Microarray technology is a powerful tool to monitor gene expression or gene expression changes of hundreds or thousands of genes in a single experiment. Meta-Genetic Programming is the meta learning technique of evolving a genetic programming system to predict cancer classes for better understanding of different types of cancers and to find the possible biomarkers for diseases. A new technique ...

Several efforts to predict student failure rate (SFR) at school accurately still remains a core problem area faced by many in the educational sector. The procedure for forecasting SFR are rigid and most often times require data scaling or conversion into binary form such as is the case of the logistic model which may lead to lose of information and effect size attenuation. Also, the high number...

abstract accurate prediction of river flow is one of the most important factors in surface water recourses management especially during floods and drought periods. in fact deriving a proper method for flow forecasting is an important challenge in water resources management and engineering. although, during recent decades, some black box models based on artificial neural networks (ann), have bee...

Investor decision making has always been affected by two factors: risk and returns. Considering risk, the investor expects an acceptable return on the investment decision horizon. Accordingly, defining goals and constraints for each investor can have unique prioritization. This paper develops several approaches to multi criteria portfolio optimization. The maximization of stock returns, the pow...

This paper develops a first comparative study of multiobjective algorithms in Multiple Instance Learning (MIL) applications. These algorithms use grammar-guided genetic programming, a robust classification paradigm which is able to generate understandable rules that are adapted to work with the MIL framework. The algorithms obtained are based on the most widely used and compared multi-objective...

Evolutionary Programming (EP) seems a promising methodology to automatically find programs to solve new computing challenges. The Evolutionary Programming techniques use classical genetic operators (selection, crossover and mutation) to automatically generate programs targeted to solve computing problems or specifications. Among the methodologies related with Evolutionary Programming we can fin...

Abstract Self-compacting concrete (SCC) is a type of known for its environmental benefits and improved workability. In this study, data-driven approaches were used to anticipate the compressive strength (CS) self-compacting containing recycled plastic aggregates (RPA). A database 400 experimental data sets was assess capabilities multi-objective genetic algorithm evolutionary polynomial regress...

In this paper, the Multi Expression Programming (MEP) technique is used for solving even-parity problems. Numerical experiments show that MEP outperforms Genetic Programming (GP) with more than one order of magnitude for the considered test cases.

In this paper, a Multi-Choice Stochastic Bi-Level Programming Problem (MCSBLPP) is considered where all the parameters of constraints are followed by normal distribution. The cost coefficients of the objective functions are multi-choice types. At first, all the probabilistic constraints are transformed into deterministic constraints using stochastic programming approach. Further, a general tran...