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Formulation of secant and reloading soil deformation moduli using multi expression programming

ENGINEERING COMPUTATIONS 2012年第1-2期29卷 173-197页

作者： Alavi, Amir Hossein Mollahasani, Ali Gandomi, Amir Hossein Bazaz, Jafar Boluori Islamic Azad Univ Mashhad Branch Mashhad Iran Univ Bologna Dept Civil Environm & Mat Engn DICAM Bologna Italy Islamic Azad Univ Cent Tehran Branch Tehran Iran Ferdowsi Univ Mashhad Dept Civil Engn Mashhad Iran

Purpose - The purpose of this paper is to develop new constitutive models to predict the soil deformation moduli using multi expression programming (MEP). The soil deformation parameters formulated are secant (Es) and reloading (Er) moduli. Design/methodology/approach - MEP is a new branch of classical genetic programming. The models obtained using this method are developed upon a series of plate load tests conducted on different soil types. The best models are selected after developing and controlling several models with different combinations of the influencing parameters. The validation of the models is verified using several statistical criteria. For more verification, sensitivity and parametric analyses are carried out. Findings T- he results indicate that the proposed models give precise estimations of the soil deformation moduli. The Es prediction model provides considerably better results than the model developed for Er. The Es formulation outperforms several empirical models found in the literature. The validation phases confirm the efficiency of the models for their general application to the soil moduli estimation. In general, the derived models are suitable for fine-grained soils. Originality/value - These equations may be used by designers to check the general validity of the laboratory and field test results or to control the solutions developed by more in-depth deterministic analyses.

关键词： Soils Deformation Modelling Substructures Soil deformation moduli multi expression programming Plate load test Soil physical properties Prediction

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Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms

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TRANSPORTATION GEOTECHNICS 2021年 30卷

作者： Jalal, Fazal E. Xu, Yongfu Iqbal, Mudassir Jamhiri, Babak Javed, Muhammad Faisal Shanghai Jiao Tong Univ State Key Lab Ocean Engn Dept Civil Engn Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Sch Naval Architecture Ocean & Civil Engn Shanghai Key Lab Digital Maintenance Bldg & Infra Shanghai 200240 Peoples R China COMSATS Univ Islamabad Dept Civil Engn Abbottabad Campus Abbottabad 22060 KP Pakistan

In this study, gene expression programming (GEP) and multi gene expression programming (MEP) are utilized to formulate new prediction models for determining the compaction parameters (rho(dmax) and wopt) of expansive soils. A total of 195 datasets with five input parameters (i.e., clay fraction C-F, plastic limit w(P), plasticity index IP, specific gravity Gs, maximum dry density rho(dmax)), and two output *** and wopt are collected from the literature comprising 119 internationally published research articles to develop the GEP and MEP models. Simplified mathematical expressions were derived for these models to determine the rho(dmax) and w(opt) of expansive soils. The performance of the models was tested using mean absolute error (MAE), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and correlation coefficient (R). Sensitivity and parametric analyses were also performed on the GEP and MEP models. Additionally, external validation of the models was also verified using commonly recognized statistical criteria. It is clear from the results that the GEP and MEP methods accurately characterize the compaction characteristics of expansive soils resulting in reasonable prediction performance, however, GEP model yielded relatively better performance. Also, the proposed predictive models were compared with previously available empirical models and they exhibited robust and superior performance. Moreover, the rho(dmax) model provided significantly improved results as compared to the w(opt) prediction model in the case of GEP, and vice versa in the MEP model. It is therefore recommended that the proposed GP based models can reliably be used for determining the compaction parameters of expansive soils which effectively reduces the time-consuming and laborious testing, hence attaining sustainability in the field of geoenvironmental engineering.

关键词： Expansive soil Gene expression programming multi expression programming Maximum dry density Optimum moisture content

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Improving multi expression programming Using Reuse-Based Evaluation

Improving Multi Expression Programming Using Reuse-Based Eva...

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6th International Symposium on Intelligence Computation and Applications (ISICA 2012)

作者： Deng, Wei He, Pei Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha 410114 Hunan Peoples R China

ISBN: (纸本)9783642342882

multi expression programming is a linear genetic programming that dynamically determines its output from a series of genes of the chromosome. It works on a fixed-length individual, but gives rise to the complexity of the decoding process and fitness computations. To solve this problem, we proposed an improved algorithm that can speed up individual assessments through reuse analysis of evaluations. The experimental result shows that the present approach performs quite well on the considered problems.

