Research graph
References from An Adaptive Fuzzy Recurrent Stochastic Configuration Network for Food Quality Prediction with Limited Samples. Local targets link to admitted publications; unresolved targets remain external evidence.
Integrating AI and advanced spectroscopic techniques for precision food safety and quality control
10.1016/j.tifs.2024.104850 · 2025 · External reference
Deep learning-based regression of food quality attributes using near-infrared spectroscopy and hyperspectral imaging: A review
10.1016/j.foodchem.2025.145932 · 2025 · External reference
10.3390/pr11092809
10.3390/pr11092809 · External reference
Prediction of quality traits in packaged mango by NIR spectroscopy
10.1016/j.foodres.2025.115963 · 2025 · External reference
10.3390/pr9071241
10.3390/pr9071241 · External reference
Recent advances and application of machine learning in food flavor prediction and regulation
10.1016/j.tifs.2023.07.012 · 2023 · External reference
Food flavor analysis 4.0: A cross-domain application of machine learning
10.1016/j.tifs.2023.06.011 · 2023 · External reference
Advanced chemometrics toward robust spectral analysis for fruit quality evaluation
10.1016/j.tifs.2024.104612 · 2024 · External reference
Classification-based machine learning approaches to predict the taste of molecules: A review
10.1016/j.foodres.2023.113036 · 2023 · External reference
Optimizing predictive models for food contaminants: The role of wavelet transforms in ANN and PLSR analysis of heavy metals
10.1016/j.jfca.2025.108792 · 2026 · External reference
Combining ACE, PLS-R, and SVM-R for rapid detection of adulteration in saffron samples by diffuse reflectance infrared fourier transform spectroscopy
10.1016/j.foodcont.2024.110853 · 2025 · External reference
Quality evaluation of the processing suitability of yam using near-infrared spectroscopy combined with enhanced CARS-SVR algorithm
10.1016/j.jfca.2025.108798 · 2026 · External reference
Random forest-assisted Raman spectroscopy and rapid detection of sweeteners
10.1016/j.infrared.2025.105871 · 2025 · External reference
Analyzing TVB-N in snakehead by Bayesian-optimized 1D-CNN using molecular vibrational spectroscopic techniques: Near-infrared and Raman spectroscopy
10.1016/j.foodchem.2024.141701 · 2025 · External reference
Age Discrimination of Chinese Baijiu Based on Midinfrared Spectroscopy and Chemometrics
10.1155/2021/5527826 · 2021 · External reference
A combinatorial approach to chicken meat spoilage detection using color-shifting silver nanoparticles, smartphone imaging, and artificial neural network (ANN)
10.1016/j.foodchem.2024.142390 · 2025 · External reference
Convolutional neural networks in the realm of food quality and safety evaluation: Current achievements and future prospects
10.1016/j.tifs.2025.105162 · 2025 · External reference
10.3390/foods14020247
10.3390/foods14020247 · External reference
Deep learning in food authenticity: Recent advances and future trends
10.1016/j.tifs.2024.104344 · 2024 · External reference
Deep learning-driven Vis/NIR spectroscopic devices for fruit quality assessment: A comprehensive review
10.1016/j.tifs.2025.105262 · 2025 · External reference
Deep learning-assisted fluorescence spectroscopy for food quality and safety analysis
10.1016/j.tifs.2024.104821 · 2025 · External reference
Harnessing Artificial Intelligence to Safeguard Food Quality and Safety
10.1016/j.jfp.2025.100621 · 2025 · External reference
Stochastic Configuration Networks: Fundamentals and Algorithms
10.1109/tcyb.2017.2734043 · 2017 · External reference
Non-destructive predictions of sugar contents in litchis based on near-infrared spectroscopy and stochastic configuration network
10.1007/s11694-024-02787-1 · 2024 · External reference
Online Self-Learning Stochastic Configuration Networks for Nonstationary Data Stream Analysis
10.1109/tii.2023.3301059 · 2024 · External reference
Fuzzy Stochastic Configuration Networks for Nonlinear System Modeling
10.1109/tfuzz.2023.3315368 · 2024 · External reference
Fuzzy Recurrent Stochastic Configuration Networks for Industrial Data Analytics
10.1109/tfuzz.2024.3511695 · 2025 · External reference
Fuzzy identification of systems and its applications to modeling and control
10.1109/tsmc.1985.6313399 · 1985 · External reference
Takagi-Sugeno-Kang Fuzzy Systems with Iterated Projection Optimization for Classification Problems
10.1109/tfuzz.2025.3635407 · 2026 · External reference
Adaptive Yager T-Norm-Based Takagi–Sugeno–Kang Fuzzy Systems
10.1109/tsmc.2025.3621346 · 2025 · External reference
Optimization and applications of echo state networks with leaky-integrator neurons
10.1016/j.neunet.2007.04.016 · 2007 · External reference
Recurrent stochastic configuration networks with block increments
10.1016/j.neunet.2025.107986 · 2026 · External reference
Unresolved reference
External reference
Non-Destructive Measurement of Sugar Content in Litchis Using Visible and Near-Infrared Spectroscopy and Fuzzy Stochastic Configuration Network
10.1111/1750-3841.70565 · 2025 · External reference
Modeling wine preferences by data mining from physicochemical properties
10.1016/j.dss.2009.05.016 · 2009 · External reference
