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Need for Artificial Intelligence in Geotechnical Earthquake Engineering
This paper reviews the use and necessity of artificial intelligence (AI) in today’s environment of geotechnical earthquake engineering (GEE). As population boom in earthquake sensitive zones the loss of life and property is on the increase. There are an increasing number of populated problematic sites and a limited number of human experts in geotechnical earthquake engineering (GEE). Automated intelligence monitored interpretation, warning and mitigation systems are required. This paper attempts to review knowledge-based system to enable us to put in place an automatic process of interpretation and determining of the risk potential then alerting the stakeholders and initiating mitigation operations. Remote monitoring of slopes movements and deformations, and automated linkage of seismographs together with coordination with state and national disaster relief teams can help in timely warning and damage reduction. Scenarios of modeling, simulation and nonlinear seismic analysis can be applied to damage models for typical of the existing urban infrastructure of India. Data mining techniques, decision trees, Geographical Information Systems and existing open source Software modules can be explored for developing a reliable model for India, incorporating machine learning in GEE. This paper will review some work already done in this area to underline the need for AI in GEE.
Need for Artificial Intelligence in Geotechnical Earthquake Engineering
This paper reviews the use and necessity of artificial intelligence (AI) in today’s environment of geotechnical earthquake engineering (GEE). As population boom in earthquake sensitive zones the loss of life and property is on the increase. There are an increasing number of populated problematic sites and a limited number of human experts in geotechnical earthquake engineering (GEE). Automated intelligence monitored interpretation, warning and mitigation systems are required. This paper attempts to review knowledge-based system to enable us to put in place an automatic process of interpretation and determining of the risk potential then alerting the stakeholders and initiating mitigation operations. Remote monitoring of slopes movements and deformations, and automated linkage of seismographs together with coordination with state and national disaster relief teams can help in timely warning and damage reduction. Scenarios of modeling, simulation and nonlinear seismic analysis can be applied to damage models for typical of the existing urban infrastructure of India. Data mining techniques, decision trees, Geographical Information Systems and existing open source Software modules can be explored for developing a reliable model for India, incorporating machine learning in GEE. This paper will review some work already done in this area to underline the need for AI in GEE.
Need for Artificial Intelligence in Geotechnical Earthquake Engineering
Lecture Notes in Civil Engineering
Sitharam, T. G. (editor) / Kolathayar, Sreevalsa (editor) / Jakka, Ravi (editor) / Souza, Leonardo (author) / Savoikar, Purnanand (author)
2022-01-04
10 pages
Article/Chapter (Book)
Electronic Resource
English
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