Intelligent Logistics Decision System Based on Economic Benefit

Jing Xin Wu

doi:10.4028/www.scientific.net/AMM.644-650.5681

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 644-650Intelligent Logistics Decision System Based on...

Intelligent Logistics Decision System Based on Economic Benefit

Abstract:

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.

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Periodical:

Applied Mechanics and Materials (Volumes 644-650)

Pages:

5681-5684

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.644-650.5681

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Online since:

September 2014

Authors:

Jing Xin Wu*

Keywords:

Data Mining (DM), Decision-Making, Genetic Algorithm (GA), Intelligent Logistics Decision System

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* - Corresponding Author

References

[1] Liu Xiangdong. Data Clustering Algorithm and Software Design Based on Disturbance Searching of Logistic Series[J]. Bulletin of Science and Technology, 2014, 30(2): 161-163.

Google Scholar

[2] GAO Zhichun, CHEN Guanwei, HU Guangbo, et al. Fault Diagnosis and Optimal Data Clustering Based on K-Means with Slope Factor[J]. Computer & Digital Engineering, 2014, 42(1): 14-18.

Google Scholar

[3] Huang Xiaoping, Lin Wen. Intelligent Logistics Code ID Technology Based on Computer Visualization[J]. Logistics Technology, 2013, 32(3): 449-451.

Google Scholar

[4] HUANG Kai- feng, ZHAO Tao. Application of Particle Swarm Optimization Clustering in Network Security[J]. Computer Simulation, 2012, 29(12): 144-147.

Google Scholar

[5] Xing Li. Study on Information Recommendation System Based on Cloud Computation [J]. Logistics Technology, 2013, 32(2): 185-188.

Google Scholar