Discrimination of black tea fermentation degree based on multi-data fusion of near-infrared spectroscopy and machine vision

Zhang, Bai; Li, Zhenfeng; Song, Feihu; Zhou, Qiaoyi; Raghavan, Vijaya; Song, Cuihua; Ling, Caijin

doi:10.1007/s11694-023-01935-3

Cited by 2 publications

(1 citation statement)

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In practical applications, multi-sensor systems leverage diverse information sources to garner comprehensive insights about experimental subjects, facilitating real-time monitoring. For instance, Bai et al [ 25 ] employed a multi-data fusion approach that integrates near-infrared spectroscopy with machine vision to evaluate the fermentation level of black tea. Eyob et al [ 26 ] constructed a continuous stream time series using terrestrial and remote sensing data combined with various machine learning algorithms.…”

Section: Introductionmentioning

confidence: 99%

Logistics Center Selection and Logistics Network Construction from the Perspective of Urban Geographic Information Fusion

Ma,

Zheng,

Liang

et al. 2024

Sensors

View full text Add to dashboard Cite

The last-mile logistics in cities have become an indispensable part of the urban logistics system. This study aims to explore the effective selection of last-mile logistics nodes to enhance the efficiency of logistics distribution, strengthen the image of corporate distribution, further reduce corporate operating costs, and alleviate urban traffic congestion. This paper proposes a clustering-based approach to identify urban logistics nodes from the perspective of geographic information fusion. This method comprehensively considers several key indicators, including the coverage, balance, and urban traffic conditions of logistics distribution. Additionally, we employed a greedy algorithm to identify secondary nodes around primary nodes, thus constructing an effective nodal network. To verify the practicality of this model, we conducted an empirical simulation study using the logistics demand and traffic conditions in the Xianlin District of Nanjing. This research not only identifies the locations of primary and secondary logistics nodes but also provides a new perspective for constructing urban last-mile logistics systems, enriching the academic research related to the construction of logistics nodes. The results of this study are of significant theoretical and practical importance for optimizing urban logistics networks, enhancing logistics efficiency, and promoting the improvement of urban traffic conditions.

show abstract

Section: Introductionmentioning

confidence: 99%