关键词： multi expression programming Linear Genetic programming Fitness Computations Reuse Analysis of Evaluations

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Dataset used to develop soft computing models that predict the stiffness modulus of bituminous mixtures

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DATA IN BRIEF 2024年 54卷 110382页

作者： Leon, Lee P. Martin, Hector Rathnayake, Upaka Felix, Portia Univ West Indies Fac Engn Dept Civil & Environm Engn St. Augustine 32080 Trinidad Tobago Univ Belfast Queens Univ Belfast Dept Civil Engn Belfast North Ireland Atlantic Technol Univ Fac Engn & Design Dept Civil Engn & Construct Ash Lane Sligo F91 YW50 Ireland

This data article presents information on the measurement of Indirect Tensile Stiffness Modulus of laboratory and field asphalt mixtures. The asphalt mixes are composed of three distinct binders that were categorised by their penetration grade (40/55-TLA, 60/75-TLA, and 60/70-MB) and aggregates (limestone, sharp sand, and filler). The asphalt mixtures are called dense-graded hot mix asphalt (HMA) and gap-graded stone matrix asphalt (SMA). The variables in the dataset were selected in accordance with the specifications of the dynamic modulus models that are currently in use as well as the needs for the quality control and assurance (QC & QA) assessment of asphalt concrete mixes. The data parameters included are temperature, asphalt content, and binder viscosity, air void content, cumulative percent retained on 19, 12.5, and 4.75 mm sieves, maximum theoretical specific gravity, aggregate passing #200 sieve, effective asphalt content, density, flow, marshal stability, coarse-to-fine particle ratio and the Indirect Tensile Stiffness Modulus (ITSM). Utilising soft computing techniques, models were developed utilising the data thus eliminating the requirement for complex and timeconsuming laboratory testing.

关键词： Asphalt concrete Gene expression programming Pavement design Indirect tensile stiffness modulus multi expression programming Pavement materials

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Formulation of uplift capacity of suction caissons using multi expression programming

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KSCE JOURNAL OF CIVIL ENGINEERING 2011年第2期15卷 363-373页

作者： Gandomi, Amir Hossein Alavi, Amir Hossein Yun, Gun Jin Univ Akron Dept Civil Engn Akron OH 44325 USA Tafresh Univ Dept Civil Engineeing Tafresh 19395 Markazi Iran Iran Univ Sci & Technol Sch Civil Engn Tehran 16846 Iran

Suction caissons have increasingly been used as foundations and anchors for deepwater offshore structures in the last decade. The increased use of suction caissons defines a serious need to develop more authentic methods for simulating their behavior. Reliable assessment of uplift capacity of caissons in cohesive soils is a critical issue facing design engineers. This paper proposes a new approach for the formulation of the uplift capacity of suction caissons using a promising variant of Genetic programming (GP), namely multi expression programming (MEP). The proposed model is developed based on experimental results obtained from the literature. The derived MEP-based formula takes into account the effect of aspect ratio of caisson, shear strength of clayey soil, point of application and angle of inclination of loading, soil permeability and loading rate. A subsequent parametric analysis is carried out and the trends of the results are confirmed via previous studies. The results indicate that the MEP formulation can predict the uplift capacity of suction caissons with an acceptable level of accuracy. The proposed formula provides a prediction performance better than or comparable with the models found in the literature. The MEP-based simplified formulation is particularly valuable for providing an analysis tool accessible to practicing engineers.

关键词： suction caissons uplift capacity multi expression programming formulation

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New design equations for elastic modulus of concrete usingmulti expression programming

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JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT 2015年第6期21卷 761-774页

作者： Gandomi, Amir H. Faramarzifar, Ali Ghanad Rezaee, Peyman Asghari, Abazar Talatahari, Siamak Univ Akron Dept Civil Engn Akron OH 44325 USA Islamic Azad Univ Qeshm Int Branch Dept Architectural Engn Qeshm Iran Inst Higher Educ Eqbal Lahoori Dept Architectural Engn Mashhad Iran Urmia Univ Technol Dept Civil Engn Orumiyeh Iran Tabriz Univ Dept Civil Engn Tabriz Iran

An innovative multi expression programming (MEP) approach is used to derive new predictive equations for tangent elastic modulus of normal strength concrete (NSC) and high strength concrete (HSC). Similar to several building codes, the modulus of elasticity of NSC and HSC is formulated in terms of concrete compressive strength. Furthermore, a generic model is developed for the estimation of the elastic modulus of both NSC and HSC. Comprehensive databases are gathered from the literature to develop the models. For more verification, a parametric analysis is carried out and discussed. The proposed formulas are found to be accurate for the prediction of the elastic modulus of NSC and HSC. The predictions made by the MEP-based models are more accurate than those obtained by the existing models.

