Quantum Classical Ridgelet Neural Network For Time Series Model
This addresses forecasting accuracy for financial analysts, but it appears incremental as it combines existing ridgelet and quantum methods.
The study tackled time series forecasting by integrating ridgelet transforms with quantum computing, resulting in a model that demonstrated superior performance on financial data compared to existing models.
In this study, we present a quantum computing method that incorporates ridglet transforms into the quantum processing pipelines for time series data. Here, the Ridgelet neural network is integrated with a single-qubit quantum computing method, which improves feature extraction and forecasting capabilities. Furthermore, experimental results using financial time series data demonstrate the superior performance of our model compared to existing models.