درخت حوزه‌های تخصصی

In customs management, the main problem is balancing the needs of trade facilita-tion as a process of simplifying and accelerating foreign business on the one hand and countering illegal trade, reducing government revenue, capital sleep and the level of controls and interventions on the other. Also, due to the financial crisis in recent years, risk management has been reconsidered, although this attention is related to various financial branches. Since risk analysis and identification is the main component of risk management, developing a suitable model for data analysis is of particular importance. The purpose of this study was to use data data analysis techniques to develop an intelligent model to timely predict the risk of import declarations in customs and thus prevent irreparable losses. In this study, data analysis techniques have been used according to the statistical population which is data-driven. Statistical data were extracted from www.eplonline.ir with 575006 import declarations of all Iranian customs during 2019-2020. having pre-processed and prepared the data using PCA, LDA and FastICA methods, attribute reduction and effective attribute extraction were performed using 14 data analysis algorithms. Using Python software, algorithms were trained and modeled with 80% of the final data. Then, 14 obtained models were tested and validated with 20% of the data. Finally, the results of these models were compared with each other and the model obtained from the random forest algorithm was selected as a comprehensive model for predicting and determining the level of risk of import declarations at customs.

The article investigates in-depth the theoretical provisions for the construction of modern product quality management systems, providing for the optimization and transformation of individual production and economic processes to a higher quality level, as well as the functions integration of enterprise management system and product quality management system; such integration is carried out on the basis of knowledge, information and communications, which are the basis of external integration processes of the enterprise. This provided an opportunity to develop a scientific and methodological approach to the formation of an adaptive quality system capable of producing high quality products over a long period of time. The generalization of practical aspects of the research provided an opportunity to build an algorithm and determine the tools for the formation of an adaptive product quality management system using modern computer technology for effective information support.