In the current paper we present the application of our Gene Expression Programming Environment in forecasting Euro-United States Dollar exchange rate. Specifically, using the GEP Environment we tried to forecast the value of the exchange rate using its previous values. The data for the EUROUSD exchange rate are online available from the European Central Bank (ECB). The environment was developed...

The CERCHAR abrasivity test is very popular for determination of rock abrasivity. An accurate estimation of the CERCHAR abrasivity index (CAI) is useful for excavation operation costs. This paper presents a model to calculate CAI based on the gene expression programming (GEP) approach. This model is trained and tested based on a database collected from the experimental results available in the ...

This paper introduces the technologies to improve the performance of function mining by Gene Expression Programming (GEP) developed in Sichuan University last year. The main results include: (a) Genetic Modifying Algorithm (Trans-gene). By injection gene segment into genome, it guides the evolutional direction and speeds up knowledge discovery process. (b) Overlapped gene expression. Borrowing ...

The problem of complex network clustering has been long studied and a satisfactory solution is still lack so far. By cohesion superiority of Gene Expression Programming and the information-theoretic topology compression framework, a novel algorithm, CNC-GEP, is proposed for complex network clustering. With no prior knowledge of the number of modules in networks, CNC-GEP not only determines the ...

Different techniques are used to model the relationship between temperatures, dew point and relative humidity. Gene expression programming is capable of modelling complex realities with great accuracy, allowing at the same time, the extraction of knowledge from the evolved models compared to other learning algorithms. We aim to use Gene Expression Programming for modelling of dew point. General...

Gene Expression Programming (GEP) is a powerful evolutionary method derived from Genetic Programming (GP) for model learning and knowledge discovery. However, when dealing with complex problems, its genotype under Karva notation does not allow hierarchical composition of the solution, which impairs the efficiency of the algorithm. We propose a new representation scheme based on prefix notation ...

Gene expression programming (GEP) is frequently used to create intelligent dispatching rules for job-shop scheduling. The proper selection of the terminal set a critical factor success GEP. However, there are various job features and machine that can be included in sets capture different characteristics state. Moreover, importance varies greatly between scenarios. irrelevant redundant may lead ...

Gene Expression Programming (GEP) is a new evolutionary algorithm that incorporates both the idea of simple, linear chromosome of fixed length used in Genetic Algorithms (GAs) and the ramified structure of different sizes and shapes used in Genetic Programming (GP). Same as other genetic programming algorithms, GEP has difficulty finding appropriate numeric constants for terminal nodes in the e...