In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and the plasticity index of the soil.
Receipt date: 8/8/2020 acceptance date: 9/11/2020 Publication date: 31/12/2021
This work is licensed under a Creative Commons Attribution 4.0 International License.
The American-Iranian relations have been characterized by tensions since the arrival of the guardian jurist regime in Iran to leadership in 1979, as it was considered a turning point not only in the cont
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The role of the public sector- Investment customizations- economic embargo - The role of the private sector - Coexistence between the public and private sectors - Ratio of growth
Abstract:
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