Introduction to Genetic Programming
نویسنده
چکیده
Genetic Programming (GP) is a method to evolve computer programs. And the reason we would want to try this is because, as anyone who’s done even half a programming course would know, computer programming is hard. Automatic programming has been the goal of computer scientists for a number of decades. Scientists would like to be able to give the computer a problem and ask the computer to build a program to solve it. Genetic programming, it has been said, shows the most potential as a way to automatically write computer programs. So there is an amount of hope for GP’s role in future computing, but what use is it now? Most research focuses on how we could improve the GP process, however there are commercially available genetic programming kernels that allow people to apply the technique. This paper will look at the basics of genetic programming: theory and examples.
منابع مشابه
A genetic algorithm for a bi-objective mathematical model for dynamic virtual cell formation problem
Nowadays, with the increasing pressure of the competitive business environment and demand for diverse products, manufacturers are force to seek for solutions that reduce production costs and rise product quality. Cellular manufacturing system (CMS), as a means to this end, has been a point of attraction to both researchers and practitioners. Limitations of cell formation problem (CFP), as one o...
متن کاملBedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming
Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...
متن کاملBankruptcy Prediction: Dynamic Geometric Genetic Programming (DGGP) Approach
In this paper, a new Dynamic Geometric Genetic Programming (DGGP) technique is applied to empirical analysis of financial ratios and bankruptcy prediction. Financial ratios are indeed desirable for prediction of corporate bankruptcy and identification of firms’ impending failure for investors, creditors, borrowing firms, and governments. By the time, several methods have been attempted in...
متن کاملApplication of Genetic Programming to Modeling and Prediction of Activity Coefficient Ratio of Electrolytes in Aqueous Electrolyte Solution Containing Amino Acids
Genetic programming (GP) is one of the computer algorithms in the family of evolutionary-computational methods, which have been shown to provide reliable solutions to complex optimization problems. The genetic programming under discussion in this work relies on tree-like building blocks, and thus supports process modeling with varying structure. In this paper the systems containing amino ac...
متن کاملBedload transport predictions based on field measurement data by combination of artificial neural network and genetic programming
Bedload transport is an essential component of river dynamics and estimation of its rate is important to many aspects of river management. In this study, measured bedload by Helley- Smith sampler was used to estimate the bedload transport of Kurau River in Malaysia. An artificial neural network, genetic programming and a combination of genetic programming and a neural network were used to estim...
متن کاملModeling Ghotour-Chai River’s Rainfall-Runoff process by Genetic Programming
Considering the importance of water and computing the amount of rainfall runoff resulted from precipitation in recent decades, using appropriate methods for predicting the amount of runoff from rainfall date has been really essential. Rainfall-runoff models are used to estimate runoff generated from precipitation in the catchment area. Rainfall-runoff process is totally a non-linear phenomenon....
متن کامل