Data stream-based multimedia application is studied and a software/hardware partitioning method is proposed using both flexible granularity mechanism and extended mapping mechanism in this paper. This partitioning method focuses on genetic algorithm (GA), considering flexible granularity mechanism and extended mapping mechanism, designing special genetic coding method--double-link coding struct...

This study proposes an Ant Colony Optimization using Genetic Information (GIACO). The GIACO algorithm combines Ant Colony Optimization (ACO) with Genetic Algorithm (GA). GIACO searches solutions by using the pheromone of ACO and the genetic information of GA. In addition, two kinds of ants coexist: intelligent ant and dull ant. The dull ant is caused by the mutation and cannot trail the pheromo...

Engineering and science disciplines make use of genetic algorithms. A number of genetic-based search paradigms have been developed and applied to different problems. A growing demand for algorithms to solve new problems and a never-ending process of designing algorithms strongly suggests the need for more efficient and more robust geneticbased optimisation techniques. Ideally these algorithms s...

task in that good explanations of the positive examples is of more importance tions of genetic algorithms to various research questions in human genetics. 2 Genetic Algorithms, Constraints, and the Knapsack Problem. 10 5.2 Inductive Learning From Examples. 6.3 Genetic Algorithms and Concept Learning. In this paper, we explore Genetic Algorithms (GA) as an alternative approach to derive these mo...

This paper discusses a genetic algorithm (GA) based method for automatically tuning mobile robot motion controllers. The genetic algorithm evolves a controller that is optimised for a given performance measure. Genetic algorithms require a mapping from the genetic code to an implementation. This translation between the chromosome and the implementation allows the use of standard GA libraries, h...

The paper presents a Genetic Algorithm (GA) approach for solving constrained reliability redundancy optimization of general systems. The advanced GA technique uses a dynamic adaptive penalty function to consider the infeasible solutions also and guides the search to optimal or near optimal solution. The penalty technique is applied to keep a certain amount of infeasible solutions in each genera...

For common misfiring fault of automobile engines, this paper presents an algorithm named GA-FNN which is the combination of the genetic algorithm (GA) and the fuzzy neural network (FNN). It calculates the memberships of inputs and initializes the weights and thresholds of the neural network by genetic algorithm firstly, and then trains the network and uses it for diagnosis. Simulation results d...

Extinction has been frequently studied by evolutionary biologists and is shown to play a significant role in evolution. The genetic algorithm (GA), one of popular algorithms, based on key concepts natural evolution such as selection, crossover, mutation. Although GA widely implemented many fields, little work done enhance the performance through extinction. In this research, we propose stagnati...