The diversity an‎d expansion of data have increased significantly in the early second decade of the twentieth century. Fifth an‎d sixth generation cellular networks are rapidly expan‎ding from Asia to Africa, an‎d for this reason, the growth of the Internet of Things (IoT) has also been provided [1]. IoT has gradually opened its place in most applications. This technology has gradually become important in agriculture [2], industry[3], smart factories [4], military technologies [5], an‎d healthcare [6]. However, there are still challenges in its expansion. Aside from the discussion of network attacks, in IoT, the problem of missing data can disrupt the network efficiency process. Important factors such as signal interference, environmental noise, sensor failure, memory an‎d battery limitations of sensors ... can all lead to the loss of some data [7].

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General Regression Neural Network Approach Towards Missing Data Recovery Between IoT Systems