摘要：Studying the piled raft behavior has been the subject of many types of research in the field of geotechnical *** studies have been conducted to understand the behavior of these types of foundations,which are often used for uniform loading on the raft and piles with the same length,while generally the transition load from the upper structure to the foundation is non-uniform and the choice of uniform length for piles in the above model will not be optimally economic and *** most common method in identifying the behavior of piled rafts is the use of theoretical relationships and software *** precise identification of this type of foundation behavior can be very difficult due to several influential parameters and interaction of set behavior,and it will be done by doing time-consuming computer analyses or costly full-scale physical *** the meantime,the technique of artificial neural networks can be used to achieve this goal with minimum time consumption,in which data from physical and numerical modeling can be used for network *** of the advantages of this method is the speed and simplicity of using *** this paper,a model is presented based on multi-layer perceptron artificial neural *** this model pile diameter,pile length,and pile spacing is considered as an input parameter that can be used to estimate maximum settlement,maximum differential settlement,and maximum raft *** this model,we can create an extensive domain of results for optimum system selection in the desired piled raft *** of neural network indicate its proper ability in identifying the piled raft *** presented procedure provides an interesting solution and economically enhancing the design of the piled raft foundation *** innovative design method reduces the time spent on software analyses.