This paper concentrates on the optimization of elementary association rule mining. The basic approach mining generates positive but focusing both and negative to find out efficient results is lacking. Thus our aim provide an optimize all rules with help a modified genetic algorithm. A algorithm technique that provides best possible solutions are stronger than other solutions. present focuses im...

The paper considers an approach to genetic optimization of Virtual Local Area Network (VLAN) scheme using the developed software — VLAN scheme design tool. Authors suggest a formal statement of the problem of VLAN scheme optimization, which solution can improve the reliability and security of operation of corporate computer networks. The paper shows that the problem considered is related to one...

this paper presents the hardware simulation (based on vhdl code) of a multiple-fault tolerant cellular genetic algorithm. this study aims to increase the immunity of cellular genetic algorithm in multiple-fault situation. here, multiple-fault refers to the situation that seu (single event upset) occurs simultaneously at two or more bits of the chromosome and fitness registers. the fault model i...

Due to the combinatorial explosions in solution space for scheduling problems, the balance between genetic search and local search is an important issue when designing a memetic algorithm [23] for scheduling problems. The main motivation of this research is to resolve the combinatorial explosion problem by reducing the possible neighborhood combinations using guided operations to remove these i...

This thesis introduces Intelligent Fitness Functions and Partial Fitness Functions both of which can improve the performance of a genetic algorithm which is limited to a fixed run time. An Intelligent Fitness Function is defined as a fitness function with a memory. The memory is used to store information about individuals so that duplicate individuals do not need to have their fitness tested. D...

Tasks scheduling is the most challenging problem in the parallel computing. Hence, the inappropriate scheduling will reduce or even abort the utilization of the true potential of the parallelization. Genetic algorithm (GA) has been successfully applied to solve the scheduling problem. The fitness evaluation is the most time consuming GA operation for the CPU time, which affect the GA performanc...

In the face of more and more faults in coal mine equipment, this paper presents the method of combining genetic algorithm (GA) and BP neural network to predict the failure. According to genetic algorithm has a very slow convergence speed, easy to fall into local optimum, this paper uses chaos and reverse individual learning initialization, followed by the use of differential algorithm to operat...

In this paper, we propose a genetic algorithm, called GenSPN, for finding highly probable differential characteristics of substitution permutation networks (SPNs). A special fitness function and a heuristic mutation operator have been used to improve the overall performance of the algorithm. We report our results of applying GenSPN for finding highly probable differential characteristics of Ser...

This paper provides an introduction to genetic algorithms and genetic programming and lists sources of additional information, including books and conferences as well as e-mail lists and software that is available over the Internet. 1 . GENETIC ALGORITHMS John Holland's pioneering book Adaptation in Natural and Artificial Systems (1975, 1992) showed how the evolutionary process can be applied t...