Optimizing E-commerce Logistics with ARIMA-BP Neural Networks and GA: A Multi-Objective Approach for Emergency Response and Network Efficiency-Reference-Cited by-同舟云学术

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Optimizing E-commerce Logistics with ARIMA-BP Neural Networks and GA: A Multi-Objective Approach for Emergency Response and Network Efficiency

Published:2024-05-10 Issue: Volume: Page:150-155
ISSN:
Container-title:Proceedings of the 2024 International Conference on Generative Artificial Intelligence and Information Security
language:
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Author:

Wang Zhihao¹^ORCID,Guo Xiaoyue²^ORCID,Li Hanzi¹^ORCID,Xu Yuting¹^ORCID,Qin Meng¹^ORCID,Liu Jianbo¹^ORCID,Zhu Haoliang¹^ORCID,Chen Tianjie¹^ORCID

Affiliation:

1. Chongqing University of Posts and Telecommunications, China

2. Anhui University of Finance and Economics, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3665348.3665375

Reference13 articles.

1. A network traffic forecasting method based on SA optimized ARIMA–BP neural network

2. Research on Container Throughput Forecast Based on ARIMA-BP Neural Network

3. Multiobjective Optimization for Planning the Service Areas of Smart Parcel Locker Facilities in Logistics Last Mile Delivery

4. A short-term load forecasting model of natural gas based on optimized genetic algorithm and improved BP neural network

5. An Optimal BP Neural Network Track Prediction Method Based on a GA–ACO Hybrid Algorithm

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