Verification of the method for prediction of the equivalent level of freely flowing traffic noise by R. MAKAREWICZ, J. JARZĘCKI

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New multifactor spatial prediction method based on Bayesian maximum entropy by YANG Yong, ZHANG Chutian, HE Liyuan

“…Six environmental factors closely related with soil organic matter content, including relative elevation (Hr), topographic relief (QFD), slope (β), variable rate of slope (SOS), topographic wetness index (ψ) and surface roughness (M), were used as auxiliary variables to produce soft data for prediction. To evaluate the advantages of this method and to compare with Kriging for different sampling density, the analysis and comparison were conducted on two groups of sampling points, which were a group with high spatial density (group Ⅰ, 330 points) and the other with low spatial density (group Ⅱ, 100 points) respectively. …”
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Intelligent prediction method of network performance based on graph neural network by Yijiang LI, Huibiao YE, Renhua XIE, Jiali LOU, Danna ZHUANG, Chuanhuang LI

“…There are some problems in the traditional network performance prediction technology, such as incomplete network state acquisition and poor accuracy of network performance evaluation.Combined with the characteristics of graph neural network learning and reasoning network relational data and the captured global information of the network, on the basis of the current network performance prediction methods, an intelligent prediction method of network performance based on graph neural network was proposed.Aiming at the complex network information, through the research of network system abstraction and network performance modeling, the network information can be transformed into the graph space convolution was used to process the message passing process of graph network nodes to realize the relationship reasoning between network information.The graph neural network model for network performance prediction was studied, and a graph neural network architecture which could deal with traffic matrix, network topology, routing strategy and node configuration was proposed.Finally, the experiments show that the model can better achieve accurate prediction of the network performance including delay, jitter and packet loss rate.…”
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Energy Prediction Method for Metro HVAC Systems based on the ARMA Model by Huang Ronggeng, Long Jing, Pan Zhigang, Chen Huanxin, Liu Jiangyan, Liu Jiahui, Li Zhengfei

“…This paper proposes an energy consumption-prediction method for metro heating, ventilation and air-conditioning (HVAC) systems based on an auto-regressive moving average (ARMA) model using a time-series data analysis. …”
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Path Prediction Method for Effective Sensor Filtering in Sensor Registry System by Sukhoon Lee, Dongwon Jeong, Doo-Kwon Baik, Dae-Kyoo Kim

“…We implement the method and the implementation and its evaluation confirm the improvement of time and accuracy for processing sensor information.…”
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Durability Prediction Method of Concrete Soil Based on Deep Belief Network by Xiao Tian, Niankun Zhu

“…The prediction of concrete durability discussed here has important guiding significance for the improvement of concrete durability test methods and the improvement of concrete durability evaluation standards in China.…”
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Landing Gear Aerodynamic Noise Prediction Using Building-Cube Method by Daisuke Sasaki, Deguchi Akihito, Hiroshi Onda, Kazuhiro Nakahashi

“…Landing gear noise prediction method is developed using Building-Cube Method (BCM). …”
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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The suggested hybrid model's performance is evaluated and compared to alternative forecasting methods. …”
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A Method for Predicting the Surface Subsidence Duration and the Maximum Subsidence Velocity by Yanjun Zhang, Fei Wang, Yueguan Yan, Yuanhao Zhu, Linda Dai, Jiayuan Kong

“…Therefore, a new prediction method was established in this paper. Measured data from 30 mining areas were used for verification. …”
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Beyond admission scores: evaluating GAT, SAAT, and English proficiency as predictors of physics performance in health science education by Abdulaziz Althewini

“…In Saudi Arabia, standardized cognitive assessments—such as the General Aptitude Test (GAT) and Scholastic Achievement Admission Test (SAAT)—are widely used for admissions. This study evaluates the predictive validity of these tests, alongside English proficiency measures, in forecasting student performance in an introductory physics course—a foundational subject in science-based programs.MethodsThis retrospective, quantitative study analyzed data from 250 Saudi college students enrolled in a required introductory physics course. …”
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Evaluating variable selection methods for multivariable regression models: A simulation study protocol. by Theresa Ullmann, Georg Heinze, Lorena Hafermann, Christine Schilhart-Wallisch, Daniela Dunkler, for TG2 of the STRATOS initiative

