Amirkabir University of Technology Amirkabir Journal of Civil Engineering 2588-297X 50 4 2018 10 23 Determining Impending Slip of Slop and Optimized Embankment Operation Volume of Earth Dams Using a Combination of Neural Networks and Genetic Algorithms (GA) Determining Impending Slip of Slop and Optimized Embankment Operation Volume of Earth Dams Using a Combination of Neural Networks and Genetic Algorithms (GA) 747 754 1955 10.22060/ceej.2017.11051.4965 FA H.R. Saba Tafresh University, Tafresh, Iran 0000-0001-9331-185X M. Kamalian Geotechnical Engineering Research Center, International Institute of Earthquake Engineering and Seismology I. Raeisizadeh Afarinesh institution of higher education, Borujerd, Iran Journal Article 2015 10 21 In this study, impending slip of slope and optimized embankment operation volume of earth dams have been determined using optimization benefiting from a combination of neural networks and genetic algorithms (GA). Further, coefficient of slope stability of earth dam have been determined using neural network and has been compared with outputs of finite element software PLAXIS. In order to training the neural network from derivative data, 150 models of earth dams have been used in finite element software PLAXIS. <br />Slope stability analysis has been done in order to determining the safety factor at desired sliding surface and the most probable fracture process and the least related safety factor. The determination of the most probable fracture process at the impending slip (determining the least safety factor) is the genetic algorithm application. Moreover, another application of genetic algorithm in this research is optimizing the embankment operation volume of earth dam in the manner that minimum of safety factor derived. In this research analysis has been done in order to simpler use of proposed dimensions for engineers using various properties of soil in embankment of earth dam for different heights. Results have been shown as figures and tables which optimal dimensions and volume of the dam without using the software can be derived from them. In this study, impending slip of slope and optimized embankment operation volume of earth dams have been determined using optimization benefiting from a combination of neural networks and genetic algorithms (GA). Further, coefficient of slope stability of earth dam have been determined using neural network and has been compared with outputs of finite element software PLAXIS. In order to training the neural network from derivative data, 150 models of earth dams have been used in finite element software PLAXIS. <br />Slope stability analysis has been done in order to determining the safety factor at desired sliding surface and the most probable fracture process and the least related safety factor. The determination of the most probable fracture process at the impending slip (determining the least safety factor) is the genetic algorithm application. Moreover, another application of genetic algorithm in this research is optimizing the embankment operation volume of earth dam in the manner that minimum of safety factor derived. In this research analysis has been done in order to simpler use of proposed dimensions for engineers using various properties of soil in embankment of earth dam for different heights. Results have been shown as figures and tables which optimal dimensions and volume of the dam without using the software can be derived from them. https://ceej.aut.ac.ir/article_1955_378a063b8fdb1db941e34f4bde584c7d.pdf