Neural network approach to forecast the state of the Internet of Things elements
Igor Vitalievich Kotenko, Igor Borisovich Saenko, Fadey Skorik, Sergey Valentinovich Bushuev · 2015
The paper presents the method to forecast the states of elements of the Internet of Things based on using an artificial neural network. The offered architecture of the neural network is a combination of a multilayered perceptron and a probabilistic neural network. For this reason, it provides high efficiency of decision-making. Results of an experimental assessment of the offered neural network on the accuracy of forecasting the states of elements of the Internet of Things are discussed.