An Improved Metabolism Grey Model for Predicting Small Samples with a Singular Datum and Its Application to Sulfur Dioxide Emissions in China by Wei Zhou, Demei Zhang

“…Some features of this model are presented based on the error analysis in the case study. Results suggest that if action is not taken immediately, sulfur dioxide emissions in 2016 will surpass the standard level required by the Twelfth Five-Year Plan proposed by the China State Council.…”
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Size Design Method of Two-phase Ejector by Du Yanjun, Liu Feng, Liu Yunfa, Zhang Bo

“…Labview8.5 was applied as the real-time data collector. Through a data analysis, it was found that the injection coefficient of the injector is the highest when the correction value is δ = 0.95, and then drops. …”
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Research on HMM based link prediction method in heterogeneous network by Rong QIAN, Jianting XU, Kejun ZHANG, Hongyu DONG, Fangyuan XING

“…In order to solve the problem that incomplete mining of structural information and semantic information in heterogeneous networks, a link prediction method combining meta-path-based analysis and hidden Markov model was proposed for link prediction of heterogeneous network.Considering that clustering could effectively capture the structural information of heterogeneous network, the k-means algorithm was improved to obtain the initial clustering center method based on the minimum distance mean square error, and it was applied to the hidden Markov model, first-order cluster hidden markov model (C-HMM⁽¹⁾) link prediction method, and a link prediction method for heterogeneous network with second-order cluster hidden Markov model (C-HMM⁽²⁾) were designed.Further, considering the feature information of the data, a link prediction method called ME-HMM that combined the maximum entropy model and the second-order Markov model was proposed.The experimental results show that the ME-HMM has higher link prediction accuracy than the C-HMM, and the ME-HMM method has better performance than the C-HMM method because it fully considers the feature information of the data.…”
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Focused Crawler for Event Detection Using Metaheuristic Algorithms and Knowledge Extraction by Hossein Moradi, Fatemeh Azimzadeh

“…By integrating this method with machine learning algorithms, the proposed technique exhibits improvements in experiments, including decreased execution time and enhancements in metrics such as Root Mean Square Error (RMSE) and accuracy score. Comparative analysis reveals that the proposed method outperformed alternative models. …”
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Leveraging Participatory Extraction to Mobility Sensing for Individual Discovery in Crowded Environments by Lin Wang, Jing Yang, Wenyuan Liu

“…Finally, the experiment data are collected by 25 volunteers, and trace-driven simulations show that Euclidean distance error is below 4.69 and the convergence time is within 0.75 s.…”
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Bridge Deformation Monitoring Combining 3D Laser Scanning with Multi-Scale Algorithms by Dongmei Tan, Wenjie Li, Yu Tao, Baifeng Ji

“…The bridge deck’s micro-settlement error was ±1.2 mm, and the pier inclination error was ±2.8 mm, meeting the Chinese Highway Bridge Maintenance Code (JTG H11-2004) and the American Association of State Highway and Transportation Officials (AASHTO) standards, and the multi-scale algorithm achieved engineering-level accuracy. …”
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Tibiofemoral Joint Contact Force Estimation Based on OpenSim Musculoskeletal Modeling by WANG Xiaoling, JIAN Jiawei, XIE Qiurong, LIAN Zhanghui, GUO Chunming, GUO Jiemei, LI Yurong

“…MATLAB 2018b is used for statistical analysis. The effectiveness of the musculoskeletal model established in this study is verified by comparing the model estimation results with the measurement results of the implanted prosthesis.ResultsThe average correlation between the estimated contact force and the measured value of medial, lateral, and total contact force were 0.921±0.079, 0.817±0.084, and 0.930±0.066, and the average root square error were 0.336±0.146 BW, 0.332±0.146 BW, and 0.442±0.160 BW. …”
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Correction of ASCAT, ESA–CCI, and SMAP Soil Moisture Products Using the Multi-Source Long Short-Term Memory (MLSTM) by Qiuxia Xie, Yonghui Chen, Qiting Chen, Chunmei Wang, Yelin Huang

