Author:
Reddy Nerusupalli Dinesh Kumar,Gupta Ashok Kumar,Sahu Anil Kumar
Publisher
Springer Nature Singapore
Reference39 articles.
1. Ahmad M, Tang X-W, Qiu J-N (2019a) Evaluating seismic soil liquefaction potential using bayesian belief network and C45 decision tree approaches. Appl Sci (Switzerland) 9(20):4226
2. Ahmad M, Tang XW, Qiu JN, Ahmad F (2019b) Interpretive structural modeling and MICMAC analysis for identifying and benchmarking significant factors of seismic soil liquefaction. Appl Sci (Switzerland) 9(2):233
3. Atangana Njock PG, Shen SL, Zhou A, Lyu HM (2020) Evaluation of soil liquefaction using AI technology incorporating a coupled ENN / t-SNE model. Soil Dynamics and earthquake engineering, vol 130. https://doi.org/10.1016/j.soildyn.2019.105988
4. Bahrami M, Bozorg-Haddad O, Chu X (2018) Cat swarm optimization (CSO) algorithm. In Advanced optimization by nature-inspired algorithms, pp 9–18. Springer, Singapore
5. Belgiu M, Drăguţ L (2016) Random forest in remote sensing: a review of applications and future directions. ISPRS J Photogramm Remote Sens 114:24–31