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Developing robust structure: multi-expression programming for anticipating mechanical properties of shape memory alloy-confined concrete cylinders

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STRUCTURAL CONCRETE 2025年

作者： Eilbeigi, Saeed Tavakkolizadeh, Mohammadreza Masoodi, Amir R. Ferdowsi Univ Mashhad Dept Civil Engn Mashhad Iran

This study emphasizes the expansion of novel relationships to determine maximum compressive stress, corresponding strain, ultimate stress, and strain in order to enhance the precision and practicality of predicting the behavior of SMA-confined concrete (SMACC) with spirals. It develops predictive equations for the mechanical properties of SMACC cylinders using the multi-expression programming (MEP) method. The MEPX software is employed to derive optimal relationships by collecting experimental data from 42 concrete cylindrical specimens subjected to uniaxial compression and confined with SMA spirals. The findings show that the developed MEP-based relationships not only provide practical equations, but also produce more precise results.

关键词： active concrete confinement axial stress and strain mechanical properties multi-expression programming shape memory alloy

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multi-expression programming based model for prediction of formation enthalpies of nitro-energetic materials

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EXPERT SYSTEMS 2013年第1期30卷 66-78页

作者： Bagheri, Mehdi Gandomi, Amir Hossein Bagheri, Mehrdad Shahbaznezhad, Mohcen Islamic Azad Univ Sci & Res Branch Tehran Iran Islamic Azad Univ Cent Tehran Branch Tehran Iran NIOC ICOFC Dept Engn Tehran Iran

There has been considerable interest in predicting the properties of nitro-energetic materials to improve their performance. Not to mention insightful physical knowledge, computational-aided molecular studies can expedite the synthesis of novel energetic materials through cost reduction labours and risky experimental tests. In this paper, quantitative structureproperty relationship based on multi-expression programming employed to correlate the formation enthalpies of frequently used nitro-energetic materials with their molecular properties. The simple yet accurate obtained model is able to correlate the formation enthalpies of nitro-energetic materials to their molecular structure with the accuracy comparable to experimental precision.

关键词： nitro-energetic materials multi-expression programming formation enthalpy QSPR

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MEPAR-miner:: multi-expression programming for classification rule mining

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2007年第2期183卷 767-784页

作者： Baykasoglu, Adil Ozbakir, Lale Gaziantep Univ Dept Ind Engn TR-27310 Gaziantep Turkey Erciyes Univ Dept Ind Engn Kayseri Turkey

Classification and rule induction are two important tasks to extract knowledge from data. In rule induction, the representation of knowledge is defined as IF-THEN rules which are easily understandable and applicable by problem-domain experts. In this paper, a new chromosome representation and solution technique based on multi-expression programming (MEP) which is named as MEPAR-miner (multi-expression programming for Association Rule Mining) for rule induction is proposed. multi-expression programming (MEP) is a relatively new technique in evolutionary programming that is first introduced in 2002 by Oltean and Dumitrescu. MEP uses linear chromosome structure. In MEP, multiple logical expressions which have different sizes are used to represent different logical rules. MEP expressions can be encoded and implemented in a flexible and efficient manner. MEP is generally applied to prediction problems;in this paper a new algorithm is presented which enables MEP to discover classification rules. The performance of the developed algorithm is tested oil nine publicly available binary and n-ary classification data sets. Extensive experiments are performed to demonstrate that MEPAR-miner can discover effective classification rules that are as good as (or better than) the ones obtained by the traditional rule induction methods. It is also shown that effective gene encoding structure directly improves the predictive accuracy of logical IF-THEN rules. (c) 2006 Elsevier B.V. All rights reserved.

