In this paper a genetic algorithm (GA) with dualfitness function is proposed and applied to solve the deterministic identical machine scheduling problem. The mating fitness function value was used to determine the mating for chromosomes, while the selection fitness function value was used to determine their survivals. The performance of this algorithm was tested on deterministic identical machi...

Computer network usage increased rapidly at the last decades, the intruders tried to satisfy their needs by many types of attack depending on the intruder objectives, this encourage the researchers to find more and more solutions to detect those attacks. Intrusion Detection System used to detect the attack. Genetic Algorithm used to support IDS. Fitness Function is helpful in chromosome evaluat...

In this paper we present a method of evolving the contrast characteristics of a satellite image by employing a real-coded genetic algorithm with subjective fitness. The contrast properties of an image are given by its contrast-stretching curve, and the task of the Genetic Algorithm is to evolve this curve in order to find the best shape according to some subjective fitness. The subjective fitne...

This work discusses asymptotic convergence of scaled genetic algorithms in a coevolutionary setting where the underlying population contains fixed numbers of creatures of various types. These types of creatures can act on each other in cooperative or competitive manner. The genetic algorithm uses common mutation and crossover operators as well as proportional fitness selection. By a scaled gene...

Software test-case generation is the process of identifying a set of test cases. It is necessary to generate the test sequence that satisfies the testing criteria. For solving this kind of difficult problem there were a lot of research works, which have been done in the past. The length of the test sequence plays an important role in software testing. The length of test sequence decides whether...

Because of the complicated conditions, great deformation, high stress, multi-variables, high non-linearity, the algorithm for structure optimization and its application in tunnel engineering has just been at the right beginning. However, how to make optimized design of structure for tunnel section, reduce excavation and increase support is a very urgent task now. Artificial intelligence shows e...

today, with the advanced statistical techniques and neural networks, predictive models of distribution have been rapidly developed in ecology. purpose of this research is to predict and map the distribution of tetranychus urticae koch (acari: tetranychidae) using mlp neural networks combined with genetic algorithm in surface of farm. population data of pest was obtained in 2016 by sampling in 1...

<p>Route planning is an important part of road network. To select optimized route several factors such as flow traffic, speed limits road. are concerned. Total cost a network depends on the number junctions between source and destination. Due to growth nodes in it becomes tough job determine exact path using deterministic algorithms so cases genetic (GA) plays vital role find route. Cross...

To predict the users navigation using web usage mining is the primary motto of the web page recommendation. Currently, researchers are trying to develop a web page recommendation using pattern mining technique. Here, we propose a technique for web page recommendation using genetic algorithm. It consists of three phases as data preparation, mining of informative rules and recommendation. The dat...

This work examines the use of genetic algorithms and neural networks to generate neural network topologies. The data set consists of digital images of objects taken from different angles. A successful neural network topology had been trained on this data, so it was investigated whether the genetic algorithm could evolve a neural network topology capable of learning the training data. The geneti...