Data-Driven Analysis of Risk-Assessment Methods for Cold Food Chains

Wang, Qian; Zhao, Zhiyao; Wang, Zhaoyang

doi:10.3390/foods12081677

Cited by 5 publications

(1 citation statement)

References 34 publications

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“…The application of the CiteSpace tool has facilitated the identification of research hotspots and trends across a spectrum of scientific disciplines, thereby significantly advancing scientific inquiry. Notably, this tool has been instrumental in fields such as food science [12,19], medicine [20], traditional Chinese medicine [21], and ecology [22], where it has helped to distill complex information and highlight areas ripe for further exploration. I. verum, as a globally significant research material, has been the subject of several literature reviews.…”

Section: Introductionmentioning

confidence: 99%

Based on CiteSpace Insights into Illicium verum Hook. f. Current Hotspots and Emerging Trends and China Resources Distribution

He,

Huan,

et al. 2024

Foods

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Illicium verum Hook. f. is a globally significant spice, which is recognized in China as a food-medicine homolog and extensively utilized across the pharmaceutical, food, and spice industries. China boasts the world’s leading resources of I. verum, yet its comprehensive utilization remains relatively underexplored. Through a resource survey of I. verum and the application of bibliometric visualization using CiteSpace, this study analyzed 324 papers published in the Web of Science Core Collection (WOSCC) from 1962 to 2023 and 353 core documents from China’s three major databases (CNKI, Wanfang Database, and VIP Database). I. verum from Guangxi province towards various southern provinces in China, with autumn fruits exhibited superior quality and market value over their spring fruits. Literature in WOSCC emerged earlier, with a research emphasis on food science technology and pharmacology pharmacy domains. WOSCC research on I. verum could be divided into two phases: an embryonic period (1962–2001) and a growth period (2002–2023), showing an overall upward trend in publication. The three major Chinese databases contain a larger number of publications, with a focus on the food sector, which could be categorized into three stages: an embryonic period (1990–1999), a growth period (2000–2010), and a stable period (2011–2023), with an overall downward trend in publication. Both Chinese and international research hotspots converge on the medical applications of I. verum, with antioxidant bioactivity research emerging as a prevailing trend. This study delineated the resource distribution of I. verum across China and identified the research hotspots and trends both in China and internationally. The findings are beneficial for guiding researchers in swiftly establishing their research focus and furnishing decision-makers with a comprehensive reference for industry information.

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Section: Introductionmentioning

confidence: 99%

Based on CiteSpace Insights into Illicium verum Hook. f. Current Hotspots and Emerging Trends and China Resources Distribution

He,

Huan,

et al. 2024

Foods

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Agricultural Financing Risk Data under Smart Contracts Based on LSTM-GRU Model

Lin

2024

2024 International Conference on Interactive Intelligent Systems and Techniques (IIST)

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Data-Driven Smart Assessment for Enterprise Audit Risks Based on Radial Base Function Neural Network and Grey Correlation Analysis

Yuan,

Zhang,

Chen

2024

J CIRCUIT SYST COMP

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In the era of big data, audit risk assessment is facing increasing business volume. Hence, it is important to develop automatic audit risk assessment methods for enterprises with the assistance of intelligent algorithms. As a consequence, this paper proposes data-driven smart assessment for enterprise audit risks-based radial basis function (RBF) neural networks and grey correlation analysis (GCA). First, evaluation data are collected and analyzed to understand the characteristics and influencing factors of enterprise audit risks. Secondly, RBF interpolation is introduced to establish the network structure for RBF neural networks. Then, GCA is integrated with RBF Interpolation (RBFNN) to formulate the automatic audit risk evaluation method, and the proposal is named RBF and GCA. Such a combined methodology can improve audit risk assessment efficiency. Finally, we make some experiments to evaluate the proposed TBF-GCA on a real-world dataset, and some evaluation indicators are specified based on the actual audit risk situation of the enterprises. The obtained results reveal that RBF–GCA has high accuracy in identity precision and can effectively identify audit risks for enterprises.

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Data-Driven Analysis of Risk-Assessment Methods for Cold Food Chains

Cited by 5 publications

References 34 publications

Based on CiteSpace Insights into Illicium verum Hook. f. Current Hotspots and Emerging Trends and China Resources Distribution

Based on CiteSpace Insights into Illicium verum Hook. f. Current Hotspots and Emerging Trends and China Resources Distribution

Agricultural Financing Risk Data under Smart Contracts Based on LSTM-GRU Model

Data-Driven Smart Assessment for Enterprise Audit Risks Based on Radial Base Function Neural Network and Grey Correlation Analysis

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