关键词： formulation compressive strength multi expression programming tangent elastic modulus normal and high strength concrete

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multi expression programming: a new approach to formulation of soil classification

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ENGINEERING WITH COMPUTERS 2010年第2期26卷 111-118页

作者： Alavi, Amir Hossein Gandomi, Amir Hossein Sahab, Mohammad Ghasem Gandomi, Mostafa Natl Elites Fdn Highest Prestige Sci & Profess Natl Fdn Tehran Iran Iran Univ Sci & Technol Coll Civil Engn Tehran Iran Tafresh Univ Coll Civil Engn Tafresh Iran Univ Tehran Coll Engn Sch Civil Engn Tehran Iran

This paper presents an alternative approach to formulation of soil classification by means of a promising variant of genetic programming (GP), namely multi expression programming (MEP). Properties of soil, namely plastic limit, liquid limit, color of soil, percentages of gravel, sand, and fine-grained particles are used as input variables to predict the classification of soils. The models are developed using a reliable database obtained from the previously published literature. The results demonstrate that the MEP-based formulas are able to predict the target values to high degree of accuracy. The MEP-based formulation results are found to be more accurate compared with numerical and analytical results obtained by other researchers.

关键词： multi expression programming Soil classification Formulation

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multi-expression Based Gene expression programming

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Chinese Intelligent Automation Conference (CIAC)

作者： Deng, Wei He, Pei Huang, Zhi Changsha Univ Sci & Technol Sch Comp & Commun Engn Changsha 410114 Hunan Peoples R China Guilin Univ Elect Technol Guangxi Key Lab Trusted Software Guilin 541004 Peoples R China

ISBN: (纸本)9783642384660;9783642384653

Among the variants of GP, GEP stands out for its simplicity of encoding method and MEP catches our attention for its multi-expression capability. In this paper, a novel GP variant-MGEP (multi-expression based Gene expression programming) is proposed to combine these two approaches. The new method preserves the GEP structure, however unlike the traditional GEP, its genes, like those of MEP, can be disassembled into many expressions. Therefore in MGEP, the traditional GEP gene can contain multiple solutions for a problem. The experimental result shows the MGEP is more effective than the traditional GEP and MEP in solving problems.

关键词： Genetic programming Gene expression programming multi expression programming

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Inference of Differential Equation Models by multi expression programming for Gene Regulatory Networks

Inference of Differential Equation Models by Multi Expressio...

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5th International Conference on Intelligent Computing

作者： Yang, Bin Chen, Yuehui Meng, Qingfang Univ Jinan Computat Intelligence Lab Sch Informat Sci & Engn Jinan 250022 Peoples R China

ISBN: (纸本)9783642040191

This paper presents an evolutionary method for identifying the gene regulatory network from the observed time series data of gene expression using a system of ordinary differential equations (ODEs) as a model of network. The structure of ODE is inferred by the multi expression programming (MEP) and the ODE's parameters are optimized by using particle swarm optimization (PSO). The proposed method can acquire the best structure of the ODE only by a small population, and also by partitioning the search space of system of ODEs can be reduced significantly. The effectiveness and accuracy of the proposed method are demonstrated by using synthesis data from the artificial genetic networks.

关键词： Evolutionary method multi expression programming ordinary differential equations particle swarm optimization artificial genetic networks

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multi-expression Based Gene expression programming

Multi-Expression Based Gene Expression Programming

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2013年中国智能自动化学术会议

作者： Wei Deng Pei He Zhi Huang School of Computer and Communication Engineering Changsha University of Science and Technology Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology

Among the variants of GP,GEP stands out for its simplicity of encoding method and MEP catches our attention for its multi-expression *** this paper,a novel GP variant-MGEP(multi-expression based Gene expression programming) is proposed to combine these two *** new method preserves the GEP structure,however unlike the traditional GEP,its genes,like those of MEP,can be disassembled into many *** in MGEP,the traditional GEP gene can contain multiple solutions for a *** experimental result shows the MGEP is more effective than the traditional GEP and MEP in solving problems.

关键词： Genetic programming Gene expression programming multi expression programming

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