Water eutrophication evaluation based on multidimensional trapezoidal cloud model

Yu, Jiabin; Shen, Zhe; Zhao, Zhiyao; Wang, Xiaoyi; Xu, Jiping; Sun, Qian; Wang, Li; Liu, Guandong

doi:10.1007/s00500-020-05343-3

Cited by 7 publications

(2 citation statements)

References 25 publications

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“…Therefore, it is more appropriate to provide estimates by a verbal value than a numerical value. Yu et al [ 28 ] applied AIVILNs to improve the trapezoidal cloud model to evaluate the eutrophication of a specific water environment.…”

Section: Introductionmentioning

confidence: 99%

A Rice Hazards Risk Assessment Method for a Rice Processing Chain Based on a Multidimensional Trapezoidal Cloud Model

Chen

Zhang

et al. 2023

Foods

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Rice is common in the human diet, making rice safety issues important. Moreover, rice processing safety is key for rice security, so rice processing chain risk assessment is critical. However, methods proposed to assess the rice processing chain risk have issues, such as the use of unreasonable thresholds for the rice processing chain and fixed weight. To solve these problems, we propose a risk assessment method for the rice processing chain based on a multidimensional trapezoidal cloud model. First, an evaluation model based on a multidimensional trapezoidal cloud model was established. Based on the historical evaluation results, Atanassov’s interval-valued intuition language numbers (AIVILNs) were introduced to determine the cloud model’s parameters. Second, the concept of dynamic weight was introduced to integrate the static and dynamic weights. An exponential function was used to construct dynamic weighting mechanisms, and the analytic hierarchy stage (AHP) was used to construct a static weight. The proposed method was validated by 104 sets of rice processing chain data, and the results show that the method could evaluate the risk level of the rice processing chain more accurately and reasonably than other methods, indicating that it can provide a sound decision-making basis for food safety supervision authorities.

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Section: Introductionmentioning

confidence: 99%

A Rice Hazards Risk Assessment Method for a Rice Processing Chain Based on a Multidimensional Trapezoidal Cloud Model

Chen

Zhang

et al. 2023

Foods

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“…Methods such as cloud model 11 and fuzzy integrated evaluation 12 convert quantitative risk values and intervals into qualitative language sets based on membership theory. Qualitative-quantitative comprehensive risk assessment methods is often used for attribute reduction 13 and risk grading 14 . Table 1.…”

Section: Introductionmentioning

confidence: 99%

A Risk Assessment Model for the Entire Rice Processing Chain Based on Kmeans++ and Extreme Learning Machine

Yu,

Ma,

Fan

et al. 2023

Preprint

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The rice processing chain is an extremely important part of the rice supply chain, so the risk assessment on the main pollutants in the rice processing chain is of great significance. The existing risk assessment methods are subjective on the weight determination of risk indicators and the comprehensive risk assessment of the processing chain, and they do not consider the characteristics of the indicators, resulting in the unreasonable assessment results. And the existing assessment models have poor robustness and low accuracy. To solve these problems, this article proposes a risk assessment method for the entire rice processing chain based on Kmeans + + and extreme learning machine (ELM). Based on multi-level risk assessment index system, a risk assessment model of main pollutants in rice processing chain was constructed. According to the characteristics of rice pollutants, the pollutant index toxicological characteristics were integrated into the entropy weight. The comprehensive risk index of the processing chain was obtained, and the Kmeans + + clustering algorithm was used to cluster the index and adaptively mining data characteristics to classify risk levels. ELM was used for risk assessment. The proposed method was validated by 75 sets of rice processing chain data, based on six pollutant indicators of Pb, Cd, Hg, aflatoxin B1, zearalenone and deoxynivalenol. The results show that the risk classification accuracy of the proposed method in the test set was 93.3%, and it was more accurately and reasonably than the compared methods. This study strengthens the advantages of big data and artificial intelligence technology in food safety and supervision in the process of digital transformation of agriculture, provides more accurate and reliable decision-making basis for food safety supervisory departments, and lays a solid foundation for subsequent rapid warning and prevention and control decisions.

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Benefit evaluation of East Route Project of South to North Water Transfer based on trapezoid cloud model

Yang

Huang

Fang

et al. 2021

Agricultural Water Management

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Water eutrophication evaluation based on multidimensional trapezoidal cloud model

Cited by 7 publications

References 25 publications

A Rice Hazards Risk Assessment Method for a Rice Processing Chain Based on a Multidimensional Trapezoidal Cloud Model

A Rice Hazards Risk Assessment Method for a Rice Processing Chain Based on a Multidimensional Trapezoidal Cloud Model

A Risk Assessment Model for the Entire Rice Processing Chain Based on Kmeans++ and Extreme Learning Machine

Benefit evaluation of East Route Project of South to North Water Transfer based on trapezoid cloud model

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