NEURO-BRA: A Bird Removal Approach for Wind Profiler Data Based on Quantum Neural Networks

This paper presents the NEURO-BRA, a neural-network-based bird removal approach for wind profiler data. The NEURO-BRA was developed by training quantum neural networks (QNNs) to identify and remove bird-contaminated data recorded by a 1290-MHz wind profiler using a set of input features computed from the wind profiler measurements. This experimental investigation indicated that the NEURO-BRA was capable of removing over 90% of the bird-contaminated data recorded by the 1290-MHz wind profiler.