Application of soft computing and statistical methods to predict rock mass permeability

Author:

Alizadeh S. M.,Iraji Amin

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Reference140 articles.

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2. Adegbite JO, Belhaj H, Bera A (2021) Investigations on the relationship among the porosity, permeability and pore throat size of transition zone samples in carbonate reservoirs using multiple regression analysis, artificial neural network and adaptive neuro-fuzzy interface system. Pet Res 6(4):321–332

3. Akbarimehr D, Aflaki E (2019) Site investigation and use of artificial neural networks to predict rock permeability at the Siazakh Dam, Iran. Q J Eng Geol 52(2):230–239

4. Al-Anazi AF, Gates ID (2012) Support vector regression to predict porosity and permeability: effect of sample size. Comput Geosci 39:64–76

5. Al-Masaeed S, Alshareef HN, Johar MGM, Ab Yajid MS, Abdeljaber O, Khatibi A (2021) A study on educational research of artificial neural networks in the Jordanian Perspective Abstract. Euras J Educ Res 96(96):281–301

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