The Kinetic Model of the Peel Brittleness of Stored Cucumis Melons Based on Visible/Near-Infrared Spectroscopy by Defang Xu, Huamin Zhao, Shujuan Zhang, Chengji Li, Fei Zhao

“…CARS and SPA were adopted to extract the feature wavelengths and establish the peel brittleness of PLS prediction model. The model’s prediction accuracy was 0.919, and the prediction root-mean-square was 25.413, indicating that NIR is able to realize the prediction of the peel brittleness of Cucumis melons. …”
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Hydrochemistry of the Hot Springs in Western Sichuan Province Related to the Wenchuan MS 8.0 Earthquake by Zhi Chen, Jianguo Du, Xiaocheng Zhou, Li Yi, Lei Liu, Chao Xie, Yueju Cui, Ying Li

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Research on the evolution of college online public opinion risk based on improved Grey Wolf Optimizer combined with LSTM model. by Chao Cao, Ziyu Li, Lingzhi Li, Fanglu Luo

“…The prediction accuracy of the model is validated through several evaluation criteria, and a comparison between real and predicted results, and the simulation of the intervention on this incident indicates that the proposed model is competent for both trend prediction and assisting in intervention. …”
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A Novel Approach for Operating Speed Continuous Predication Based on Alignment Space Comprehensive Index by Ying Yan, Gengping Li, Jinjun Tang, Zhongyin Guo

“…Although extensive studies have been conducted on operating speed prediction, few models can finish practical continuous prediction at each point along alignment on multilane highways. …”
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Temperature-dependent toxicity and mechanisms of florfenicol on the embryonic development of marine medaka (Oryzias melastigma) by Xingying Guo, Xu Gong, Jinhui Wang, Tan-Duc Nguyen, Syed Shabi Ul Hassan Kazmi, Jiezhang Mo, Feng Hua, Wenhua Liu, Zhen Wang

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Adaptive Hybrid Soft-Sensor Model of Grinding Process Based on Regularized Extreme Learning Machine and Least Squares Support Vector Machine Optimized by Golden Sine Harris Hawk Op... by Wei Xie, Jie-sheng Wang, Cheng Xing, Sha-Sha Guo, Meng-wei Guo, Ling-feng Zhu

“…In order to deal with the problem that the prediction accuracy of the model decreases due to changes of industrial status, this paper adopts moving window (MW) strategy to adaptively revise the LSSVM (MW-LSSVM), which greatly improves the prediction accuracy of the LSSVM. …”
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Two-Phase Model of Multistep Forecasting of Traffic State Reliability by Jufen Yang, Zhigang Liu, Guiyan Jiang, Lin Zhu

“…Multistep prediction of traffic state is a key technology for advanced transportation information system. …”
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Spectroscopic Method for Detection of Soluble Solid Content in Cherry Tomato Using Deep Convolutional Generative Adversarial Network-Based Data Augmentation by WU Zhijing, LIU Fuqiang, LI Zhigang, CHEN Hui

“…The results showed that the 1D-CNNR model based on the calibration set separated from the combined dataset was the optimal regression model for SSC detection. The prediction accuracy of the model for the test set from the combined dataset was the highest, with correlation coefficient of prediction (rp) of 0.980 7, and root mean square error of prediction (RMSEp) of 0.192 9. …”
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A combined model of shoot phosphorus uptake based on sparse data and active learning algorithm by Tianli Wang, Yi Zhang, Haiyan Liu, Fei Li, Dayong Guo, Ning Cao, Yubin Zhang

“…In this study, we proposed a combination prediction model based on some representative samples. …”
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A Novel Improved Grey Incidence Model for Evaluating the Performance of Supply Chain Resilience by Feipeng Huang

“…Taking into account that the resilience index is easily affected by nonconventional factors in the real environment, the WAWBO weakening buffer operator and the metabolism idea are introduced to improve the grey prediction method, so as to realize the dynamic prediction of the resilience index. …”
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CFD Simulation of Transonic Flow in High-Voltage Circuit Breaker by Xiangyang Ye, Mahesh Dhotre

