Genetic Programming

Bankruptcy 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...

Application of Genetic Programming as a Powerful Tool for Modeling of Cellulose Acetate Membrane Preparation

Bedload 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...

A Method for Solving Optimal Control Problems Using Genetic Programming

This paper deals with a novel method for solving optimal control problems based on genetic programming. This approach produces some trial solutions and seeks the best of them. If the solution cannot be expressed in a closed analytical form then our method produces an approximation with a controlled level of accuracy. Using numerical examples, we will demonstrate how to use the results.

Dimensionality Reduction and Improving the Performance of Automatic Modulation Classification using Genetic Programming (RESEARCH NOTE)

This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. Automatic modulation recognition is one of the essential components of modern receivers. In this regard, selection of suitable features may significantly affect the performance of the process. Simulations were conducted with 5db and 10db SNRs. Test and ...

Modeling 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....