Aiming at the problem of node location in Wireless Sensor Network(WSNs), Unmanned Aerial Vehicle-assisted localization algorithm based on Feedforward Neural Network(UAV-NN) is proposed. The localization is performed by using mobile Unmanned Aerial Vehicles(UAVs) as the anchor nodes to send the beacon signals every period of time, thus every unknown node can estimate its current position based on the Received Signal Strength Indicator(RSSI) values of the received beacon signals by training the Single hidden-Layer Feedforward Neural Network(SLFN) using Extreme Learning Machine(ELM) technique. The proposed method requires fewer anchor nodes and no ground anchor node compared to traditional RSSI based localization technique to yield better accuracy. Simulation results show that this technique is capable of performing real-time localization for unknown nodes with less localization error by using ELM compared to other traditional machine learning algorithms.