in this study, the performance of an irreversible regenerative brayton cycle is sought through power maximizations using finite-time thermodynamic concept in finite-size components. optimizations are performed using a genetic algorithm. in order to take into account the finite-time and finite-size concepts in the current problem, a dimensionless mass-flow rate parameter is used to deploy time v...

A common practice is to design a controller by plant observations (i.e. experiments) and to optimize some of its parameters by trial-and-error. This paper proposes a genetic algorithm for the automation of the search procedure and its implementation on a programmable logic controller. The details of this implementation will be discussed along with an example one carried out for the control of a...

A modified genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. Under suitable hypotheses, the estimation error is shown to converge in probability to zero. The scheme is also applied to feedforward and recurrent neural networks.

This paper concerns the use of genetic algorithms for line labelling. We are interested in finding an optimal set of algorithm control parameters for this problem. We give results from using a simple genetic algorithm to solve several line labelling problems and discuss the effects of crossover type, population size, crossover rate, mutation rate and iteration limit on algorithm performance. We...

Evolutionary computing techniques were used to understand and model the time series observations of environmental parameters recorded by buoys on the ocean surface. The environmental parameters such as sea surface temperature, air temperature and surface wave height etc. are important in understanding the ocean characteristics and any suitable model that can forecast or predict the trend to any...

Genetic Algorithms are a class of powerful, robust search techniques based on genetic inheritance and the Darwinian metaphor of “Natural Selection”. These algorithms maintain a finite memory of individual points on the search landscape known as the “population”. Members of the population are usually represented as strings written over some fixed alphabet, each of which has a scalar value attach...