Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) is a monthly peer-reviewed scopus indexed journal originally founded in 1986. It is sponsored by the Ministry of Education, china and Northeastern University, china. Kongzhi yu Juece/Control and Decision (ISSN:1001-0920) has always adhered to the correct purpose of running the journal, and has been committed to gathering and disseminating excellent academic achievements, inspiring technological innovation, and promoting the development of disciplines in my country.Aiming at major national needs and international frontiers, this journal has published a large number of original and high-level research result. The journal was selected into the "China Science and Technology Journal Excellence Action Plan Project" in December 2019.In the future, it will strive to build an open innovation, collaborative integration.
In the modern manufacturing environment, the production systems develop towards a flexible direction due to the increasing of the market demands of multiple varieties and small batch-based customized products. In order to make better use of existing resources and improve production efficiency, real-time performance evaluation and prediction of real-time scheduling and optimization improvement based on small batch production have important research significance in distributed flexible production systems. This paper mainly studies the performance analysis of multi-batch serial production line
The dynamic optimization of the closed-loop supply chain (CLSC) is a hot research topic. Members’ competitive behavior and product goodwill play an important role in the decision making of CLSC members. In this paper, a closed-loop supply chain (CLSC) with competitive manufacturers and single retailers is studied, in which the manufacturer produces and recycles the products, and the retailer is responsible for the sales of the products. On this basis, a dynamic linear differential equation of product goodwill is constructed, the optimal dynamic path of each decision variable is found,
By analyzing the mechanism relationship between the input angular velocity and the output position of the engraving machine system in speed control mode, the system is simulated as a model connected by an integrating factor and a stable transfer function. By introducing a differential filter to process the sampling data, the critical unstable integrating model is transformed into a stable model which is easy to identify. This paper proposes a recursive least squares algorithm which can accurately estimate the model with integrating factor. Besides, the instrumental variables method is appli
Tunnel linings require routine inspection as they have a big impact on a tunnel’s safety and longevity. In this study, the convolutional neural network was utilized to develop the MFF-YOLO model. To improve feature learning efficiency, a multi-scale feature fusion network was constructed within the neck network. Additionally, a reweighted screening method was devised at the prediction stage to address the problem of duplicate detection frames. Moreover, the loss function was adjusted to maximize the effectiveness of model training and improve its overall performance. The results show
The mobile node location method can find unknown nodes in real time and capture the movement trajectory of unknown nodes in time, which has attracted more and more attention from researchers. Due to their advantages of simplicity and efficiency, intelligent optimization algorithms are receiving increasing attention. Compared with other algorithms, the black hole algorithm has fewer parameters and a simple structure, which is more suitable for node location in wireless sensor networks. To address the problems of weak merit-seeking ability and slow convergence of the black hole algorithm, thi