As one of the strategies to mitigate climate change and increase resource use efficiency, there is a need to improve energy recovery and recycling. Then, sector-coupling methods between industries are expected to improve resource recycling efficiency. This study considered the supply of extracted steam from waste treatment plants (WTP) to neighboring factories. We focused on the fact that the company names contained characteristic terms depending on the type of industry. The target factories of the steam supply were classified into industry types by the LSTM method based on the database of company names, and we estimated spatial steam demand using developed models However, they lack of spatial energy demand data could not validate this model result. From this situation, the process database of industries for matching recyclable resources and the list of company names for estimating the location of industries would need to be developed. Therefore, it is necessary to establish a beneficial system to provide data for validation. Based on the knowledge obtained from estimating the location of industries based on the company names and estimating the distribution of industrial steam demand, we developed a database arrangement model system.. In this context, trial consideration of the industrial process with Resource Description Framework (RDF) formatting was conducted to enable the data collection and retrieval of process data through a knowledge base.
Maki et al. (Wed,) studied this question.