Results 31 to 40 of about 208,088 (288)

Robust Gene Expression Programming

Procedia Computer Science, 2011
AbstractGenetic/evolutionary methods are frequently used to deal with complex adaptive systems. The classic example is a Genetic Algorithm. A Genetic Algorithm uses a simple linear representation for possible solutions to a problem. This is usually a bit vector. Unfortunately, the natural representation for many problems is a tree structure.
Ryan, Noah, Hibler, David
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Deterministic Ensemble Forecasts Using Gene-Expression Programming* [PDF]

Weather and Forecasting, 2009
AbstractA method called gene-expression programming (GEP), which uses symbolic regression to form a nonlinear combination of ensemble NWP forecasts, is introduced. From a population of competing and evolving algorithms (each of which can create a different combination of NWP ensemble members), GEP uses computational natural selection to find the ...
Bakhshaii, Atoossa, Stull, Roland B.
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Corticotropin-releasing hormone as the homeostatic rheostat of feto-maternal symbiosis and developmental programming In utero and neonatal life [PDF]

, 2017
A balanced interaction between the homeostatic mechanisms of mother and the devel- oping organism during pregnancy and in early neonatal life is essential in order to ensure optimal fetal development, ability to respond to various external and internal ...
Alcantara-Alonso, Alexander, Arborelius, Bale, Baram, Barker, Bellisario, Benjamin Neelon, Bosch, Bouret, Bowman, Briana, Brummelte, Brunson, Brunton, Brunton, Brunton, Brunton, Capron, Chen, Chen, Choy, Cirulli, Cirulli, Class, Clifton, Cottrell, Dallman, Davis, de Weerth, Demendi, Desai, Dimasuay, Dunkel, D’Amato, Eghbal-Ahmadi, Ehlers, Ellman, Entringer, Fasting, Faturi, Fenoglio, Gao, Gillman, Glynn, Gomez-Roig, Grammatopoulos, Gunnar, Harville, Hollrigel, Husum, Ibanez, Kammerer, Kensara, Korosi, Labonte, Ladyman, Larsen, Lee, Lockwood, Machado, MacKay, Maffeis, Magiakou, Maniam, Marciniak, McLean, Mingrone, Owens, Pasquali, Paternain, Pedersen, Pelleymounter, Peng, Perrone, Pervanidou, Petraglia, Pihoker, Plotsky, Purcell, Robinson, Romens, Sanchez, Sandman, Sandman, Schmidt, Schulte, Seckl, Seckl, Sferruzzi-Perri, Shapiro, Singh-Taylor, Smith, Soma-Pillay, Stout, Suderman, Sun, Symonds, Tamashiro, Turecki, van Bodegom, Vazquez, Vickers, Wadhwa, Wakahashi, Walker, Wang, Weaver, Weaver, Weinstock, Whitaker, Whitehead, Wolfe, Yam, Zambrano   +114 more
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Inducible and Deterministic Forward Programming of Human Pluripotent Stem Cells into Neurons, Skeletal Myocytes, and Oligodendrocytes

Stem Cell Reports, 2017
Summary: The isolation or in vitro derivation of many human cell types remains challenging and inefficient. Direct conversion of human pluripotent stem cells (hPSCs) by forced expression of transcription factors provides a potential alternative. However,
Matthias Pawlowski, Daniel Ortmann, Alessandro Bertero, Joana M. Tavares, Roger A. Pedersen, Ludovic Vallier, Mark R.N. Kotter   +6 more
doaj   +1 more source

Modelling and trading the Greek stock market with gene expression and genetic programing algorithms [PDF]

, 2014
This paper presents an application of the gene expression programming (GEP) and integrated genetic programming (GP) algorithms to the modelling of ASE 20 Greek index. GEP and GP are robust evolutionary algorithms that evolve computer programs in the form
Dunis, Christian, Karathanasopoulos, Andreas, Laws, Jason, Sermpinis, Georgios   +3 more
core   +1 more source

Maternally expressed gene 3 in metabolic programming

Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms, 2020
Maternally Expressed Gene 3 (MEG3) is a long noncoding RNA (lncRNA) that coordinates a diverse array of cellular processes requiring epigenetic regulation of genes and interactions with key signaling proteins and by acting as a competitive endogenous (ce)RNA.
Samuel, Hamilton, Rafael, de Cabo, Michel, Bernier   +2 more
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Deriving Trading Rules Using Gene Expression Programming [PDF]

Informatică economică, 2011
This paper presents how buy and sell trading rules are generated using gene expression programming with special setup. Market concepts are presented and market analysis is discussed with emphasis on technical analysis and quantitative methods. The use of
Adrian VISOIU
doaj  

Deep gene selection method to select genes from microarray datasets for cancer classification

BMC Bioinformatics, 2019
Background Microarray datasets consist of complex and high-dimensional samples and genes, and generally the number of samples is much smaller than the number of genes.
Russul Alanni, Jingyu Hou, Hasseeb Azzawi, Yong Xiang   +3 more
doaj   +1 more source

A Comparative Study of Dispatching Rule Representations in Evolutionary Algorithms for the Dynamic Unrelated Machines Environment

IEEE Access, 2022
Dispatching rules are most commonly used to solve scheduling problems under dynamic conditions. Since designing new dispatching rules is a time-consuming process, it can be automated by using various machine learning and evolutionary computation methods.
Lucija Planinic, Hrvoje Backovic, Marko Durasevic, Domagoj Jakobovic   +3 more
doaj   +1 more source

A Gene Expression Programming Model for Predicting Tunnel Convergence

Applied Sciences, 2019
Underground spaces have become increasingly important in recent decades in metropolises. In this regard, the demand for the use of underground spaces and, consequently, the excavation of these spaces has increased significantly.
Mohsen Hajihassani, Shahrum Shah Abdullah, Panagiotis G. Asteris, Danial Jahed Armaghani   +3 more
doaj   +1 more source