关键词： data mining classification rules multi-expression programming evolutionary programming

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Prediction of stiffness modulus of bituminous mixtures using the applications of multi-expression programming and gene expression programming

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ROAD MATERIALS AND PAVEMENT DESIGN 2023年第9期24卷 2192-2208页

作者： Leon, Lee P. Azamathulla, Hazi Felix, Portia Prasad, C. Venkata Siva Rama Univ West Indies Dept Civil & Environm Engn St Augustine Trinidad Tobago Vignana Bharathi Inst Technol Dept Civil Engn Hyderabad India

An essential factor in the design and in situ performance of asphalt concrete pavements is its elastic-stiffness properties. The objective of the present study, is to develop empirical equations to estimate indirect tensile stiffness modulus (ITSM) of bituminous mixture using the soft computing techniques of multi expression programming (MEP) and gene expression programming (GEP). The soft computing models were developed using experimental data points containing laboratory and field blended dense-graded hot mix asphalt (HMA) and gap-graded stone matrix asphalt (SMA) mixtures including three asphalt binders. The dominant parameters covered mix physical and volumetric properties, test temperatures, and the mix variables needed during quality control and assurance assessments. The soft computing models could successfully estimate the stiffness modulus with notable values of R values between 0.835 and 0.944. The GEP equations estimated the elastic stiffness modulus with a higher rate of accuracy when compared to the MEP, non-linear and linear regression estimates.

关键词： Asphalt concrete gene expression programming HMA indirect tensile stiffness modulus multi-expression programming SMA

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multi-objective breast cancer classification by using multi-expression programming

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APPLIED INTELLIGENCE 2015年第3期43卷 499-511页

作者： Diosan, Laura Andreica, Anca Univ Babes Bolyai Dept Comp Sci R-3400 Cluj Napoca Romania

Despite many years of research, breast cancer detection is still a difficult, but very important problem to be solved. An automatic diagnosis system could establish whether a mammography presents tumours or belongs to a healthy patient and could offer, in this way, a second opinion to a radiologist that tries to establish a diagnosis. We therefore propose a system that could contribute to lowering both the costs and the work of an imaging diagnosis centre of breast cancer and in addition to increase the trust level in that diagnosis. We present a multi-objective evolutionary approach based on multi-expression programming-a linear Genetic programming method-that could classify a mammogram starting from a raw image of the breast. The processed images are represented through Histogram of Oriented Gradients and Kernel Descriptors since these image features have been reported as being very efficient in the image recognition scientific community and they have not been applied to mammograms before. Numerical experiments are performed on freely available datasets consisting of normal and abnormal film-based and digital mammograms and show the efficiency of the proposed decision support system.

关键词： multi-objective optimization Genetic programming multi-expression programming Breast cancer

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Crack width prediction of self-healing engineered cementitious composite using multi-expression programming

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JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T 2023年 24卷 918-927页

作者： Althoey, Fadi Sor, Nadhim Hamah Hadidi, Haitham M. Shah, Syed Farasat Ali Alaskar, Abdulaziz Eldin, Sayed M. Bashir, Tariq Javed, Muhammad Faisal Najran Univ Coll Engn Dept Civil Engn Najran Saudi Arabia Univ Garmian Civil Engn Dept Kalar 46021 Kurdistan Reg Iraq Jazan Univ Coll Engn Dept Mech Engn POB 706 Jazan 45142 Saudi Arabia Iqra Natl Univ Dept Civil Engn Peshawar 25000 Pakistan King Saud Univ Coll Engn Dept Civil Engn Riyadh 11451 Saudi Arabia Future Univ Egypt Fac Engn Ctr Res New Cairo 11835 Egypt CECOS Univ Dept Civil Engn Peshawar 25000 Pakistan COMSATS Univ Islamabad Dept Civil Engn Abbottabad Campus Abbottabad 22060 Pakistan

