scholarly journals Implementation of Data Mining Technology in Bonded Warehouse Inbound and Outbound Goods Trade

2022 ◽  
Vol 34 (3) ◽  
pp. 1-18
Yanan Song ◽  
Xiaolong Hua

For the taxed goods, the actual freight is generally determined by multiplying the allocated freight for each KG and actual outgoing weight based on the outgoing order number on the outgoing bill. Considering the conventional logistics is insufficient to cope with the rapid response of e-commerce orders to logistics requirements, this work discussed the implementation of data mining technology in bonded warehouse inbound and outbound goods trade. Specifically, a bonded warehouse decision-making system with data warehouse, conceptual model, online analytical processing system, human-computer interaction module and WEB data sharing platform was developed. The statistical query module can be used to perform statistics and queries on warehousing operations. After the optimization of the whole warehousing business process, it only takes 19.1 hours to get the actual freight, which is nearly one third less than the time before optimization. This study could create a better environment for the development of China's processing trade.

2013 ◽  
Vol 433-435 ◽  
pp. 2424-2428
Xun Wang

The most useful function of data mining technology is extracting valuable information and knowledge from irregular data. This paper briefly described the steps of data mining technology, elaborated logistics intelligent decision-making system components, proposed an improved genetic algorithm, took logistics distribution center location problem as argumentation. Applied data mining technology to logistics smart decisions, it can improve service quality, and establish long-term friendly and cooperative relations with customers.

2014 ◽  
Vol 644-650 ◽  
pp. 5681-5684 ◽  
Jing Xin Wu

The data mining technology has strong function of extracting unknown information and knowledge with potential value from irregular data. The data mining procedures are introduced in this paper, it is applied in the intelligent decision system, and application and the solving steps are analyzed. The composition of intelligent logistics decision system is described. Finally, the simulation is taken, and the genetic algorithm of data mining technology is proposed and it is applied in the intelligent decision-making system of logistics. The simulation results show that the system can be applied in the logistics planning and decision making, the data mining technology can provide guidance for decision layer.

2014 ◽  
Vol 496-500 ◽  
pp. 2108-2111
Jian Hu Zhang ◽  
Lei Lei ◽  
Xin You Cui ◽  
Yong Wu ◽  
Lin Tao Li

Through in-depth understanding of the domain knowledge of insurance and the study of the technology of data warehouse, the paper illustrate the application of data mining technology and data warehouse technology in the insurance clients analysis, and from the basic flow of, discusse the application of data warehouse technology in the field of insurance industry. Then, from the concept of data warehouse, describe the design and implementation of data warehouse concept model and logical model.

Anastasia Y. Nikitaeva

This chapter substantiates the importance of improving management effectiveness of mesoeconomic systems in current economic conditions and the features of mesoeconomy as a management object which defines the high complexity of decision making at the meso level. There are approaches, methods, and technologies which provide support of the decision making process via the integration of formal methods for objective data analysis and methods of accounting to solve semi-structured complex problems of mesoeconomy. A cognitive approach, and an approach involving the integration of the On-Line Analytical Processing and Data mining technologies with methods of a multi-criteria assessment of alternative, in particular methods of Multi-Attribute Utility Theory are considered in the chapter. Cognitive mapping of interaction between state and business in a mesoeconomic system are included as a case-study.

Robab Saadatdoost ◽  
Alex Tze Hiang Sim ◽  
Hosein Jafarkarimi ◽  
Jee Mei Hee

This project presents the patterns and relations between attributes of Iran Higher Education data gained from the use of data mining techniques to discover knowledge and use them in decision making system of IHE. Large dataset of IHE is difficult to analysis and display, since they are significant for decision making in IHE. This study utilized the famous data mining software, Weka and SOM to mine and visualize IHE data. In order to discover worthwhile patterns, we used clustering techniques and visualized the results. The selected dataset includes data of five medical university of Tehran as a small data set and Ministry of Science - Research and Technology's universities as a larger data set. Knowledge discovery and visualization are necessary for analyzing of these datasets. Our analysis reveals some knowledge in higher education aspect related to program of study, degree in each program, learning style, study mode and other IHE attributes. This study helps to IHE to discover knowledge in a visualize way; our results can be focused more by experts in higher education field to assess and evaluate more.

Alysson Bolognesi Prado ◽  
Carmen Freitas ◽  
Thiago Ricardo Sbrici

In the growing challenge of managing people, Human Resources need effective artifacts to support decision making. On Line Analytical Processing is intended to make business information available for managers, and HR departments can now encompass this technology. This paper describes a project in which the authors built a Data Warehouse containing actual Human Resource data. This paper provides data models and shows their use through OLAP software and their presentation to end-users using a web portal. The authors also discuss the progress, and some obstacles of the project, from the IT staff’s viewpoint.

Martin Burgard ◽  
Franca Piazza

The increased use of information technology leads to the generation of huge amounts of data which have to be stored and analyzed by appropriate systems. Data warehouse systems allow the storage of these data in a special multidimensional data base. Based on a data warehouse, business intelligence systems provide different analysis methods such as online analytical processing (OLAP) and data mining to analyze these data. Although these systems are already widely used and the usage is still growing, their application in the area of electronic human resource management (e-HRM) is rather scarce. Therefore, the objective of this article is to depict the components and functionality of these systems and to illustrate the application possibilities and benefits of these systems by selected application examples in the context of e-HRM.

2011 ◽  
Vol 24 (3) ◽  
pp. 45-60
Ben Ali ◽  
Samar Mouakket

E-business domains have been considered killer domains for different data analysis techniques. Most researchers have examined data mining (DM) techniques to analyze the databases behind E-business websites. DM has shown interesting results, but this technique presents some restrictions concerning the content of the database and the level of expertise of the users interpreting the results. In this paper, the authors show that successful and more sophisticated results can be obtained using other analysis techniques, such as Online Analytical Processing (OLAP) and Spatial OLAP (SOLAP). Thus, the authors propose a framework that fuses or integrates OLAP with SOLAP techniques in an E-business domain to perform easier and more user-friendly data analysis (non-spatial and spatial) and improve decision making. In addition, the authors apply the framework to an E-business website related to online job seekers in the United Arab Emirates (UAE). The results can be used effectively by decision makers to make crucial decisions in the job market of the UAE.

Kheri Arionadi Shobirin ◽  
Adi Panca Saputra Iskandar ◽  
Ida Bagus Alit Swamardika

A data warehouse are central repositories of integrated data from one or more disparate sources from operational data in On-Line Transaction Processing (OLTP) system to use in decision making strategy and business intelligent using On-Line Analytical Processing (OLAP) techniques. Data warehouses support OLAP applications by storing and maintaining data in multidimensional format. Multidimensional data models as an integral part of OLAP designed to solve complex query analysis in real time.

2013 ◽  
Vol 846-847 ◽  
pp. 1141-1144
Dan Dan Chen ◽  
Zhi Gang Yao

A comprehensive analysis on a large amount of ship equipment consumption data accumulated over the years is achieved through the establishment of data warehouse, online analytical processing, regression analysis, cluster analysis, etc. by means of data mining. The analysis results present important references for equipment guarantee department in terms of equipment preparation and carrying, etc. and provide the comprehensive analysis and utilization on massive ship maintenance support data with technical means.

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