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Advances in Intelligent Systems and Computing
In this paper, a neural network-based procedure is suggested to produce estimated solutions (controllers) for the second-order nonlinear partial differential equations (PDEs). This concept is laid down so as to produce a prevalent approximation on the basis of the learning method which is at par with quasi-Newton rule. The proposed neural network contains the regularizing parameters (weights and biases), that can be utilized for making the error function least. Besides, an advanced technique isdoi:10.1007/978-3-319-97982-3_5 fatcat:3lnvpo6oabeupaoifyhrzuwxuy