“…These methods will be compared with respect to false inclusion and/or exclusion of variables, consequences on bias and variance of the estimated regression coefficients, the validity of the confidence intervals for the coefficients, the accuracy of the estimated variable importance ranking, and the predictive performance of the selected models. …”
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Predicting Ocean Current Temperature Off the East Coast of America with XGBoost and Random Forest Algorithms Using Rstudio by Lulut Alfaris, Anas Noor Firdaus, Ukta Indra Nyuswantoro, Ruben Cornelius Siagian, Aldi Cahya Muhammad, Rohana Hassan, Rodulfo T. Aunzo, Jr., Reza Ariefka

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Prediction of Work-relatedness of Shoulder Musculoskeletal Disorders as by Using Machine Learning by Saemi Jung, Bogeum Kim, Yoon-Ji Kim, Eun-Soo Lee, Dongmug Kang, Youngki Kim

“…Additionally, machine learning algorithms, including logistic regression, support vector machine, decision tree, random forest, and the XGBoost, were utilized to construct prediction models for work-relatedness assessment. Results: The performance of each model was evaluated. …”
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Evaluating the Accuracy of Land-Use Change Models for Predicting Vegetation Loss Across Brazilian Biomes by Macleidi Varnier, Eliseu José Weber

“…The predicted maps were evaluated by comparing them with reference land-use maps using rigorous accuracy methods. …”
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Evaluating combinations of rainfall datasets and optimization techniques for improved hydrological predictions using the SWAT+ model by Mahesh R. Tapas, Randall Etheridge, Thanh-Nhan-Duc Tran, Manh-Hung Le, Brian Hinckley, Van Tam Nguyen, Venkataraman Lakshmi

“…The combination of the GPM IMERG dataset and the GLUE method proved most effective, offering valuable guidance for selecting optimal datasets and methods to enhance prediction accuracy in complex watersheds.…”
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Evaluation of the Desire to Avoid Pregnancy Scale in the UK: a psychometric analysis including predictive validity by Geraldine Barrett, Jennifer Hall, Corinne Rocca

“…Objectives To evaluate the psychometric performance, including predictive validity, of a UK version of the Desire to Avoid Pregnancy (DAP) scale.Design Prospective cohort study for psychometric evaluation.Setting UK.Participants Women in the UK aged 15 years to menopause, who were not pregnant at the time of recruitment in October 2018, were eligible. 994 women completed the baseline survey and 90.2% of women eligible for the 12-month survey participated.Primary and secondary outcome measures The DAP scale was assessed according to key measurement properties of validity (construct (structural and hypothesis testing) and criterion (predictive)), reliability (internal consistency using Cronbach’s alpha and test–retest using intraclass correlation coefficients, ICC) and differential item functioning. …”
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Methodical basis for assessing the development innovative capacity industrial enterprise by S. K. Almrshed, A. S. Bishin

“…The article describes the essence of the innovation potential of the enterprise, identifies its main components. For the evaluation and selection of directions for the development of innovation potential, it is proposed to use the method of informal (expert) system analysis. …”
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Evaluating Explainable AI Methods in Deep Learning Models for Early Detection of Cerebral Palsy by Kimji N. Pellano, Inga Strumke, Daniel Groos, Lars Adde, Espen F. Alexander Ihlen

“…This paper tests the reliability and applicability of Explainable AI (XAI) methods using a deep learning method that predicts CP by analyzing skeletal data extracted from video recordings of infant movements. …”
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Evaluating variant pathogenicity prediction tools to establish African inclusive guidelines for germline genetic testing by Kangping Zhou, Kazzem Gheybi, Pamela X. Y. Soh, Vanessa M. Hayes

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Evaluating the Validity of Risk Scoring in Predicting Pacemaker Rates following Transcatheter Aortic Valve Replacement by Alexander M. Spring, Michael A. Catalano, Vikram Prasad, Bruce Rutkin, Elana Koss, Alan Hartman, Pey-Jen Yu

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