“…The correlation between the flow prediction accuracy and the breakdown voltage prediction capability is identified.…”
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A Novel Discrete DGM (2, 1, t2) Model Based on Stochastic Oscillation Sequence and Its Application by Jun-Lin Xu, You-Jun Chen

“…This article aims to improve the prediction accuracy of the grey model for stochastic oscillation sequence, to overcome the defect of the direct span from difference to differential and to better depict the growth trend of data series. …”
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Research on the Influence of Volatility of International Energy Commodity Futures Market on CPI in China by Keyao Lin, Chao Xun, Fei Wang, Angela Chi Chao, Zhenyu Du

“…However, when exceptional circumstances occur, the prediction results will show a specific deviation, and the prediction accuracy will also be reduced. …”
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Short-Term Passenger Flow Forecasting for Rail Transit considering Chaos Theory and Improved EMD-PSO-LSTM-Combined Optimization by Lixin Zhao, Hui Jin, Xintong Zou, Xiao Liu

“…Each subsequence of the phase-space reconstruction was built into an improved PSO-LSTM prediction model, and the output of each prediction model was summed to determine the final output. …”
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Extracting knowledge of preventive maintenance using data mining technique in interaction with production within textile industry by Shahram Fatemi

“…Using IBM SPSS Modeler 18, the most significant results of datamining calculations to extract knowledge are as follows, which are arranged based on main predictors of the research: predicting models of "strategy innovation in net with data code (A5)" with the prediction wight of 0.34; "technology innovation in net with data code (A1)" with the prediction wight of 0.30; "work environment innovation in net with data code (A3)" with the prediction wight of 0.16; Quality innovation in net with data code (A4)" with the prediction wight of 0.15; "employe  innovation in net with data code (A2)" with the prediction wight of 0.10 are utilized to accurately analyze preventive maintenance in interaction with production.…”
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Photoplethysmography based psychological stress detection with pulse rate variability feature differences and elastic net by Fenghua Li, Peida Xu, Shichun Zheng, Wenfeng Chen, Yang Yan, Suo Lu, Zhengkui Liu

“…However, existing stress-detection models with only heartbeat/pulse input are limited in prediction output granularity, and models with multiple prediction levels output usually require additional bio-signal other than heartbeat, which may increase the number of sensors and be wearable unfriendly. …”
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Well Control Optimization of Waterflooding Oilfield Based on Deep Neural Network by Lihui Tang, Junjian Li, Wenming Lu, Peiqing Lian, Hao Wang, Hanqiao Jiang, Fulong Wang, Hongge Jia

“…Based on the production dynamic prediction model, a series of model generation, production prediction, comparison, and optimization are carried out to find the best production plan of the reservoir. …”
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A New Synergistic Forecasting Method for Short-Term Traffic Flow with Event-Triggered Strong Fluctuation by Darong Huang, Zhenping Deng, Bo Mi

“…Directing against the shortcoming of low accuracy in short-term traffic flow prediction caused by strong traffic flow fluctuation, a novel method for short-term traffic forecasting based on the combination of improved grey Verhulst prediction algorithm and first-order difference exponential smoothing is proposed. …”
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Fuzzy-Swarm Intelligence-Based Short-Term Load Forecasting Model as a Solution to Power Quality Issues Existing in Microgrid System by Demsew Mitiku Teferra, Livingstone M. H. Ngoo, George N. Nyakoe

“…The Fuzzy-PSO load prediction model shows results that have superior performance to the fuzzy-alone load prediction results.…”
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Study of Problems Related to Laying Ballastless Track in the Turnout of Ballasted Track at High-Speed Railway Stations by Ma Xue-Ning, Hao Zi-Xiang, Liu Chang, Wang Xu, Wang Bo-Lin

“…The sum of squares of the minimum errors of the combined model is used as the objective function to solve the optimal weighting coefficient, and in this way the combined prediction model is constructed. Through the prediction comparison, we found that the accuracy of the three-model combination prediction model is better than any single- or two-model combination, and its adaptability and reliability are stronger and more reliable. …”
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