Accurately and continuously monitoring the hot metal temperature status of the blast furnace (BF) is a challenging job. To solve this problem, we propose a hot metal temperature prediction model based on the AdaBoost integrated algorithm using the real production data of the BF. We cleaned the raw data using the data analysis technology combined with metallurgical process theory, which mainly included data integration, outliers elimination, and missing value supplement. The redundant features were removed based on Pearson’s thermodynamic diagram analysis, and the input parameters of the model were preliminarily determined by using recursive feature elimination method. We built the hot metal temperature prediction model using the AdaBoost ensemble algorithm on a dataset with selected features as well as derived features by using K-mean clustering tags. The results show that the performance of the hot metal temperature prediction model with K-means clustering tags has been further improved, and the accurate monitoring and forecast of molten iron temperature has been achieved. The model can achieve an accuracy of more than 90% with an error of ±5°C.

With the rise of live streaming commerce, the relationship between consumers and content creators on the short-video platforms has become closer, forming a peculiar culture and language in each consumer community, which promotes the short-video platforms to become a natural breeding ground for forming consumer communities. While such communities give birth to its own language and culture from the interaction between content creators and consumers, this kind of co-creation can not only enhance the consumers’ trust to improve commodity premium space, but also strengthen the ties within the community and spread the information outside the communities, and consequently, expand community scale. Based on the view of the value co-creation from the language and culture among content creators and consumers in the communities, this study starts from the point of product type, employs consumers’ Willingness to pay premium (WoPP) as a proxy variable of brand advocacy in the co-creation of cultural and language values in consumer communities, and conducts three single-factor experiments between two groups. By analyzing the experimental results, this study identified the influence under the potential relationship mechanism, social comparison, and found another variable that can moderate the relationship, consumer trust, portrays the relationship between the product types of the live streaming commerce and the consumers’ WoPP, and explores the mediating effect of social comparison and the moderate effect of consumer trust effect. This paper also analyzes and discusses the WoPP caused by the co-creation of cultural and language values co-created by creators and consumer communities.

Permanent magnet synchronous motor (PMSM) driving stable platform directly is often used in guided rockets. Due to the extended state observe (ESO) contained in the active disturbance rejection controller (ADRC), it can estimate the speed of the rotated carrier and the uncertain disturbances accurately without requiring exact mathematic model of system. An active disturbance rejection controller based on single axis stable platform is designed and optimized. The simulation results show that the system using the simplified ADRC has such characters as high robustness, high accurate and quickness.

No abstract

No abstract