Prediction and performance analysis of compression index of multiple‑binder‑treated soil by genetic programming approach

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dc.contributor.authorOnyelowe, Kennedy C.
dc.contributor.authorEbid, Ahmed M.
dc.contributor.authorNwobia, Light
dc.contributor.authorDao‑Phuc, Lam
dc.date.accessioned2022-09-12T13:49:08Z
dc.date.available2022-09-12T13:49:08Z
dc.date.issued2021
dc.description.abstractThe use and its advantage in overcoming time and equipment needs of an evolutionary prediction technique known as the genetic programming have been studied using unsaturated sample of soft soil treated with multiple binders. The soil classified as weak and highly plastic was stabilized and multiple experiments were conducted to measure the effect of the dosages of the treatment on the selected properties. The geotechnics of the exercise showed that the studied parameters substantially improved with increased proportion of hybrid cement (HC) and nanostructured quarry fines (NQF). These measured selected properties were further deployed to predict the compression index of the soil. The prediction operation proposed four-model equation by the degree of importance, sensitivity and influence of the independent parameters. This shows eventually that plasticity index has the greatest sensitivity on the compression behaviour of clay soils. The performance analysis shows that the models have very low error with model trial 4 presented in Eq. 7: CGP C = (IP−Hc⋅NQF) ( part∕ max)NQF (Ip∕wmax) Ln(wmax+3.0) , showing the least error with more consideration for the influence of more of the selected variables. It also exhibited the highest degree of determination. Generally, GP has proven to be flexible, fast and able to predict models for engineering problems for use in design and performance study.en_US
dc.identifier.citationOnyelowe, K. C., Ebid, A. M., Nwobia, L., & Dao-Phuc, L. (2021). Prediction and performance analysis of compression index of multiple-binder-treated soil by genetic programming approach. Nanotechnology for Environmental Engineering, 6(2), 1-17. https://doi.org/10.1007/s41204-021-00123-2en_US
dc.identifier.urihttps://doi.org/10.1007/s41204-021-00123-2
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/4695
dc.language.isoenen_US
dc.publisherNanotechnology for Environmental Engineeringen_US
dc.subjectNanostructured quarry finesen_US
dc.subjectGenetic programming (GP)en_US
dc.subjectPerformance analysis and error analysisen_US
dc.subjectSoft computingen_US
dc.subjectCompression indexen_US
dc.subjectUnsaturated soilen_US
dc.titlePrediction and performance analysis of compression index of multiple‑binder‑treated soil by genetic programming approachen_US
dc.typeArticleen_US
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