Research on Evaluation of Intelligent Manufacturing Capability and Layout Superiority of Supply Chain by Big Data Analysis

With the rise of cloud computing, big data and Internet of Things technology, intelligent manufacturing is leading the transformation of manufacturing mode and industrial upgrading of manufacturing industry, becoming the commanding point of a new round of global manufacturing competition. Based on the literature review of intelligent manufacturing and intelligent supply chain, a total factor production cost model for intelligent manufacturing and its formal expression are proposed. Based on the analysis of the model, 12 first-level indicators and 29 second-level indicators of production line, workshop/factory, enterprise and enterprise collaboration are proposed to evaluate the intelligent manufacturing capability of supply chain. This article also further studies the layout superiority and spatial agglomeration characteristics of intelligent manufacturing supply chain, providing useful reference and support for enterprises and policy makers in the decision-making.

Research on Evaluation Model of Hospital Informatization Level Based on Decision Tree Algorithm

In order to improve the weight calculation accuracy of hospital informatization level evaluation and shorten the evaluation time, a research method of hospital informatization level evaluation model based on the decision tree algorithm is proposed. Using the decision tree algorithm combining fuzzy theory and ID3, the decision tree is constructed to analyze the hospital information data. By means of questionnaire survey, expert experience, mathematical statistics, and in-depth interview, information facilities construction, information resources construction, information scientific research application, management information, and information guarantee are selected as the nodes of the decision tree to evaluate the hospital information level. Construct the structural equation model, standardize the data, extract the weight of each evaluation index, and complete the evaluation of hospital informatization level. The experimental results show that the weight calculation results of this method are basically consistent with the actual results, and the evaluation efficiency is improved.

Research on Evaluation of Green Smart Building Based on Improved AHP-FCE Method

With the accelerated pace of urbanization, green buildings and green smart buildings gradually come into people’s vision and are highly valued by all sectors of society on the premise of meeting sustainable development strategy. Firstly, this paper selects 7 first-level index factors and 20 second-level index factors to establish the green smart building evaluation system. Secondly, this paper uses the analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE) method to determine the weight of each secondary index. Finally, the feasibility of the evaluation system is verified by case analysis, and some suggestions on green smart building are put forward.