Early warning modeling and analysis based on a deep radial basis function neural network integrating an analytic hierarchy process: A case study for food safety

Z Geng, D Shang, Y Han, Y Zhong - Food control, 2019 - Elsevier
Food safety is vital to the national economy and livelihood of people. Therefore, effective
food safety warnings are helpful to the healthy and sustainable development of society …

Early warning and control of food safety risk using an improved AHC-RBF neural network integrating AHP-EW

Z Geng, F Liu, D Shang, Y Han, Y Shang… - Journal of Food …, 2021 - Elsevier
Food safety is an important issue affecting social development. Early warning analysis and
risk control of food safety is of great significance in managing food safety risks, thereby …

An ensemble of AHP-EW and AE-RNN for food safety risk early warning

J Zhong, L Sun, E Zuo, C Chen, C Chen, H Jiang, H Li… - Plos one, 2023 - journals.plos.org
Food safety problems are becoming increasingly severe in modern society, and establishing
an accurate food safety risk warning and analysis model is of positive significance in …

Risk early warning of food safety using novel long short-term memory neural network integrating sum product based analytic hierarchy process

Z Geng, L Liang, Y Han, G Tao, C Chu - British Food Journal, 2022 - emerald.com
Purpose Food safety risk brought by environmental pollution seriously threatens human
health and affects national economic and social development. In particular, heavy metal …

Early warning modeling and analysis based on analytic hierarchy process integrated extreme learning machine (AHP-ELM): Application to food safety

ZQ Geng, SS Zhao, GC Tao, YM Han - Food Control, 2017 - Elsevier
Since the actual food safety monitoring data have characteristics of high-dimension,
complexity, discreteness and nonlinear properties, it is difficult to accurately predict the risk …

A Data-driven Integrated Safety Risk Warning Model based on Deep Learning for Civil Aircraft

Y Guo, Y Sun, Y He, F Du, S Su… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the extensive application of sensor technology, airlines accumulate a lot of flight data
during fleet operations. Quick access recorder (QAR) is an important basis for aircraft state …

Risk prediction model for food safety based on improved random forest integrating virtual sample

Z Geng, X Duan, J Li, C Chu, Y Han - Engineering Applications of Artificial …, 2022 - Elsevier
Food safety has a severe impact on the world economy and global health, and improving the
prediction accuracy and prevention ability of food safety risks and hazards protection is of …

Novel IAPSO-LSTM neural network for risk analysis and early warning of food safety

Z Geng, X Wang, Y Jiang, Y Han, B Ma… - Expert Systems with …, 2023 - Elsevier
Ensuring food quality and safety is essential after ensuring the quantity of food. Therefore,
an improved adaptive particle swarm optimization algorithm (IAPSO) for optimizing the long …

Generative adversarial network-based semi-supervised learning for real-time risk warning of process industries

R He, X Li, G Chen, G Chen, Y Liu - Expert Systems with Applications, 2020 - Elsevier
Due to the non-cognition of real-time data, rare loss-based risk warning methods can
effectively respond to unexpected emergencies. Machine learning has powerful data …

Prediction and Visual Analysis of Food Safety Risk Based on TabNet-GRA

Y Chen, H Li, H Dou, H Wen, Y Dong - Foods, 2023 - mdpi.com
Food safety risk prediction is crucial for timely hazard detection and effective control. This
study proposes a novel risk prediction method for food safety called TabNet-GRA, which …