“…The RPE, LST, FVC, and ET were used as inputs to the LSTM to obtain loss data against in-situ SM measurements. Second, the ASCAT, ESA–CCI, and SMAP SM datasets were used as inputs to the LSTM to generate loss data, which were subsequently corrected using LSTM-derived loss data based on in-situ SM measurements. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…Results The model conducted predictions on missing detection data and achieved indirect measurements of key indicators, with a relative error between predicted and measured values staying below 25%, meeting acceptable standards. …”
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Ketahanan Perbankan Syariah Indonesia Terhadap Fluktuasi Kondisi Makroekonomi dan Kondisi Fundamental Saat Pandemi Covid-19 by Ayu Yuningsih, Esti Alfiah

“…Data analysis in this study uses a vector error correction model (VECM) as an approach to see short-term relationships, and cointegration tests as an approach to see indications of long-term relationships. . …”
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Crowd navigation monitoring during emergencies by Oksana Tymoshchuk, Maksym Tishkov, Victor Bondarenko

“…Implementation of the algorithm was tested on real videos and showed an error of about 0.04 m/s.…”
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Research on the Liquid Helium Insulation Characteristics of an Experimental System by Ye Chen, Liang Guo, Qiming Jia, Xiujuan Xie, Weiping Zhu, Ping Wang

“…The overall relative error between the simulated and experimental temperature distribution of the insulation layer is 14.3%, with a maximum error of 22.3%. …”
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Artificial intelligence models for determining the strength of centrally compressed pipe-concrete columns with square cross-section by Chepurnenko Anton, Yazyev Batyr, Tyurina Vasilina, Akopyan Vladimir

“…Artificial intelligence is currently widely used in data processing and analysis, including data on the load-bearing capacity of building structures. …”
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Risk Factors and Scabious Prevalence in Cats During 2020 in Griya Satwa Clinic, Magetan by Nedriana Cahya, Hardany Primarizky, Maya Nurwartanti Yunita

“…The results of the prevalence of scabious in cats from the study during January-February 2021 in the 2020 period were 9.5%, and the analysis of the association (Chi-Square) and the increased (Odds Ratio) of factors including breed, age, sex on the risk of scabious in cats were not significance / absent influence, The probability of error obtained is outside the tolerance set by the researcher, so the results are not significant (p>0,05).…”
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Machine learning model optimization for compressional sonic log prediction using well logs in Shahd SE field, Western Desert, Egypt by Khaled Saleh, Walid M. Mabrouk, Ahmed Metwally

“…Additionally, feature engineering and data cleaning significantly improve model performance, while input scaling is essential for SVM, KNN, and DNN models. …”
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Improved gated recurrent unit-based osteosarcoma prediction on histology images: a meta-heuristic-oriented optimization concept by S. Prabakaran, S. Mary Praveena

“…From the segmented images, the features are extracted by the linear discriminant analysis (LDA) approach. These extracted features undergo the final prediction phase that is accomplished by the novel improved recurrent gated recurrent unit (IGRU), in which the parameter tuning of GRU is accomplished by the osprey optimization algorithm (OOA) with the consideration of error minimization as the major objective function. …”
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An Improved Empirical Model for Estimation of Temperature Effect on Performance of Photovoltaic Modules by Abdul Rehman Jatoi, Saleem Raza Samo, Abdul Qayoom Jakhrani

“…The model has been developed by fitting of one year experimental data using the least squares method. The estimated results of the developed model were validated with real-time data (winter and summer season) and a comparison of other existing model estimates using error analysis with 95% confidence interval. …”
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Construction of a Chemical Kinetic Mechanism of Five-Component Surrogate Fuel for RP-3 Kerosene by Changxuan Dai, Zhaolei Zheng, Qin Chen

“…Whether under normal pressure or high pressure, the relative error between the simulation data and the experimental data was within ±5%. …”
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Highly concentrated iron ore slurry flow through pipeline with and without chemical additive; part II: 3d cfd modelling by Mishra Stuti, Kaushal Deo Raj

“…Based on comparison with experimental data, it is observed that the 3D CFD model can predict the pressure drop with an error band of ±30%. …”
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Lamb wave ultrasonic testing technology for diagnosis and prediction of hidden cracks in metal structures by Dawen Yao, Peiwen Meng, Shuqi Li, Jinggang Xu

“…Abstract In the field of traditional hidden crack detection in metal structures, detection technologies are often limited by low sensitivity and imprecise data analysis. To overcome these challenges, the advanced Lamb wave ultrasonic testing technology is applied in this article. …”
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