Artificial neural networks are a tool for modeling of nonlinear systems in various engineering fields. These networks are effective tools for modeling the nonlinear systems. Each artificial neural network includes an input layer, an output layer between which there are one or some hidden layers. In each layer, there are one or several processing elements or neurons. The neurons of the input layer are independent variables of the understudy issue, and the neurons of the output layer are its dependent variables. Artificial neural system, through exerting weight on inputs and by suing an activation function attempts to achieve a desirable output. In this research, in order to calculate the drain spacing in an unsteady state in a region situated in the north east of Ahwaz, Iran with different soil properties and drain spacing, the artificial neural networks have been used. The neurons in the input layer were: Specific yield, hydraulic conductivity, depth of the impermeable layer, height of the water table in the middle of the interval between the drains in two-time steps. The neurons in output layer were drain spacing. The network designed in this research was included a hidden layer with four neurons. The distance of drains computed via this method had a good agreement with real values and had a high precision in compare with other methods.

人工神经网络是在各种工程领域中对非线性系统进行建模的工具。这些网络是建模非线性系统的有效工具。每个人工神经网络都包括一个输入层，一个输出层，在它们之间存在一个或一些隐藏层。在每一层中，都有一个或几个处理元件或神经元。输入层的神经元是研究不足问题的独立变量，输出层的神经元是其因变量。人工神经系统通过在输入上施加权重并使用激活函数来尝试获得理想的输出。在这项研究中，为了计算位于伊朗阿瓦士东北部一个具有不同土壤性质和排水间距的区域中的非稳态排水间距，人工神经网络已被使用。输入层中的神经元为：比产率，水力传导率，不可渗透层的深度，两次排水之间的排水沟中间的地下水位高度。输出层中的神经元是漏极间距。在这项研究中设计的网络包括具有四个神经元的隐藏层。通过该方法计算出的排水距离与实际值有很好的一致性，与其他方法相比具有很高的精度。在这项研究中设计的网络包括具有四个神经元的隐藏层。通过该方法计算出的排水距离与实际值有很好的一致性，与其他方法相比具有很高的精度。在这项研究中设计的网络包括具有四个神经元的隐藏层。通过该方法计算出的排水距离与实际值有很好的一致性，与其他方法相比具有很高的精度。