论文标题
使用神经细胞自动机预测地理信息
Predicting Geographic Information with Neural Cellular Automata
论文作者
论文摘要
本文使用神经细胞自动机（NCA）提出了一个新型框架，以再生并预测地理信息。该模型扩展了使用NCA通过使用各种地理数据训练模型来生成/重新生成特定图像的想法，从而以交通状况映射为例，该模型能够通过提供某些感应信息来预测流量条件。我们的研究验证了生物学中NCA和基因之间的类比，而模型的创新显着扩大了基于NCA的应用的边界。从我们的实验结果中，该模型在其可用性和多功能性方面具有巨大的潜力，这在先前的研究中没有可用。用于模型实现的代码可在https：//已编辑中获得。
This paper presents a novel framework using neural cellular automata (NCA) to regenerate and predict geographic information. The model extends the idea of using NCA to generate/regenerate a specific image by training the model with various geographic data, and thus, taking the traffic condition map as an example, the model is able to predict traffic conditions by giving certain induction information. Our research verified the analogy between NCA and gene in biology, while the innovation of the model significantly widens the boundary of possible applications based on NCAs. From our experimental results, the model shows great potentials in its usability and versatility which are not available in previous studies. The code for model implementation is available at https://redacted.
