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.
This paper considers an approach to optimizing hyperparameters of recommendation algorithms using an integral assessment that combines several metrics into four key subindexes: accuracy, ranking, diversity, and resource intensity. This method allows for a more balanced tuning of models, ensuring improved quality of recommendations without loss in individual characteristics. Unlike adjusting for one metric, which can worsen the rest of the parameters, the proposed approach takes into account the mutual dependencies between the metrics. It is shown that different algorithms react differently to
The article presents a research approach to the formation of synthetic data for training neural networks of computer vision systems using the technological process of crushed stone production as an example. The main attention is paid to the problem of scarcity and heterogeneity of real images used in the training of industrial computer vision models. In order to overcome these limitations, a method for generating photorealistic images based on the Unity game engine and the Unity Perception toolkit is proposed. An algorithm for generating pseudorandom objects based on the deformation of the ico
Diabetes is one of the most prevalent chronic diseases, requiring accurate predictive approaches to support diagnosis and clinical decision-making. This study aims to enhance the performance of the Decision Tree (DT) model through hyperparameter optimization using Enhanced Grey Wolf Optimization (EGWO). The proposed method integrates Lévy flight, adaptive exploration–exploitation control, and local search mechanisms to prevent premature convergence and improve solution stability. Experiments were conducted on the Pima Indians Diabetes Dataset (PIDD) using 10-fold cross-validation. The resul
The rapid growth of e-commerce and digital marketing is reshaping traditional supply chain models, prompting shifts in distribution network design, fulfillment strategies, and logistics cost structures. While previous studies have explored digital transformation in isolation, there is limited quantitative evidence on how these changes jointly influence operational performance and cost trade-offs. This study examines the quantitative impact of e-commerce growth and marketing investment on supply chain configuration, fulfillment practices, and key logistics performance metrics, with a focus on i
This study investigates the impact of artificial intelligence (AI)-based teaching media on the literacy and numeracy skills of elementary school students in Enrekang Regency, South Sulawesi, Indonesia. The study employs a design-based research approach and involves 60 fifth-grade students who were divided into an experimental group using AI-supported instruction and a control group using traditional methods. The results show that the experimental group exhibited significant improvements in both literacy and numeracy, with higher gains observed in fluent reading, vocabulary comprehension, numbe