains
D Molina, M Lozano, AM Sánchez, F Herrera
Soft Computing 15, 2201-2220, 2011
1162011
An insight into bio-inspired and evolutionary algorithms for global optimization: review, analysis, and lessons learnt over a decade of competitions
D Molina, A LaTorre, F Herrera
Cognitive Computation 10, 517-544, 2018
1012018
SHADE with iterative local search for large-scale global optimization
D Molina, A LaTorre, F Herrera
2018 IEEE congress on evolutionary computation (CEC), 1-8, 2018
972018
A walk into metaheuristics for engineering optimization: principles, methods and recent trends
N Xiong, D Molina, ML Ortiz, F Herrera
international journal of computational intelligence systems 8 (4), 606-636, 2015
962015
A prescription of methodological guidelines for comparing bio-inspired optimization algorithms
A LaTorre, D Molina, E Osaba, J Poyatos, J Del Ser, F Herrera
Swarm and Evolutionary Computation 67, 100973, 2021
852021
Hệ thống không thể thực hiện thao tác ngay bây giờ. Hãy thử lại sau.
Bài viết 1–20