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AI-Enhanced Traffic Flow Monitoring Algorithm Model for Highway Logistics Transportation Vehicles Based on ETC Gantry Marking Technology
(2026-01-14)
Zheng, Zhong
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He, Wanxian
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Wei, Ganglan
Facing the challenges of real-time and accuracy in traffic monitoring technology. This article proposes a traffic flow monitoring algorithm model for highway logistics vehicles and all types of vehicles based on ETC gantry recognition technology. By constructing a gantry road network direction map, real-time driving record table, and anomaly detection algorithm, vehicle path tracking, traffic statistics, and abnormal behavior recognition are achieved. This model fully utilizes the data collection capability of the existing ETC gantry system, combined with the shortest path algorithm and spatiotemporal relationship analysis, to explore the feasibility of this model in real-time traffic monitoring, and is expected to provide a low-cost reference solution for intelligent highway management.
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Intelligent Database Feature Mining Method Based on Genetic Clustering Algorithm
(2026-01-14)
Gao, Lu
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Zheng, Zhong
The intelligent database feature mining method relies on preset thresholds, resulting in the omission of key features and affecting classification performance. Therefore, research on intelligent database feature mining methods based on genetic clustering algorithm. Firstly, a balanced processing method is adopted for the data in the database to preserve key information. Then, set the autocorrelation function and combine it with the data hierarchy and attribute integration relationship to accurately extract useful features from the database. Finally, the genetic clustering algorithm is applied to iteratively classify database features, and the clustering results are continuously optimized by combining genetic algorithm and K-means clustering algorithm to obtain the optimal or approximately optimal clustering scheme. The experimental results show that our method outperforms the three compared methods in terms of classification accuracy and execution efficiency, providing an efficient and reliable solution for feature mining of large-scale data.
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Exploring the Impact of Digital Platform on Energy-Efficient Consumption Behavior: A Multi-Group Analysis of Air Conditioning Purchase in China Using the Extended TPB Model
(2025-06-01)
Zheng, Zhong
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Srinuan, Chalita
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Rojniruttikul, Nuttawut
Energy-efficient consumption has become a strategic priority to mitigate global climate change and enhance national energy security. While social media has reshaped online consumption behavior, the mechanisms through which these digital platforms influence energy-efficient purchasing remain underexplored. This study extends the Theory of Planned Behavior (TPB) by integrating price perception variables and applies multi-group structural equation modeling to examine how social media shapes Chinese consumers’ intentions to purchase energy-efficient air conditioning. The results show that (1) social media exposure strengthens energy-efficient purchasing intentions indirectly via behavioral attitude, subjective norm, and perceived behavioral control; (2) price perception is negatively associated with purchase intention; and (3) these effects vary by age cohort, gender, and income—Generation Z and female consumers are more susceptible to social media influence, while low-income groups exhibit heightened price sensitivity. These findings advance TPB theory and offer guidance for digital platform policies aimed at promoting energy-efficient consumption.
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Analysis of Carbon Emissions in Guangxi Logistics Industry Based on Environmental Kuznets Model
(2025-04-10)
Zheng, Zhong
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Xie, Rongyi
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Liu, Meiting
The development of social production has highlighted the issues of energy security and environmental pollution, making green and low-carbon development an urgent need. Green development is the foundation of high-quality development, and transportation and logistics, as an important part of energy consumption, have become an important system for green development. This article intends to use the Environmental Kuznets Model to conduct regression analysis on the output value and carbon emissions data of the logistics industry in Guangxi. Through analysis, the EKC curve is found to be N-shaped, indicating that with the continuous development of the logistics industry in Guangxi, the environmental quality first decreases, then improves, and then decreases again, indicating that the logistics industry in Guangxi is facing enormous carbon reduction pressure. The paper analyzes and proposes feasible suggestions in order to make positive contributions to the low-carbon development of the logistics industry in Guangxi.
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Influence of Social Media on Consumers' Green Purchase Intention of Air Conditioners: The Mediating Role of Behavioral Attitude
(2025-01-01)
Zheng, Zhong
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Srinuan, Chalita
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Rojniruttikul, Nuttawut
This study explores the factors influencing green purchase intentions among Chinese consumers in the context of air conditioners, focusing on the roles of behavioral attitudes and social media. The research examines three key hypotheses: the relationship between favorable behavioral attitudes and green purchase intentions, the influence of social media on shaping these attitudes, and the mediating role of social media in enhancing green purchase intentions. The findings support all three hypotheses, demonstrating a significant positive relationship between behavioral attitudes and green purchase intentions, a strong influence of social media on shaping favorable attitudes, and the mediating effect of social media in amplifying these attitudes' impact on purchase intentions. These results underscore the importance of leveraging social media for effective marketing strategies and fostering positive behavioral attitudes to promote environmentally friendly products. The study offers practical implications for businesses and policymakers aiming to enhance consumer engagement and drive green purchases. Future research directions include longitudinal studies, cross-cultural comparisons, and investigations into emerging technologies' impact on consumer behavior. This research contributes to the growing body of knowledge on digital consumer behavior and provides actionable insights for optimizing marketing strategies in the digital age.
