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The paper presents the use of genetic programming for forecasting the wire geometry after forming.
The paper is presenting the use of genetic programming to predict the wire geometry after forming.
Model structure estimation is approached through physical understanding of the system and the use of genetic programming methods.
This work proposes the use of genetic programming (GP) for automatic design of a fuzzy expert system aimed to provide the control of axial xenon oscillations in pressurized water reactors (PWRs).
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This paper proposes discovery of knowledge in the form of CPRFHs using island model of genetic programming with two advanced genetic operators, namely; fission and fusion.
In this work, the research about this problem has been made by using the technique of Genetic Programming (GP) for exploring the possible cost functions.
This study presents new models for the prediction of unconfined compressive strength (UCS) of geopolymer stabilized clayey soils using a modified branch of genetic programming, called multi-gen genetic programming (MGGP).
Therefore, the present study focuses on the design of robust models of these parameters for PEMFCs using an optimization approach of genetic programming (GP).
However, AM's success led to the development of genetic programming [56], which is a general method to search function spaces using genetic search [57], and is systematically used in feature generation systems.
The article includes a comprehensive overview of genetic programming and empirical experiments that demonstrate the increased learning rate obtained by using our principled program evolution approach.
This paper investigates the feasibility of using genetic programming (GP) to create an empirical model for the complicated non-linear relationship between various input parameters associated with reinforced concrete (RC) deep beams and their ultimate shear strength.
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