Abstract
With the deepening of globalization, cross-border industrial e-commerce has increasingly become a mainstream means of trade exchanges, however, with the continuous increase in business volume. How to accurately estimate the procurement volume of cross-border materials is a significant issue, which plays a vital role in quantifying economic efficiency. To this end, this study proposes a financial decision-making algorithm for cross-border industrial e-commerce material procurement based on the Markov chain. The algorithm first preprocesses the original logistics data, including data cleaning, missing data filling, and noisy data removal, represents the data as structured panel data, finally builds a Markov chain model based on the panel data, and then makes predictions on the new data. We verified the effectiveness of the proposed model on a simulated dataset and an actual dataset.
Highlights
In recent years, my country’s foreign trade has faced severe internal and external environments
To solve the problem of low efficiency in the existing cross-border industrial e-commerce logistics, this study proposes a Markov chain-based cross-border industrial e-commerce material purchase economic decision algorithm. e algorithm first preprocesses the original logistics data, including data cleaning, data missing filling, and noisy data removal, represents the data as structured panel data, builds a Markov chain model based on the panel data, and makes predictions on the new data
(2) e algorithm first preprocesses the original logistics data, including data cleaning, data missing filling, and noisy data removal, represents the data as structured panel data, builds a Markov chain model based on the panel data, and makes predictions on the new data
Summary
My country’s foreign trade has faced severe internal and external environments. (1) Accurately estimating the procurement volume of cross-border materials is a critical issue, which plays a vital role in quantifying economic efficiency To this end, this study proposes a financial decisionmaking algorithm for cross-border industrial e-commerce material procurement based on the Markov chain. (2) e algorithm first preprocesses the original logistics data, including data cleaning, data missing filling, and noisy data removal, represents the data as structured panel data, builds a Markov chain model based on the panel data, and makes predictions on the new data (3) We verified the effectiveness of the proposed model on a simulated dataset and an actual dataset e remainder of this study is organized as follows.
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