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Technical Scheme for Optimizing Urban and Rural Logistics Operations and Improving the Informatization of Rural Logistics
(2024-02-13)
Zheng, Zhong
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He, Wanxian
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Wei, Ganglan
In order to optimize the core problems encountered in the operation of urban and rural logistics and improve the informatization degree of rural logistics, the authors of this paper conduct research on the application of big data, cloud computing, and other technologies in urban and rural logistics and informatization. Based on the current problems, the authors adopt the hierarchical design, C/S architecture, and cloud API technology to improve the low level of informatization in urban and rural logistics, as well as optimize the dispersion and repetitive construction of logistics resources for logistics enterprises in urban and rural areas. Overall, a feasible sharing technology solution for urban-rural logistics informatization has been provided, providing a certain reference for optimizing urban-rural logistics operations and improving rural informatization issues.
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Optimization of Logistics Distribution Route Based on Ant Colony Algorithm – Taking Nantian Logistics as an Example
(2023-01-01)
Zheng, Zhong
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Liu, Shan
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Zhou, Xiaoying
The continuous development of social economy and the people’s growing yearning for a better life have promoted the rapid development of e-commerce, and urban distribution business has become increasingly important. Urban distribution is also faced with relatively complex task requirements, such as short time window, strict requirements, complex road conditions, high frequency of tasks, etc. Choosing the right path has become the key issue to improve distribution efficiency. Aiming at the problems encountered in the distribution of urban distribution routes, the paper uses ant colony algorithm to analyze and optimize the distribution routes, and uses MATLAB programming to solve the optimized distribution scheme. By comparing the data before and after optimization, it is found that the logistics transportation cost is effectively reduced, and the logistics transportation resources are saved, which proves the feasibility of the algorithm, and provides a certain reference for improving the efficiency of urban distribution and reducing the distribution cost.
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Evaluation Index System of Core Competitiveness of Small and Medium-Sized Logistics Enterprises in Nanning
(2022-01-01)
Zheng, Zhong
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Wang, Jingzuo
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Li, Liwei
Under the impact of economic transformation, the presence and prosperity of small and medium-sized logistics enterprises have been seriously impacted, and cultivating and improving the core competitiveness of enterprises has become an effective way for its survival and development. Based on the analysis of the current theoretical research and application status of the core competitiveness of small and medium-sized logistics enterprises at home and abroad, this paper establishes a set of evaluation index system in line with the core competitiveness of small and medium-sized logistics enterprises. Taking small and medium-sized logistics enterprises in Nanning as an example, this paper uses analytic hierarchy process to analyze the factors restricting the competitiveness of small and medium-sized logistics enterprises, mainly including liquidity ratio capital factors such as asset liability ratio and accounts receivable turnover rate show that in the current complex and changeable macro development environment, enterprise capital factor is an important factor related to enterprise production and development. The research of this paper looks for the direction for logistics enterprises to improve their competitiveness, so as to put forward constructive suggestions for enterprise development decision-making.
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Analysis on the Training Strategy of Applied Logistics Talents in the New Era Under CDIO Mode
(2022-01-01)
Zheng, Zhong
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Li, Liwei
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Zhang, Geng E.
In order to explore how to cultivate applied logistics talents in line with the new model and new business format, this paper uses the questionnaire to statistically analyze the effect of school talent training, combined with the gap between the actual employment demand of enterprises and the current situation of talents, analyzes the contradiction between the supply and demand of logistics talents, and analyzes in detail the rapidly developing new retail, real-time distribution, intelligent logistics The knowledge demand, core competence and demand of logistics talents in new modes and new business states such as cold chain logistics, introduce CDIO mode to design talent training scheme, analyze the curriculum index system of logistics talents under CDIO mode by analytic hierarchy process, and summarize the training strategies of Applied Logistics Talents under CDIO mode to adapt to the new mode and new business state, In order to provide some reference value for optimizing the logistics talent training program under the background of the new era.
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The Role of Artificial Intelligence Technology in Improving the Resilience of Supply Chain During COVID-19
(2022-01-01)
Zheng, Zhong
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Zhang, Genge
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Lin, Yun
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Pan, Yanfang
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He, Yandong
The outbreak of COVID-19 has posed continuous and huge challenges to the global supply chain. Difficulties in resuming work, border blockade, and sharp decline in market sales have increased the brittleness of the supply chain, which has put forward new and urgent demands on the resilience of the supply chain. In this context, this paper studies the impact of the epidemic on the supply chain, summarizes the thinking of enterprise representatives in typical industries on improving supply chain resilience under the epidemic situation, studies the specific strategies of using artificial intelligence technology to improve supply chain resilience, studies the correlation between supply chain resilience and artificial intelligence technology, analysis of artificial intelligence in improving supply chain resilience mechanism, specific analysis of artificial intelligence through what key technologies to improve supply chain resilience. On the basis, this paper construct artificial intelligence in the supply chain resilience technical framework, and construct a preliminary scheme for the integration of artificial intelligence and supply chain resilience, in order to provide for the outbreak to improve supply chain resilience reference and guiding significance.

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