基于量子自组织网络的预测模型

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

This paper presents a novel predictive model based on quantum self-organization networks (QSONs). The model leverages quantum graph theory and self-organization network principles to predict system states and behaviors. We propose a framework where the inherent properties of quantum states facilitate the prediction process, offering a significant advancement over traditional predictive methods. The core mechanism involves constructing a quantum self-organizing network that evolves through quantum states, enabling the model to discern patterns and anticipate future states. This approach promises enhanced accuracy and robustness in predicting complex systems. This work contributes to the field of quantum machine learning and provides a foundation for future research exploring the potential of quantum systems in predictive modeling.

DOI: 10.5281/zenodo.22224156

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