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Turbo coding is an influential method of channel coding in telecommunications. The introduction of the turbo principle allowed close approach to the Shannon limit, a theoretical boundary describing the maximum capacity of a noisy communication channel. The invention of the turbo codes and its superior performance in practical applications also initiated a renaissance of channel coding research. The...
In this study we discuss a method for evolution of quasigroups with desired properties based on genetic algorithms. Quasigroups are a well-known combinatorial design equivalent to the more familiar Latin squares. One of their most important properties is that all possible elements of certain quasigroup occur with equal probability. The quasigroups are evolved within a framework of a simple hash function...
The satisfiability is a decision problem that belongs to NP-complete class and has significant applications in various areas of computer science. Several works have proposed high-performance algorithms and solvers to explore the space of variables and look for satisfying assignments. Pedrycz, Succi and Shai (2002) have studied a fuzzy-genetic approach which demonstrates that a formula of variables...
Risk assessment is often done by human experts, because there is no exact and mathematical solution to the problem.Usually the human reasoning and perception process cannot be expressed precisely. This paper propose a genetic programming approach for risk assessment. Preliminary results indicate that genetic programming methods are robust and suitable for this problem when compared to other risk assessment...
Bacterial-foraging optimization algorithm (BFOA) attempts to model the individual and group behavior of E.Coli bacteria as a distributed optimization process. Since its inception, BFOA has been finding many important applications in real-world optimization problems from diverse domains of science and engineering. One key step in BFOA is the computational chemotaxis, where a bacterium (which models...
The requirements imposed on information retrieval systems are increasing steadily. The vast number of documents in today's large databases and especially on World Wide Web causes notable problems when searching for concrete information. It is difficult to find satisfactory information that accurately matches user information needs even if it is present in the database. One of the key elements when...
Job Scheduling on Computational Grids is gaining importance due to the need for efficient large-scale Grid-enabled applications. Among different optimization techniques addressed for the problem, Genetic Algorithm (GA) is a popular class of solution methods. As GAs are high level algorithms, specific algorithms can be designed by choosing the genetic operators as well as the evolutionary strategies...
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