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Article summary:
1. The article presents a shallow sliding failure prediction model of expansive soil slope based on Gaussian process theory and its engineering application.
2. It discusses the use of support vector machines, orthogonal and uniform experimental design, intelligent rock mechanics, system probabilistic stability analysis, variational Bayesian multinomial probit regression with Gaussian process priors, graph generation on slope stability analysis, forecast analysis of monitoring data for high slopes, and artificial neural networks analysis in geotechnical engineering.
3. It also reviews literature related to the prediction of slope stability in expansive soils, surficial stability of compacted clay slopes, strength effective normal stress relationship, permeation of rainwater effects on unsaturated soil slope stability, and landslide nonlinear displacement analysis and prediction with computational intelligence approaches.
Article analysis:
The article is generally reliable and trustworthy as it provides a comprehensive overview of the shallow sliding failure prediction model of expansive soil slope based on Gaussian process theory and its engineering application. The article is well-researched and provides detailed information about the various methods used in geotechnical engineering such as support vector machines, orthogonal and uniform experimental design, intelligent rock mechanics, system probabilistic stability analysis, variational Bayesian multinomial probit regression with Gaussian process priors, graph generation on slope stability analysis, forecast analysis of monitoring data for high slopes, and artificial neural networks analysis. Furthermore, it reviews relevant literature related to the prediction of slope stability in expansive soils as well as surficial stability of compacted clay slopes among other topics.
The article does not appear to have any biases or one-sided reporting as it presents both sides equally by providing an overview of the various methods used in geotechnical engineering as well as reviewing relevant literature related to the topic. Additionally there are no unsupported claims or missing points of consideration as all claims are supported by evidence from relevant sources such as journal articles or books. There is also no promotional content or partiality present in the article which further adds to its trustworthiness and reliability. Finally possible risks are noted throughout the article which further adds to its credibility.