Genetic Laws Applied

Genetic Programming Operators Applied to Genetic Algorithms

Like other learning paradigms, the performance of the genetic algorithms (GAs) is dependent on the parameter choice, on the problem representation, and on the fitness landscape. Accordingly, a GA can show good or weak results even when applied on the same problem. Following this idea, the crossover operator plays an important role, and its study is the object of the present paper. A mathematica...

Geostatistical Scaling Laws Applied to Core and Log Data

Reconciling data from different scales is a longstanding problem in reservoir characterization. Data from core plugs, well logs of different types, and seismic data must all be accounted for in the construction of a geostatistical reservoir model. These data are at vastly different scales and it is inappropriate to ignore the scale difference when constructing a geostatistical model. Geostatist...

Sharing Data under Genetic Privacy Laws

Clinical medical practice and biomedical research utilize genetic information for specific purposes. Irrespective of the purpose of obtaining genetic material, methodologies for protecting the privacy of patients/donors in both clinical and research settings have not kept pace with rapid genetic advances. When the usage of genetic information is not predicated on the latest laws and policies, t...

Genetic models in applied physiology.

Genetic Algorithms Applied to Clustering

In the following paper it is developed an image compression technique using clustering with genetic algorithms. This technique tries to avoid the problems associated with limitations from the operating system (MS-DOS), as Mariano O'kon [1] proposses in his tesis on genetic algorithms. The main problem, appears to be the large size of the data structures used by this kind of algorithms, which ca...