Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU by Jinwei Wang, Xirong Ma, Yuanping Zhu, Jizhou Sun

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An Intelligence Optimized Rolling Grey Forecasting Model Fitting to Small Economic Dataset by Li Liu, Qianru Wang, Ming Liu, Lian Li

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Model-fitting approach for methylene blue dye adsorption on and seeds-derived adsorbents by Sunanda Sharma, DP Tiwari, KK Pant

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Kinetic Analysis of Low-Rank Coal Pyrolysis by Model-Free and Model-Fitting Methods by Qiuli Zhang, Min Luo, Long Yan, Aiwu Yang, Xiangrong Hui

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Analysis of Model Fit and Test Information on Otis-Lennon School Ability Test Using Item Response Theory by Rey-Mark Basagre

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Kinetic Analysis of the Thermal Decomposition of Polymer-Bonded Explosive Based on PETN: Model-Fitting Method and Isoconversional Method by Trung Toan Nguyen, Duc Nhan Phan, Van Thom Do, Hoang Nam Nguyen

“…Both model-free (isoconversional) and model-fitting methods were applied to determine the kinetic parameters of the thermal decomposition. …”
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Modelling seasonal influenza in Israel by Oren Barnea, Rami Yaari, Guy Katriel, Lewi Stone

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An exact approach to calibrating infectious disease models to surveillance data: The case of HIV and HSV-2 by David J. Gerberry

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Posttraumatic stress disorder in disaster-exposed youth: examining diagnostic concordance and model fit using ICD-11 and DSM-5 criteria by BreAnne A. Danzi, Ellen A. Knowles, Rachel C. Bock

“…The ITQ-CG exhibited excellent model fit and was associated with several constructs important to PTSD.…”
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The role of a vaccine booster for a fractional order model of the dynamic of COVID-19: a case study in Thailand by Puntipa Pongsumpun, Puntani Pongsumpun, I-Ming Tang, Jiraporn Lamwong

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Mathematical Modeling of Tuberculosis Transmission Dynamics With Reinfection and Optimal Control by Francis Oketch Ochieng

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Fitting the Integrated Model of Location of the Pre-urban Areas with Emphasis on Environmental Balance by Atefeh Moradi, Mariam Daneshvar, Seyed Abdol-Hadi Daneshpour, Hooman Bahmanpour

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Basic assumptions, core connotations, and path methods of model modification—using confirmatory factor analysis as an example by Zhangbo Xiong, Huixian Xia, Jianjun Ni, Hongzhen Hu

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Linear discriminant analysis in network traffic modeling by ZHANG Bing-yi, BIAN Yu-lan, ZHANG Hong-ke, SUN Ya-min

“…It was not easy to give an accurate judgment of whether the traffic model fitting the actual traffic. The common method was to compare the Hurst parameter, data histogram and autocorrelation function. …”
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The Low Temperature Specific Heat of Pr0.65Ca0.35MnO3 by Zhiyong Han, Zhenzhu Jing

“…To get the contribution of phonon to the specific heat precisely, the lattice specific heat is calculated by Debye model fitting. Results confirm that the low temperature specific heat of Pr0.65Ca0.35MnO3 is related to the itinerant electrons in ferromagnetic clusters and the disorder in the sample.…”
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Research on wireless coverage area detection technology for 5G mobile communication networks by Hongjun Wang, Yu Zhou, Wenhao Sha

“…To overcome the human subjectivity of the traditional model fitting when performing the variation function fitting in the interpolation estimation, a support vector regression algorithm is employed. …”
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Multi-dimensional time series anomaly detection method based on VAE-WGAN by Xueyuan DUAN, Yu FU, Kun WANG

“…As the deficiency of learning ability of traditional semi-supervised depth anomaly detection model to unbalanced multidimensional data distribution and the difficulty of model training, a multi-dimensional time series anomaly detection method based on VAE-WGAN architecture was proposed.VAE was used as a generator of WGAN.The Wasserstein distance was used as a measure between the model fitting distribution and the real distribution of the data to be measured, complex and high-dimensional data distributions could be learned.A sliding window was applied to divide the time series, the normal sequence data were used to train the model.According to the abnormal score of the waiting test sequence in the trained model, the anomaly was judged with adaptive threshold technology.The experimental results show that the model is easy to train and stable, and has obvious improvement over the existing generative anomaly detection model in accuracy, recall rate, F1 score and other anomaly detection performance indicators.…”
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REMAINING USEFUL LIFE OF ROLLING BEARING BASED ON t⁃SNE by ZHONG JianHua, HUANG Cong, ZHONG ShunCong, XIAO ShunGen

“…Due to the limited bearing degradation data under actual working conditions,it is impossible to obtain enough degradation data to train the neural network,it is difficult to obtain good prediction results in the deep learning network,so a new fusion method was proposed.Firstly,the features of the original vibration signal was extracted,dozens of dimensional features were obtained through the ensemble empirical mode decomposition(EEMD)and the singular value decomposition(SVD),and the effective features such as kurtosis and mean value commonly used in remaining useful life prediction were added,then the decision tree to filter out 15⁃dimensional features was used the data was obtained by double exponential model fitting and the degraded signal was reduced to a linear trend through t⁃SNE.The linear degradation trend has better generalization in prediction than the exponential trend,and the prediction accuracy is superior to support veotor regression(SVR)and deep belief network(DBN)model.…”
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RELIABILITY ANALYSIS OF RIGHT CENSORED WEIBULL DISTRIBUTION BASED ON GENETIC ALGORITHM by ZHANG Qing, ZHENG Yan, WANG Xuan, MA Min, WANG WenBo

“…Finally,with the aid of KS test,this paper tries to verify the degree of model fitting,proving that it is appropriate to employ the right censoring three-parameter Weibull distribution model. …”
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Hardening Concrete Exposed to Realistic Curing Temperature Regimes and Restraint Conditions: Advanced Testing and Design Methodology by Anja Estensen Klausen, Terje Kanstad, Øyvind Bjøntegaard

“…The basis of the methodology is to define and describe the material properties of a given concrete through laboratory testing and succeeding model fitting. The obtained material parameters are then evaluated and calibrated by comparing (1) stress development measured in a Temperature-Stress Testing Machine with (2) stress development calculated by using the obtained material properties and various multiphysical EAC calculation approaches. …”
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