Search Results - Multi-expression based Gene expression programming

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  1. 1

    Sustainable use of fly-ash: Use of gene-expression programming (GEP) and multi-expression programming (MEP) for forecasting the compressive strength geopolymer concrete by Chu, Hong-Hu, Khan, Mohsin Ali, Javed, Muhammad, Zafar, Adeel, Ijaz Khan, M., Alabduljabbar, Hisham, Qayyum, Sumaira

    ISSN: 2090-4479
    Published: Elsevier B.V 01.12.2021
    Published in Ain Shams Engineering Journal (01.12.2021)
    “… Which has been proficiently used for the manufacture of FA based geopolymer concrete (FGC). To accelerate the usage of FA in building industry, an innovative machine learning techniques namely gene expression programming (GEP…”
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    Journal Article
  2. 2

    Energy consumption predictions by genetic programming methods for PCM integrated building in the tropical savanna climate zone by Nazir, Kashif, Memon, Shazim Ali, Saurbayeva, Assemgul, Ahmad, Abrar

    ISSN: 2352-7102, 2352-7102
    Published: Elsevier Ltd 01.06.2023
    Published in Journal of Building Engineering (01.06.2023)
    “… In this research, multi-expression and genetic expression programming were utilized to anticipate the energy consumption of PCM-integrated buildings by taking early-stage design parameters into consideration…”
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    Journal Article
  3. 3

    Compressive strength of waste-derived cementitious composites using machine learning by Tian, Qiong, Lu, Yijun, Zhou, Ji, Song, Shutong, Yang, Liming, Cheng, Tao, Huang, Jiandong

    ISSN: 1605-8127, 1605-8127
    Published: De Gruyter 15.05.2024
    Published in Reviews on advanced materials science (15.05.2024)
    “…) of MC-based concrete that contained FA and RHA were built. Gene expression programming (GEP…”
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    Journal Article
  4. 4

    Comparative study of genetic programming-based algorithms for predicting the compressive strength of concrete at elevated temperature by Alaskar, Abdulaziz, Alfalah, Ghasan, Althoey, Fadi, Abuhussain, Mohammed Awad, Javed, Muhammad Faisal, Deifalla, Ahmed Farouk, Ghamry, Nivin A.

    ISSN: 2214-5095, 2214-5095
    Published: Elsevier Ltd 01.07.2023
    Published in Case Studies in Construction Materials (01.07.2023)
    “…) and multi-expression programming (MEP) provides the accurate prediction of concrete C-S. This article presents the genetic programming-based models…”
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    Journal Article
  5. 5

    Predicting the compaction characteristics of expansive soils using two genetic programming-based algorithms by Jalal, Fazal E., Xu, Yongfu, Iqbal, Mudassir, Jamhiri, Babak, Javed, Muhammad Faisal

    ISSN: 2214-3912, 2214-3912
    Published: Elsevier Ltd 01.09.2021
    Published in Transportation Geotechnics (01.09.2021)
    “…•Performance comparison of gene expression programming (GEP) and multi expression programming (MEP…”
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    Journal Article
  6. 6

    MERGE: A Novel Evolutionary Algorithm Based on Multi Expression Gene Programming by Shucheng Dai, Changjie Tang, Mingfang Zhu, Yu Chen, Peng Chen, Shaojie Qiao, Chuan Li

    ISBN: 9780769533049, 0769533043
    ISSN: 2157-9555
    Published: IEEE 01.10.2008
    “… To solve the problem, this paper presents a new evolutionary algorithm named multi expression gene programming (MERGE…”
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    Conference Proceeding
  7. 7

    Forecasting Strength of CFRP Confined Concrete Using Multi Expression Programming by Ilyas, Israr, Zafar, Adeel, Javed, Muhammad, Farooq, Furqan, Aslam, Fahid, Musarat, Muhammad, Vatin, Nikolai

    ISSN: 1996-1944, 1996-1944
    Published: Basel MDPI AG 24.11.2021
    Published in Materials (24.11.2021)
    “… “Multi Expression Programming” (MEP) to forecast the compressive strength of carbon fiber-reinforced polymer (CFRP) confined concrete…”
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    Journal Article
  8. 8

    An evolutionary-based predictive soft computing model for the prediction of electricity consumption using multi expression programming by Fallahpour, Alireza, Wong, Kuan Yew, Rajoo, Srithar, Tian, Guangdong

    ISSN: 0959-6526, 1879-1786
    Published: Elsevier Ltd 10.02.2021
    Published in Journal of cleaner production (10.02.2021)
    “…) as a soft computing technique, known as Multi Expression Programming (MEP) to predict the electricity consumption of China for the first time based on the data collected from 1991 to 2019…”
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    Journal Article
  9. 9

    Forecasting Compressive Strength of RHA Based Concrete Using Multi-Expression Programming by Amin, Muhammad Nasir, Khan, Kaffayatullah, Javed, Muhammad Faisal, Ewais, Dina Yehia Zakaria, Qadir, Muhammad Ghulam, Faraz, Muhammad Iftikhar, Alam, Mir Waqas, Alabdullah, Anas Abdulalim, Imran, Muhammad

    ISSN: 1996-1944, 1996-1944
    Published: Switzerland MDPI AG 26.05.2022
    Published in Materials (26.05.2022)
    “… To encourage the re-use of RHA, this work used multi expression programming (MEP) to construct an empirical model for forecasting the compressive nature of concrete made with RHA (CRHA…”
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    Journal Article
  10. 10

    Interpretable prediction of chloride ingress in marine concrete using gene and multi-expression programming by Amin, Muhammad Nasir, Khan, Suleman Ayub, Qadir, Muhammad Tahir, Al-Naghi, Ahmed A. Alawi, Bhatti, Abdul Qadir, Althoey, Fadi, Arifeen, Siyab Ul, Imran, Muhammad

    ISSN: 2214-5095, 2214-5095
    Published: Elsevier Ltd 01.12.2025
    Published in Case Studies in Construction Materials (01.12.2025)
    “… This research applies linear regression and advanced symbolic machine learning methods, specifically Gene Expression Programming (GEP…”
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    Journal Article
  11. 11

    Multi Expression Programming Model for Strength Prediction of Fly-Ash-Treated Alkali-Contaminated Soils by Khan, Kaffayatullah, Ashfaq, Mohammed, Iqbal, Mudassir, Khan, Mohsin Ali, Amin, Muhammad Nasir, Shalabi, Faisal I., Faraz, Muhammad Iftikhar, Jalal, Fazal E.

