Genetic algorithm approach for the optimization of technical trading rule parameters.

2001
Hülagü, Timur
Show full item record
70
views
0
downloads
https://hdl.handle.net/11511/10777
Graduate School of Natural and Applied Sciences, Thesis

Suggestions

Genetic algorithm approach for the optimization of technical trading rule parameters
Ergökmen, N. Gülden; Department of Statistics (2001)
Genetic algorithm for constrained optimization models and its application in groundwater resources management
Guan, Jiabao; Kentel Erdoğan, Elçin; Aral, Mustafa M. (American Society of Civil Engineers (ASCE), 2008-01-01)
Genetic algorithms (GAs) have been shown to be an efficient tool for the solution of unconstrained optimization problems. In their standard form, GA formulations are "blind" to the constraints of an optimization model when the model involves these constraints. Thus, in GA applications alternative procedures are used to satisfy the constraints of the optimization model. In this study, the method that is utilized in the Complex Algorithm to solve constrained optimization problems is abstracted to develop a re...
Genetic Algorithms for Continuous Design Domain
Dölen, Melik; Kayıkçı, Ekrem (null; 1999-11-10)
Genetic algorithms for distributed database design and distributed database query optimization
Sevinç, Ender; Coşar, Ahmet; Department of Computer Engineering (2009)
The increasing performance of computers, reduced prices and ability to connect systems with low cost gigabit ethernet LAN and ATM WAN networks make distributed database systems an attractive research area. However, the complexity of distributed database query optimization is still a limiting factor. Optimal techniques, such as dynamic programming, used in centralized database query optimization are not feasible because of the increased problem size. The recently developed genetic algorithm (GA) based optimi...
Genetic Algorithm Application to the Structural Properties of Si-Ge Mixed Clusters
Dugan, Nazim; Erkoç, Şakir (Informa UK Limited, 2009-01-01)
Optimum geometries of silicon-germanium (Si-Ge) clusters are found using a single parent genetic algorithm. 100 atom and 150 atom clusters are studied with some variety of compositions and initial geometries. Total interaction energies, distances of Si and Ge atoms to the cluster centers, and average bond lengths are calculated. Si-core Ge-shell geometry is found to be favorable compared to other geometries.
Citation Formats
T. Hülagü, “Genetic algorithm approach for the optimization of technical trading rule parameters.,” Middle East Technical University, 2001.
METU IIS - Integrated Information Service open@metu.edu.tr