Link Quality Prediction Based On Gradient Boosting - Shu Jian, Liu Linlan (International Journal of Advanced Science and Technology, 2020)
To predict the consistency of the connections in the Wireless Sensor Network (WSN), which can aid in the selection of links for the upper layer protocol. In this article we proposed a GBM (Gradient Boosting Machine)-based prediction of the relation efficiency. This measures the relation parameters (RSSI, LQI, SNR, and PRR) and trains the model to predict the future value of PRR based on real experimental data. Experimental findings suggest that our proposed LQP-GBM prediction accuracy indicates the efficacy of LQP-GBM as compared to CART AND LDA.