Concrete structures are prone to cracking due to environmental damage and/or tensile strain. Self-healing concrete has garnered scientific interest in recent years as it addresses the cracking problem and extends the service life of concrete structures. Engineered cementitious composite (ECC), a high-performance fiber-reinforced cement composite, is known to have some self-healing characteristics. However, the self-healing capability of ECC is characterized by the type and content of input parameters and is difficult to predict. This investigation utilised a multi-expression programming algorithm for the prediction of self-healing characteristics of ECC containing various admixtures. The database, containing 619 points, was extracted from literature containing crack width before self-healing (CB), limestone powder (LP), silica fume (SF), and fly ash (FA) as input parameters and crack width after self-healing as an output parameter. The performance of the developed model was evaluated based on various statistical indices and parametric analysis. The results showed that the developed model is robust and efficient in predicting the selfhealing behavior of ECC containing various admixtures. Parametric and sensitivity analysis revealed that among the admixtures used, fly ash had the least impact and limestone powder had the highest impact on the self-healing capacity of ECC.(C) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC

关键词： Engineering cementitious composites Self-healing multi-expression programming Parametric analysis

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Performance evaluation of concrete made with plastic waste using multi-expression programming

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MATERIALS TODAY COMMUNICATIONS 2024年 39卷

作者： Asif, Usama Javed, Muhammad Faisal Alyami, Mana Hammad, Ahmed W. A. Nazarbayev Univ Dept Civil Engn Astana Kazakhstan Ghulam Ishaq Khan Inst Engn Sci & Technol Dept Civil Engn Topi Pakistan Najran Univ Coll Engn Dept Civil Engn Najran Saudi Arabia Macroview Projects Sydney Australia

The immense production of plastic waste due to its non-biodegradable nature has become a major issue for the world. Several researchers have recently tried to incorporate plastic waste in building materials, particularly as a substitute for cement in concrete, using conventional experimental testing. However, it is difficult to examine the optimal mix design in experimental investigations due to time and resource constraints. Therefore, this study aims to provide robust multi-expression programming (MEP) based predictive equations to evaluate the compressive strength (CS) and tensile strength (TS) of concrete containing plastic waste. Based on the literature, a comprehensive data record of 276 and 235 samples of the CS and TS of plastic concrete was generated for model development. The models ' prediction capabilities were assessed by evaluating the various statistical indicators and comparing the results with a multi -linear regression (MLR) model. Furthermore, a sensitivity analysis was conducted to find out the contribution of each parameter to the CS and TS of plastic concrete. According to the statistical findings, the MEP model demonstrated higher efficacy in prediction, with an R 2 value of 0.87 and 0.89 for the CS and TS models. In addition, MEP generates a simple mathematical formula, which can be employed as a design tool for estimating the CS and TS of plastic concrete. In sensitivity analysis, age demonstrated the highest sensitivity (24.8% and 31%), demonstrating its substantial impact on the model ' s outputs. Cement (17.63% and 17.3%) and plastic (17.4% and 15.3%) have similar contributions to the CS and TS. These results are consistent with previous research, highlighting the agreement between the results of this study and the literature. Therefore, this study can be employed for sustainable construction practices.

关键词： Plastic concrete multi-expression programming Compressive strength Tensile strength Sensitivity analysis

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Development of applicable design models for concrete columns confined with aramid fiber reinforced polymer using multi-expression programming

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STRUCTURES 2020年 23卷 225-244页

作者： Arabshahi, Alireza Gharaei-Moghaddam, Nima Tavakkolizadeh, Mohammadreza Ferdowsi Univ Mashhad Sch Engn Civil Engn Dept Mashhad Razavi Khorasan Iran

In this paper, a new series of applicable relations, including maximum confined stress and strain as well as the stress-strain relationship, for AFRP confined concrete are proposed based on the design-oriented approach. The main advantages of these new relations are their higher accuracy and unified nature for both circular and square cross sections as well as their ability to predict stress and strain of partially confined columns. For this purpose, a complete database of the available experimental results from the previous studies is collected. In order to achieve higher accuracy and reliability, only part of the collected experimental results that passes a series of deliberately considered criteria are used for derivation of the relations. In addition to the mentioned relations, a threshold for confinement pressure is defined which can be used as a beneficial tool by designers to specify sufficiency of their designed AFRP confinement. Furthermore, a simple relation to predict lateral hoop rupture strain of AFRP wraps is also provided. In order to make the suggested models utilizable for the cases that fibers are not placed perpendicular to the column axis, simple modification factors are also derived. The proposed models are formulated using an evolutionary algorithm named multi-expression programming (MEP), which is an approach for predicting models in the cases of unknown mathematical structures. Accuracy of the proposed relations is compared with the other available models based on the collected experimental database. The obtained results showed that the suggested relations and especially the stress-strain model are capable to predict behavior of AFRP confined concretes with remarkable accuracy.

