Short-Term Traffic Flow Prediction: A Method of Combined Deep Learnings by Chuanxiang Ren, Chunxu Chai, Changchang Yin, Haowei Ji, Xuezhen Cheng, Ge Gao, Heng Zhang

“…Short-term traffic flow prediction can provide a basis for traffic management and support for travelers to make decisions. …”
Get full text

Durability Test and Service Life Prediction Methods for Silicone Structural Glazing Sealant by Bo Yang, Junjin Liu, Jianhui Li, Chao Wang, Zhiyuan Wang

“…A recursive algorithm was developed to predict TBS degradation under actual service conditions based on the degradation model and environmental records, with verification through outdoor aging tests. …”
Get full text

Two Machine-learning Hybrid Models for Predicting Type 2 Diabetes Mellitus by Rahman Farnoosh, Karlo Abnoosian, Rasha Abbas Isewid

“…The samples are categorized into three classes: diabetic (Y), nondiabetic (N), and predicted diabetic (P). The dataset contains twelve attributes and includes outlier data. …”
Get full text

Study on Predicting Blueberry Hardness from Images for Adjusting Mechanical Gripper Force by Hao Yin, Wenxin Li, Han Wang, Yuhuan Li, Jiang Liu, Baogang Li

“…Firstly, a chimpanzee optimization algorithm (ChOA) was used to optimize a prediction model that established a mapping relationship between fruit diameter, thickness, weight, and fruit hardness. …”
Get full text

Towards Predicting Business Activity Classes from European Digital Corporate Reports by Péter Molnár, Alex Suta, Bence Lukács, Árpád Tóth

Get full text

Fault prediction of smart meter based on spatio-temporal convolution neural network by Gao Wenjun, Xue Binbin, Pang Zhenjiang

“…Then, combined with CNN, the fault prediction model of smart meter is established, and the model parameters are optimized by adaptive momentum estimation (Adam) algorithm. …”
Get full text

PREDICTING AND ANALYZING OF TURKISH SUGAR PRICE WITH ARCH, GARCH, EGARCH AND ARIMA METHODS by Mehmet Arif ŞAHİNLİ

“…Mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute deviation (MAD) were used to determine the fit model for making predicting. In this study, we found the best model as a GARCH (1,1) model.…”
Get full text

Predicting Financial Extremes Based on Weighted Visual Graph of Major Stock Indices by Dong-Rui Chen, Chuang Liu, Yi-Cheng Zhang, Zi-Ke Zhang

“…In addition, we propose an extremes indicator through the network, which is constructed from the price time series using a weighted visual graph algorithm. Experimental results on 12 stock indices show that the proposed indicators can predict financial extremes very well.…”
Get full text

The Method of Predicting the Ｒise of Temperature by Combining Fuzzy System and Ｒecursive Least Square by WANG Gang, ZHANG Bo, WANG Guan, YE San-pai

“…For the problem that the rise of temperature of fitting is too high to control，a new method of predicting the rise of temperature has been put forward. …”
Get full text

Research on wind temperature prediction of tunneling working site based on PSO−SVR by Yanhe LI, Zhijun WAN, Zhenzi YU, Hong GOU, Wanli ZHAO, Jiale ZHOU, Peng SHI, Zheng ZHEN, Yuan ZHANG

“…By comparing with the MLR model estimated by the least square method and the conventional SVR model calibrated by the “trial and error” method, the advantages of the PSO-SVR algorithm are analyzed. The PSO-SVR algorithm model was applied to predict airflow temperature in J-24120 protective airway of Pingmei No.10 Coal Mine. …”
Get full text

Analysis of the dynamics of changes in factor load models for predicting failures of a spacecraft by Kraev Konstantin, Zaitsev Pavel, Kazakovtsev Vladimir

“…The paper considers the theoretical aspects of factor analysis as applied to the problem of predicting the failure-free operation of low-orbit communication satellites. …”
Get full text

A Multistep Prediction of Hydropower Station Inflow Based on Bagging-LSTM Model by Lulu Wang, Hanmei Peng, Mao Tan, Rui Pan

“…Under the joint influence of soil, upstream inflow, and precipitation, the inflow is often characterized by time lag, nonlinearity, and uncertainty and then results in the difficulty of accurate multistep prediction of inflow. To address the coupling relationship between inflow and the related factors, this paper proposes a long short-term memory deep learning model based on the Bagging algorithm (Bagging-LSTM) to predict the inflows of future 3 h, 12 h, and 24 h, respectively. …”
Get full text

Research on Temperature Prediction of EMU Transformer Based onMultiple Nonlinear Regression by YAN Youjun

“…At present, the use of EMU data is mainly based on quantitative observation and qualitative analysis, lacking of accurate state prediction. Therefore, this paper proposes a prediction algorithm based on multiple nonlinear regression to establish a transformer temperature prediction model. …”
Get full text

Regional Heatwave Prediction Using Graph Neural Network and Weather Station Data by Peiyuan Li, Yin Yu, Daning Huang, Zhi‐Hua Wang, Ashish Sharma

“…In this paper, we propose a heatwave prediction algorithm based on a novel deep learning model, that is, Graph Neural Network (GNN). …”
Get full text

A Machine Learning Method for Predicting Driving Range of Battery Electric Vehicles by Shuai Sun, Jun Zhang, Jun Bi, Yongxing Wang

“…The study is innovative in its application of machine learning method, the gradient boosting decision tree algorithm, on the driving range prediction which includes a very large number of factors that cannot be considered by conventional regression methods. …”
Get full text

Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

“… Accurate water level (WL) prediction is essential for the efficient management of various water resource projects. …”
Get full text

Prediction of magnetohydrodynamics fluid flow with viscous dissipation through artificial neural network by Sewli Chatterjee

“…The Levenberg–Marquardt algorithm to predict the Nusselt Number (NN) and Skin Friction Coefficients (SFCs). …”
Get full text

Drought Prediction Model of Pearl River Basin Based on SST and Machine Learning by FENG Xin, LIU Yanju, TONG Hongfu, QIAN Shuni

Get full text

LEO satellite Internet resource allocation strategy based on terminal traffic prediction by SHEN Fei, LYU Chengcheng, ZHANG Jiaxuan, RUAN Xiaoting

“…An improved LSTM-ARIMA algorithm was proposed with real datasets by the strategy to accurately predict the data traffic generated in the ground area over a certain period of time in the future. …”
Get full text

Predicting Energy Consumption in Building Heating Systems Using Model Identification Methods by Qu Minglu, Du Shanghe, Zhang Xinlin, Yu Zhen, Li Huai

“…During deployment, the predicted <italic>R</italic>² value and total energy consumption deviation were 0.87 and 5.18%, respectively. …”
Get full text