a sensor network is made up of a large number of sensors with limited energy. sensors collect environmental data then send them to the sink. energy efficiency and thereby increasing the lifetime of sensor networks is important. direct transfer of the data from each node to the central station will increase energy consumption. previous research has shown that the organization of nodes in cluster...

Apparent shear stress acting on a vertical interface between the main channel and floodplain in a compound channel serves to quantify the momentum transfer between sub sections of this cross section. In this study, three soft computing methods are used to simulate apparent shear stress in prismatic compound channels. The Genetic Algorithm Artificial neural network (GAA), Genetic Programming (GP...

In the field of robotics, before the conception of any approach to solve robot path planning, it would be the procedure to derive a model for the problem and solution theoretically, then going for simulations to verify the derived model and then implemented and validated in the real time applications, by taking into account many real time factors. This survey studies the evolution of implementa...

in this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (anfsga) controlsystem is proposed for a ph neutralization system. in ph reactors, determination and control of ph isa common problem concerning chemical-based industrial processes due to the non-linearity observedin the titration curve. an anfsga control system is designed to overcome the complexity of precisecontrol o...

In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier’s fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier’s fitness is given by a measure of the prediction’s accuracy. The system executes the genetic algorithm in ni...

Skepticism of the building block hypothesis (BBH) has previously been expressed on account of the weak theoretical foundations of this hypothesis and the anomalies in the empirical record of the simple genetic algorithm. In this paper we hone in on a more fundamental cause for skepticism—the extraordinary strength of some of the assumptions that undergird the BBH. Specifically, we focus on assu...

In many classifier systems, the classifier strength parameter serves as a predictor of future payoff and as the classifier’s fitness for the genetic algorithm. We investigate a classifier system, XCS, in which each classifier maintains a prediction of expected payoff, but the classifier’s fitness is given by a measure of the prediction’s accuracy. The system executes the genetic algorithm in ni...

This paper presents a novel genetic algorithm approach for network design with a robust fitness function which finds the best least distance network for any number of nodes. A network design problem for this paper falls under the network topology category which is a minimum spanning tree. Since many researchers have tried to solve this problem for small to mid size, we have explored the use of ...

We first revisit a problem in the literature of genetic algorithms: arranging numbers into groups whose summed weights are as nearly equal as possible. We provide a new genetic algorithm which very aggressively breeds new individuals which should be improved groupings of the numbers. Our results improve upon those in the literature. Then we extend and generalize our algorithm to a related class...

Process discovery techniques automatically extract the real workflow of a process by analyzing the events that are collected and stored in log files. Although in the last years several process discovery algorithms have been presented, none of them guarantees to find complete, precise and simple models for all the given logs. In this paper we address the problem of process discovery through a ge...