    ISSN: 1996-1944, 1996-1944
    Published: Switzerland MDPI AG 06.06.2022
    Published in Materials (06.06.2022)
    “…%) on the UCSkaolin and UCSBC soils was also studied. Sufficient laboratory test data comprising 384 data points were collected, and multi expression programming (MEP…”
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    Journal Article
  12. 12

    Development of predictive models for sustainable concrete via genetic programming-based algorithms by Chen, Lingling, Wang, Zhiyuan, Khan, Aftab Ahmad, Khan, Majid, Javed, Muhammad Faisal, Alaskar, Abdulaziz, Eldin, Sayed M.

    ISSN: 2238-7854
    Published: Elsevier B.V 01.05.2023
    “… In the present study, gene expression programming (GEP) and multi-expression programming (MEP) are used to generate predictive models for the split tensile strength (STS…”
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    Journal Article
  13. 13

    Predictive modeling for depth of wear of concrete modified with fly ash: A comparative analysis of genetic programming-based algorithms by Khan, Adil, Khan, Majid, Ali, Mohsin, Khan, Murad, Khan, Asad Ullah, Shakeel, Muhammad, Fawad, Muhammad, Najeh, Taoufik, Gamil, Yaser

    ISSN: 2214-5095, 2214-5095
    Published: Elsevier Ltd 01.07.2024
    Published in Case Studies in Construction Materials (01.07.2024)
    “… Therefore, to avoid costly and laborious tests, this study utilized two machine learning methods, including multi-expression programming (MEP…”
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    Journal Article
  14. 14

    Artificial intelligence-based optimized models for predicting the slump and compressive strength of sustainable alkali-derived concrete by Zou, Baoping, Wang, Yanbing, Nasir Amin, Muhammad, Iftikhar, Bawar, Khan, Kaffayatullah, Ali, Mujahid, Althoey, Fadi

    ISSN: 0950-0618
    Published: Elsevier Ltd 15.12.2023
    Published in Construction & building materials (15.12.2023)
    “…•The sensitivity analysis of the database showed the relevance of input parameters.•The resulting prediction models based on empirical equations agreed well with targets…”
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    Journal Article
  15. 15

    Soft computing models for prediction of bentonite plastic concrete strength by Inqiad, Waleed Bin, Javed, Muhammad Faisal, Onyelowe, Kennedy, Siddique, Muhammad Shahid, Asif, Usama, Alkhattabi, Loai, Aslam, Fahid

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 05.08.2024
    Published in Scientific reports (05.08.2024)
    “…) and gene expression programming (GEP) and a boosting-based algorithm known as AdaBoost to predict the 28-day compressive strength…”
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    Journal Article
  16. 16

    Investigating the feasibility of genetic algorithms in predicting the properties of eco-friendly alkali-based concrete by Jin, Conghe, Qian, Yongjiu, Ayub Khan, Suleman, Ahmad, Waqas, Althoey, Fadi, Saad Alotaibi, Badr, Awad Abuhussain, Mohammed

    ISSN: 0950-0618
    Published: Elsevier Ltd 15.12.2023
    Published in Construction & building materials (15.12.2023)
    “… Gene expression programming (GEP) models and multi-expression programming (MEP) models were developed to predict the rheological…”
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    Journal Article
  17. 17

    Predicting the Oil Well Production Based on Multi Expression Programming by Ma, Xin, Liu, Zhi-bin

    ISSN: 1874-8341, 1874-8341
    Published: 09.03.2016
    Published in The open petroleum engineering journal (09.03.2016)
    “… In this paper the multi expression programming (MEP) method has been employed to build the prediction model for oil well production, combined with the phase space reconstruction technique…”
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    Journal Article
  18. 18
  19. 19

    Performing multi-target regression via gene expression programming-based ensemble models by Moyano, Jose M., Reyes, Oscar, Fardoun, Habib M., Ventura, Sebastián

    ISSN: 0925-2312, 1872-8286
    Published: Elsevier B.V 07.04.2021
    Published in Neurocomputing (Amsterdam) (07.04.2021)
    “…•Three multi-target regression ensemble models with different architectures.•Use gene-expression programming to build each member of the ensemble…”
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    Journal Article
  20. 20

    Interpretable machine learning approaches to assess the compressive strength of metakaolin blended sustainable cement mortar by Khan, Naseer Muhammad, Ma, Liqiang, Inqiad, Waleed Bin, Khan, Muhammad Saud, Iqbal, Imtiaz, Emad, Muhammad Zaka, Alarifi, Saad S.

    ISSN: 2045-2322, 2045-2322
    Published: London Nature Publishing Group UK 03.06.2025
    Published in Scientific reports (03.06.2025)
    “… Thus, this study was conducted to develop reliable empirical prediction models to assess CS of MK-based mortar from its mixture proportion using machine learning algorithms like gene expression programming (GEP…”
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    Journal Article