关键词： Effective confinement threshold Unified Design-oriented model multi-expression programming Stress-Strain curve Partial confinement AFRP

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Application of multi-expression programming (MEP) in predicting the soaked California bearing ratio (CBR) value of fine-grained soil

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INNOVATIVE INFRASTRUCTURE SOLUTIONS 2022年第4期7卷 1-16页

作者： Verma, Gaurav Kumar, Brind Banaras Hindu Univ Indian Inst Technol Dept Civil Engn Varanasi 221005 Uttar Pradesh India

This study is attempted to develop the prediction model for the soaked California bearing ratio (CBR) value of fine-grained soil through the multi-expression programming (MEP) approach. The modeling phase was performed on 1011 in situ collected soil samples from an ongoing highway construction project work site. Based on the literature recommendations and present study database analysis, six relevant input parameters were extracted from numerous geotechnical parameters achieved through laboratory experiments. Using those parameters, several tentative combinations were prepared to develop the most efficient predictive model. The comparative results of all the models demonstrate the higher accuracy with PL, PI, S, FC, MDD and OMC as input parameters. The developed model with the adopted input parameters is able to explain 63% variability in the soaked CBR value of fine-grained soil. Almost 97% of total observations were found to be predicted within +/- 20% variations. Additionally, the sensitivity analysis reveals that the soaked CBR value is prominently influenced by the MDD followed by FC, PL, S, PI and OMC. The validation results of the model exhibit that the developed model is also worthy in predicting the soaked CBR value of the unseen dataset. Eventually, a graphical user interface was generated for the future convenience of the researchers and site engineers.

关键词： multi-expression programming Genetic programming California bearing ratio Maximum dry density Optimum moisture content Graphical user interface

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Sustainable utilization of foundry waste: Forecasting mechanical properties of foundry sand based concrete using multi-expression programming

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SCIENCE OF THE TOTAL ENVIRONMENT 2021年 780卷 146524-146524页

作者： Iqbal, Muhammad Farjad Javed, Muhammad Faisal Rauf, Momina Azim, Iftikhar Ashraf, Muhammad Yang, Jian Liu, Qing-feng Shanghai Jiao Tong Univ Sch Naval Architecture Ocean & Civil Engn State Key Lab Ocean Engn Shanghai 200240 Peoples R China GIK Inst Engn Sci & Technol Dept Civil Engn Topi 23460 Swabi Pakistan COMSATS Univ Islamabad Dept Civil Engn Abbottabad Campus Islamabad Pakistan NUST Mil Coll Engn Risalpur 24080 Pakistan

Waste Foundry sand (WFS), a major solid waste from metal casting industry, is posing a significant environmental threat owing to its disposal to landfills. In this research, an innovative artificial intelligence technique i.e. multi-expression programming (MEP) is applied to model the split tensile strength (ST) and modulus of elasticity (E) of concrete containing waste foundry sand (CWFS). The presented formulations correlate mechanical properties with four input variables i.e. w/c, foundry sand content, superplasticizer content and compressive strength. The results of statistical analysis validate the model accuracy as evident by the low values of objective function (0.033 for E and 0.052 for ST). Moreover, the average error in the predicted values is significantly low i.e. 0.287 MPa and 1.75 GPa for ST and E model, respectively. Parametric study depicts that the models are well trained to accurately predict the trends of mechanical properties with variation in mix parameters. The prediction models can promote the usage of WFS in green concrete thereby preventing waste disposal and contributing towards and sustainable construction. (c) 2021 Elsevier B.V. All rights reserved.

关键词： Foundry sand Solid waste multi-expression programming Parametric analysis Sustainable construction

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