The initial stress field is very important in rock mechanics. The particle swarm optimization (PSO) algorithm developing in recent years is a stochastic optimization algorithm based on swarm intelligence. By use of the theory of particle swarm optimization (PSO) algorithm, a modified PSO algorithm is proposed for the calculation of the initial stress field. PSO algorithm possesses advantages. Then by use of integrating the advantages of other traditional methods and taking into account the factors affecting the initial stress, the reasonability of the present method is shown by a case study. The intelligent inversion analysis of initial stress field in Xinyuan coal mine is carried out by using the particle swarm (PSO) algorithm. The field results show the method is accurate and high velocity which conforms well to the practical data.


The initial stress field is a never mining-induced natural stress that lies in the strata. Also as we known that the original rock stress, rock initial stress and so on. It is the fundamental forces that caused by mining engineering, civil engineering, water conservancy and hydropower, and various other underground or open-pit rock and soil excavation deformation and destruction. To achieve a scientific design and decision-making in mining and geotechnical engineering excavation, it is a necessary precondition that accurate information on initial stress. It is decided by several tectonic movements, which include the loading and unloading caused by crustal movements, the thermal stress caused by magmatic activity, changes in physical and chemical properties of rock mass and so on. However, it is impossible to solution quantitatively, based on the development history of the earth, the initial stress field for the engineering application. It mainly depend on the measured data, but a few measuring points is hard to meet the needs of construction projects.

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