Results 51 to 60 of about 6,017,267 (341)

Prospects for computational steering of evolutionary computation [PDF]

, 2002
Currently, evolutionary computation (EC) typically takes place in batch mode: algorithms are run autonomously, with the user providing little or no intervention or guidance. Although it is rarely possible to specify in advance, on the basis of EC theory,
Bullock, Seth, Cartlidge, J., Thompson, M.   +2 more
core   +2 more sources

A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization

IEEE Transactions on Evolutionary Computation, 2019
Surrogate-assisted evolutionary algorithms (SAEAs) have been developed mainly for solving expensive optimization problems where only a small number of real fitness evaluations are allowed.
Linqiang Pan, Cheng He, Ye Tian, Handing Wang, Xing-yi Zhang, Yaochu Jin   +5 more
semanticscholar   +1 more source

Expression and DNA methylation of 20S proteasome subunits as prognostic and resistance markers in cancer

Molecular Oncology, EarlyView.
Comprehensive analysis of genomic mutations, gene expression, DNA methylation, and pathway analysis of TCGA data was carried out to define cancer types in which proteasome subunits expression is associated with worse survival. Albeit the effect of specific proteasome subunits on cellular function, the main role of the proteasome is better evaluated ...
Ruba Al‐Abdulla, Simone Venz, Ruslan Al‐Ali, Martin Wendlandt, Mandy Radefeldt, Elke Krüger   +5 more
wiley   +1 more source

Decomposition-Based Multi-Objective Evolutionary Algorithm Design Under Two Algorithm Frameworks

IEEE Access, 2020
The development of efficient and effective evolutionary multi-objective optimization (EMO) algorithms has been an active research topic in the evolutionary computation community. Over the years, many EMO algorithms have been proposed.
Lie Meng Pang, Hisao Ishibuchi, Ke Shang
doaj   +1 more source

Evolutionary algorithm-based analysis of gravitational microlensing lightcurves

, 2012
A new algorithm developed to perform autonomous fitting of gravitational microlensing lightcurves is presented. The new algorithm is conceptually simple, versatile and robust, and parallelises trivially; it combines features of extant evolutionary ...
Asada, Beaulieu, Bennett, Bennett, Bennett, Bourassa, Bozza, Burnham, Cassan, Charbonneau, Charbonneau, Di Stefano, Dominik, Dominik, Eiben, Gaudi, Gaudi, Gaudi, Gould, Gregory, Haario, Haupt, Heavens, Holland, Hundertmark, Jaroszyński, Kains, King, Kramer, Lagarias, Mao, Mao, Michalewicz, Michalewicz, Miller, Moré, Nelder, Night, Pospichal, Press, Quanz, Rajpaul, Ralston, Risco-Martín, Shin, Shvartzvald, Skowron, Sumi, Sumi, Thierens, Udalski, V. Rajpaul, Vermaak, Vermaak, Wambsganss, Wehrens, Witt   +56 more
core   +1 more source

Competent genetic-evolutionary optimization of water distribution systems [PDF]

, 2001
A genetic algorithm has been applied to the optimal design and rehabilitation of a water distribution system. Many of the previous applications have been limited to small water distribution systems, where the computer time used for solving the problem ...
Simpson, A., Wu, Z.
core   +1 more source

Unraveling LINE‐1 retrotransposition in head and neck squamous cell carcinoma

Molecular Oncology, EarlyView.
The novel RetroTest method allows the detection of L1 activation in clinical samples with low DNA input, providing global L1 activity and the identification of the L1 source element. We applied RetroTest to a real‐world cohort of HNSCC patients where we reported an early L1 activation, with more than 60% of T1 patients showing L1 activity.
Jenifer Brea‐Iglesias, Ana Oitabén, Sonia Zumalave, Bernardo Rodriguez‐Martin, María Gallardo‐Gómez, Martín Santamarina, Ana Pequeño‐Valtierra, Laura Juaneda‐Magdalena, Ramón García‐Escudero, José Luis López‐Cedrún, Máximo Fraga, José M. C. Tubio, Mónica Martínez‐Fernández   +12 more
wiley   +1 more source

A Novel Multi-Objective Hybrid Evolutionary-Based Approach for Tuning Machine Learning Models in Short-Term Power Consumption Forecasting

AI
Accurately forecasting power consumption is crucial important for efficient energy management. Machine learning (ML) models are often employed for this purpose. However, tuning their hyperparameters is a complex and time-consuming task.
Aleksei Vakhnin, Ivan Ryzhikov, Harri Niska, Mikko Kolehmainen   +3 more
doaj   +1 more source

A convergence acceleration operator for multiobjective optimisation [PDF]

, 2007
A novel multiobjective optimisation accelerator is introduced that uses direct manipulation in objective space together with neural network mappings from objective space to decision space.
Adra, S.F., Fleming, P.J., Griffin, I.A.
core   +1 more source

A Hybrid Artificial Bee Colony Algorithm for Graph 3-Coloring

, 2012
The Artificial Bee Colony (ABC) is the name of an optimization algorithm that was inspired by the intelligent behavior of a honey bee swarm. It is widely recognized as a quick, reliable, and efficient methods for solving optimization problems. This paper
A. Hertz, A.D. Petford, A.E. Eiben, A.E. Eiben, C. Fleurent, D. Brelaz, D. Karaboga, E. Aarts, F. Glover, J. Kennedy, J. Robinson, J.A. Bondy, J.S. Turner, M. Dorigo, M.F. Tasgetiren, M.R. Garey, P. Galinier, P. Galinier, Q.K. Pan, S.S. Rao, X.-S. Yang, Z. Lü   +21 more
core   +1 more source