Tracing the technological trajectory of coal slurry pipeline transportation technology: An HMM-based topic modeling approach

Coal slurry pipeline transportation is an important way to realize green coal logistics. However, there are still challenges in understanding the cognitive aspects of technology development trajectory. This study attempts trace and predict trend from patent texts through stochastic process analysis topic evolution. It helps understand technology. And capture trends characteristics improve research (R&D) efficiency sustainability. As a result, this extracts potential topics text by using Latent Dirichlet Distribution method. Then, Word2vec-based word vector model applied calculate cosine similarity between topics. HMM-based evolution constructed introducing Hidden Markov Model (HMM) which can portray dual process. Finally, it used analyze technological field. was found that advancement related pulping fundamental promoting technology, also common topic. technologies capacity enhancement industrial application will be focus future R&D field with broad prospects. intended provide directions for sustainable activities facilitate interdisciplinary discussions, objective data decisions making scientists managers