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Optimized ensemble-classification for prediction of soil liquefaction with improved features

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Abstract

The occurrence of soil liquefaction is an interesting and complicated field in the geotechnical earthquake, which has attained the consideration of a lot of analysts in current years. Liquefaction is a process, where the stiffness and strength of soil are minimized by sudden cyclic loading or earthquakes. Liquefaction and associated phenomenon were accountable for the massive quantity of damages during earlier earthquakes around the globe. Here, pre-processing is done with data normalization. Subsequently, the features including “statistical and raw features, higher-order statistical features, and improved entropy and Mutual Information (MI) features” are derived. Further, ensemble classifiers like “Deep Belief Network (DBN), Long Short Term Memory (LSTM), and Recurrent Neural Network (RNN)” are deployed during prediction. Here, the outputs obtained from DBN and LSTM are fused and then given to optimized RNN, which provides the final predicted output. Particularly, the weights of RNN are fine-tuned by Opposition based Self Adaptive SSO (OSA-SSO) model. Eventually, the advantage of the adopted model is proven on diverse metrics. The accuracy of the developed approach was 9.09%, 8.08%, and 10.1% higher than the values obtained for traditional schemes such as EC + SSO, EC + SSA, EC + PRO, and EC + BOA at the 90th LP, respectively.

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  1. Department of Civil engineering, Delhi Technological University, Delhi, India

    Nerusupalli Dinesh Kumar Reddy, Ashok Kumar Gupta & Anil Kumar Sahu

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All authors have made substantial contributions to conception and design, revising the manuscript, and the final approval of the version to be published. Also, all authors agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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Correspondence to Nerusupalli Dinesh Kumar Reddy.

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Reddy, N.D.K., Gupta, A.K. & Sahu, A.K. Optimized ensemble-classification for prediction of soil liquefaction with improved features. Multimed Tools Appl 82, 31467–31486 (2023). https://doi.org/10.1007/s11042-023-14816-0

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