Slope Stability Prediction Method Based on Intelligent Optimization and Machine Learning Algorithms

Towards Intelligent Machine Learning Algorithms

Comparative Analysis of Machine Learning Algorithms with Optimization Purposes

The field of optimization and machine learning are increasingly interplayed and optimization in different problems leads to the use of machine learning approaches‎. ‎Machine learning algorithms work in reasonable computational time for specific classes of problems and have important role in extracting knowledge from large amount of data‎. ‎In this paper‎, ‎a methodology has been employed to opt...

Fractured Reservoirs History Matching based on Proxy Model and Intelligent Optimization Algorithms

   In this paper, a new robust approach based on Least Square Support Vector Machine (LSSVM) as a proxy model is used for an automatic fractured reservoir history matching. The proxy model is made to model the history match objective function (mismatch values) based on the history data of the field. This model is then used to minimize the objective function through Particle Swarm Optimization (...

Soil and Rock Slope Stability Analysis based on Numerical Manifold Method and Graph Theory

Limit equilibrium method, strength reduction method and Finite Difference Methods are the most prevalently used methods for soil and rock slope stability analysis. However, it can be mention that those have some limitations in practical application. In the Limit equilibrium method, the constitutive model cannot be considered and many assumptions are needed between slices of soil and rock. The s...

Slope Deformation Prediction Based on Support Vector Machine

This paper principally studies the prediction of slope deformation based on Support Vector Machine (SVM). In the prediction process,explore how to reconstruct the phase space. The geological body’s displacement data obtained from chaotic time series are used as SVM’s training samples. Slope displacement caused by multivariable coupling is predicted by means of single variable. Results show that...