Non-destructive predictions of sugar contents in litchis based on near-infrared spectroscopy and stochastic configuration network
10.1007/s11694-024-02787-1 · ExternalCitation · doi-reference
Modeling wine preferences by data mining from physicochemical properties
10.1016/j.dss.2009.05.016 · ExternalCitation · doi-reference
Analyzing TVB-N in snakehead by Bayesian-optimized 1D-CNN using molecular vibrational spectroscopic techniques: Near-infrared and Raman spectroscopy
10.1016/j.foodchem.2024.141701 · ExternalCitation · doi-reference
A combinatorial approach to chicken meat spoilage detection using color-shifting silver nanoparticles, smartphone imaging, and artificial neural network (ANN)
10.1016/j.foodchem.2024.142390 · ExternalCitation · doi-reference
Deep learning-based regression of food quality attributes using near-infrared spectroscopy and hyperspectral imaging: A review
10.1016/j.foodchem.2025.145932 · ExternalCitation · doi-reference
Combining ACE, PLS-R, and SVM-R for rapid detection of adulteration in saffron samples by diffuse reflectance infrared fourier transform spectroscopy
10.1016/j.foodcont.2024.110853 · ExternalCitation · doi-reference
Classification-based machine learning approaches to predict the taste of molecules: A review
10.1016/j.foodres.2023.113036 · ExternalCitation · doi-reference
Prediction of quality traits in packaged mango by NIR spectroscopy
10.1016/j.foodres.2025.115963 · ExternalCitation · doi-reference
Random forest-assisted Raman spectroscopy and rapid detection of sweeteners
10.1016/j.infrared.2025.105871 · ExternalCitation · doi-reference
Optimizing predictive models for food contaminants: The role of wavelet transforms in ANN and PLSR analysis of heavy metals
10.1016/j.jfca.2025.108792 · ExternalCitation · doi-reference
Quality evaluation of the processing suitability of yam using near-infrared spectroscopy combined with enhanced CARS-SVR algorithm
10.1016/j.jfca.2025.108798 · ExternalCitation · doi-reference
Harnessing Artificial Intelligence to Safeguard Food Quality and Safety
10.1016/j.jfp.2025.100621 · ExternalCitation · doi-reference
Optimization and applications of echo state networks with leaky-integrator neurons
10.1016/j.neunet.2007.04.016 · ExternalCitation · doi-reference
Recurrent stochastic configuration networks with block increments
10.1016/j.neunet.2025.107986 · ExternalCitation · doi-reference
Food flavor analysis 4.0: A cross-domain application of machine learning
10.1016/j.tifs.2023.06.011 · ExternalCitation · doi-reference
Recent advances and application of machine learning in food flavor prediction and regulation
10.1016/j.tifs.2023.07.012 · ExternalCitation · doi-reference
Deep learning in food authenticity: Recent advances and future trends
10.1016/j.tifs.2024.104344 · ExternalCitation · doi-reference
Advanced chemometrics toward robust spectral analysis for fruit quality evaluation
10.1016/j.tifs.2024.104612 · ExternalCitation · doi-reference
Deep learning-assisted fluorescence spectroscopy for food quality and safety analysis
10.1016/j.tifs.2024.104821 · ExternalCitation · doi-reference
Integrating AI and advanced spectroscopic techniques for precision food safety and quality control
10.1016/j.tifs.2024.104850 · ExternalCitation · doi-reference
Convolutional neural networks in the realm of food quality and safety evaluation: Current achievements and future prospects
10.1016/j.tifs.2025.105162 · ExternalCitation · doi-reference
Deep learning-driven Vis/NIR spectroscopic devices for fruit quality assessment: A comprehensive review
10.1016/j.tifs.2025.105262 · ExternalCitation · doi-reference
Stochastic Configuration Networks: Fundamentals and Algorithms
10.1109/tcyb.2017.2734043 · ExternalCitation · doi-reference
Fuzzy Stochastic Configuration Networks for Nonlinear System Modeling
10.1109/tfuzz.2023.3315368 · ExternalCitation · doi-reference
Fuzzy Recurrent Stochastic Configuration Networks for Industrial Data Analytics
10.1109/tfuzz.2024.3511695 · ExternalCitation · doi-reference
Takagi-Sugeno-Kang Fuzzy Systems with Iterated Projection Optimization for Classification Problems
10.1109/tfuzz.2025.3635407 · ExternalCitation · doi-reference
Online Self-Learning Stochastic Configuration Networks for Nonstationary Data Stream Analysis
10.1109/tii.2023.3301059 · ExternalCitation · doi-reference
Fuzzy identification of systems and its applications to modeling and control
10.1109/tsmc.1985.6313399 · ExternalCitation · doi-reference
Adaptive Yager T-Norm-Based Takagi–Sugeno–Kang Fuzzy Systems
10.1109/tsmc.2025.3621346 · ExternalCitation · doi-reference
Non-Destructive Measurement of Sugar Content in Litchis Using Visible and Near-Infrared Spectroscopy and Fuzzy Stochastic Configuration Network
10.1111/1750-3841.70565 · ExternalCitation · doi-reference
Age Discrimination of Chinese Baijiu Based on Midinfrared Spectroscopy and Chemometrics
10.1155/2021/5527826 · ExternalCitation · doi-reference
10.3390/foods14020247
10.3390/foods14020247 · ExternalCitation · doi-reference
10.3390/pr11092809
10.3390/pr11092809 · ExternalCitation · doi-reference
10.3390/pr9071241
10.3390/pr9071241 · ExternalCitation · doi-reference
