Reliable method of determining stable threshold channel shape using experimental and gene expression programming techniques

2018 ◽  
Vol 31 (10) ◽  
pp. 5799-5817 ◽  
Author(s):  
Azadeh Gholami ◽  
Hossein Bonakdari ◽  
Mohammad Zeynoddin ◽  
Isa Ebtehaj ◽  
Bahram Gharabaghi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reliable Method ◽  
Gene Expression Programming ◽  
Channel Shape ◽  
Threshold Channel ◽  
Programming Techniques

Sediment transport modeling in open channels using neuro-fuzzy and gene expression programming techniques

2019 ◽  
Vol 79 (12) ◽  
pp. 2318-2327 ◽  
Author(s):  
Katayoun Kargar ◽  
Mir Jafar Sadegh Safari ◽  
Mirali Mohammadi ◽  
Saeed Samadianfard
Keyword(s):  
Gene Expression ◽  
Sediment Transport ◽  
Gene Expression Programming ◽  
Technical Problem ◽  
Deposition Condition ◽  
Regression Equations ◽  
Rigid Boundary ◽  
Channel Characteristics ◽  
Neuro Fuzzy ◽  
Programming Techniques

Abstract Deposition of sediment is a vital economical and technical problem for design of sewers, urban drainage, irrigation channels and, in general, rigid boundary channels. In order to confine continuous sediment deposition, rigid boundary channels are designed based on self-cleansing criteria. Recently, instead of using a single velocity value for design of the self-cleansing channels, more hydraulic parameters such as sediment, fluid, flow and channel characteristics are being utilized. In this study, two techniques of neuro-fuzzy (NF) and gene expression programming (GEP) are implemented for particle Froude number estimation of the non-deposition condition of sediment transport in rigid boundary channels. The models are established based on laboratory experimental data with wide ranges of sediment and pipe sizes. The developed models' performances have been compared with empirical equations based on two statistical factors comprising the root mean square error (RMSE) and the concordance coefficient (CC). Besides, Taylor diagrams are used to test the resemblance between measured and calculated values. The outcomes disclose that NF4, as the precise NF model, performs better than the best GEP model (GEP1) and regression equations. As a conclusion, the obtained results proved the suitable accuracy and applicability of the NF method in estimation.

Gene Expression Programming Evolution Difficulty Prediction Based on Posture Model

2011 ◽  
Vol 22 (5) ◽  
pp. 899-913 ◽  
Author(s):  
Jiao-Ling ZHENG ◽  
Chang-Jie TANG ◽  
Kai-Kuo XU ◽  
Ning YANG ◽  
Lei DUAN ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming

Modeling Self-reported Instrument Data with Gene Expression Programming

2013 ◽  
Vol 45 (6) ◽  
pp. 704-714
Author(s):  
Jinxin QIAN ◽  
Jiayuan YU
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming

Gene expression programming algorithm based on multi-threading evaluator

2013 ◽  
Vol 32 (4) ◽  
pp. 986-989
Author(s):  
Sheng-qiao NI ◽  
Chang-jie TANG ◽  
Ning YANG ◽  
Jie ZUO
Keyword(s):  
Gene Expression ◽  
Gene Expression Programming ◽  
Programming Algorithm
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