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A study of slope stability prediction using least square support vector machine

Samui P.

International Journal of Applied Mechanics and Engineering

2012

Vol. 17, no. 1

279-287

The determination of stability of slope is an important task in geological engineering practice. This paper proposes the use of the least square support vector machine (LSSVM) for the determination of stability of slope. The LSSVM is a statistical learning method which has a self-contained basis of statistical-learning theory and excellent learning performance. The five input variables used for the LSSVM model in this study are the unit weight (d), cohesion (c), angle of internal friction, slope angle, height (H) and pore water pressure coefficient (ru). The LSVM model also gives a probabilistic output. This study shows that the LSSVM model is a robust tool for slope stability analysis.

A distributed implementation of parallel genetic algorithm for slope stability evaluation

Srokosz P. E., Tran Ch.

Computer Assisted Mechanics and Engineering Sciences

2010

Vol. 17, no. 1

13-26

Parallel processing, the method of considering many small tasks to solve one large problem, has emerged as a key enabling technology in modern computing. Parallel computers can be simply classified into shared memory systems and distributed memory systems. The shared memory computers have a global memory attached to a number of processors enabling several processors to work concurrently on different parts of the same computation. A different approach towards building large parallel computers is to connect several processors via a network. Each processor has its own local memory. The cost of building these computers increases with the number of processors. The distributed memory multiprocessor systems are scalable over a wider range than the shared memory computers. There are many intermediate computer architectures, each with its distinct programming model. Common between them is the notion of message passing. In all parallel processing, data must be exchanged between cooperating tasks. Several research groups have developed software packages such as Parallel Virtual Machine (PVM), theMessage Passing Interface (MPI), and others. In this paper, hardware implementation of parallel information processing is introduced by application of a multicellular computer idea, in which working cells were composed of general purpose one-chip microcomputers. The influence of the cellular computer's structure size on quality and efficiency of calculations was analyzed. The optimal structure consisted of 4x4 cells which guaranteed achieving satisfactory recurrence of results for an assumed set of working parameters. This paper presents an idea and the results of trial computations regarding the problem of slope stability evaluation by variational calculus assisted by genetic algorithm.