Correlations of Strength and Elastic Modulus of Cohesive Soil with SPT in Bakrajo Region-Kurdistan of Iraq by Kamal Ahmad Rashed

“…Seventeen (17) high-quality undisturbed samples were collected and tested in the laboratory, and the results were then used to develop predictive models using simple regression analysis and multi-linear regression analysis. …”
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Time-coexpress: temporal trajectory modeling of dynamic gene co-expression patterns using single-cell transcriptomics data by Shuyi Yang, Anderson Bussing, Giampiero Marra, Michelle L. Brinkmeier, Sally A. Camper, Shannon W. Davis, Yen-Yi Ho

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Analysis of active learning in management engineering: A study at EDEM Business School by Vicente Asensio, Irene Canals, Claudia Silvestre

Subjects: “…active learning, linear regression models, stem, continuous assessment, learning results…”
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Statistical modeling and application of machine learning for antibiotic degradation using UV/persulfate-peroxide based advanced oxidation process by Musfekur Rahman Dihan, Md. Ashraful Alam, Surya Akter, Md. Abdul Gafur, Md. Shahinoor Islam

“…The Shapley values of ANN and estimated predictor importance of LSBoost indicated that PSconc and time have the highest impact on % removal and initial pH, and PSconc on final pH modeling. Initiating the ML modeling approach for the homogeneous AOPs with this study, further research is needed to come out with more accurate ML prediction models with larger data sets, higher numbers of variables, and real wastewater samples.…”
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Evaluation of Parametric and Non-Parametric Models in Estimating Canopy Cover Density of Zagros Forests Using Remote Sensing and Machine Learning by Sajad Alimahmoodi Sarab, MohamadHadi Moayery, MOhammad Mirzavand, Shaban Shataee Jouibary, Alireza Rashki

“…To compare the performance of these two models, the metrics RMSE, RMSE%, and R² were utilized.Results: The results indicated that the MLR model achieved an R² value of 0.54 and an RMSE% of 10.4 at a 0.05 confidence level, while the MLP model yielded an R² of 0.82 and an RMSE% of 4.5.Conclusions: The comparative analysis demonstrated that the artificial neural network (MLP) provided more accurate estimates with lower error rates than the multiple linear regression (MLR) method in predicting vegetation density.…”
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Macro-Level Modeling of Traffic Crash Fatalities at the Scene: Insights for Road Safety by Carlos Fabricio Assunção da Silva, Mauricio Oliveira de Andrade, Cintia Campos, Alex Mota dos Santos, Hélio da Silva Queiroz Júnior, Viviane Adriano Falcão

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Threshold detection by fitting segmented regression models in Microsoft Excel by Amy J Hopper, Angus M Brown

“…•Experimental data that follow a model comprising two distinct functions that meet at an unknown transition point is amenable to segmented regression analysis.…”
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Study of linear and nonlinear isotherm and kinetic parameters of hexavalent chromium adsorption onto reduced graphene oxide coated iron oxide by Selim Gürsoy, Nagehan Kübra Zeytinci, Buse Tuğba Zaman, Sezgin Bakırdere, Elif Öztürk Er

“…Adsorption equilibrium mechanism was analyzed through the application of Langmuir and Freundlich isotherm models, utilizing both linear and nonlinear regression approaches. …”
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Unsupervised Anomaly Detection in Spatio‐Temporal Stream Network Sensor Data by Edgar Santos‐Fernandez, Jay M. Ver Hoef, Erin E. Peterson, James McGree, Cesar A. Villa, Catherine Leigh, Ryan Turner, Cameron Roberts, Kerrie Mengersen

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Evaluating machine leaning algorithms for accuracy, stability, and among-predictors discriminability in modeling species-richness across ten datasets by Yong Cao, Tyler E. Schartel, David C. Houghton, Jared Ross, Dana M. Infante

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Pedestrian gap acceptance behavior at unsignalized mid-block crossing under mixed traffic conditions by Satanan Piyalungka, Kunnawee Kanitpong, Ampol Karoonsoontawong

“…This study analyzed the critical gap and dilemma zone for pedestrians crossing unsignalized mid-block crosswalks in Bangkok, Thailand, utilizing Raff's and logit methods. Multiple linear regression and binary logit regression models were developed to identify the factors affecting accepted gap size and gap acceptance behavior. …”
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Evaluation of ground based spectral imaging for real time maize biomass monitoring by Andrea Szabó, Andrea Szabó, Nxumalo Gift Siphiwe, Nxumalo Gift Siphiwe, Erika Buday-Bódi, Erika Buday-Bódi, Blessing Ademola, János Tamás, János Tamás, Attila Nagy, Attila Nagy

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Estimation of Beginning Points of Cross-Shore Sandbars Using Artificial Neural Network by Mert SABANCIOGLU, Mustafa DEMIRCI, Yunus Ziya KAYA

“…When the results were compared, it was concluded that the ANN model gave better results than traditional statistical methods. …”
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A comparison among Different Methods for Estimating Regression Parameters with Autocorrelation Problem under Exponentially Distributed Error by Ahmed Dheyab Ahmed, Baydaa Ismael Abdulwahhab, Ebtisam Karim Abdulah

“…In this paper the multiple linear regression model and three covariates were studied in the presence of the problem of auto-correlation of errors when the random error distributed the distribution of exponential. …”
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Performance of the Ridge and Liu Estimators in the zero-inflated Bell Regression Model by Zakariya Yahya Algamal, Adewale F. Lukman, Mohamed R. Abonazel, Fuad A. Awwad

“…The Poisson regression model is popularly used to model count data. …”
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Predicting flavonoid physicochemical properties using topological indices and regression modeling by Huili Li, Shamaila Yousaf, Komal Shahzadi, Sobhy M. M. Ibrahim, Adnan Aslam, Guoping Zhang, Keneni Abera Tola

“…This study leverages degree-based topological indices (TIs) to predict six physicochemical properties of sixty flavonoids using linear, quadratic, and logarithmic regression models. …”
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MODELING LONGITUDINAL MEASUREMENTS OF CLINICAL AND EPIDEMIOLOGICAL PARAMETERS USING JOINPOINT REGRESSION by Mihaela Moscalu, Ionela-Lăcrămioara Șerban, Norin Forna, Mihaela Pundiche, Loredana Mitran, Madalina-Elena Datcu, Nicolae Șerban Dragomir, Alin Constantin Pînzariu

“…Materials and methods The Joinpoint regression model was employed in integration with joint longitudinal–time-to-event models, as well as with Bayesian extensions. …”
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The effect of collinearity between observed and model derived training variables on estuarine algal species distribution models by Dante M.L. Horemans, Jennifer C. Lin, Marjorie A.M. Friedrichs, Pierre St-Laurent, Raleigh R. Hood, Christopher W. Brown

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Forecasting model to predict the first occurrence of Scaphoideus titanus nymphal stages in selected locations in Austria by Kerstin Kolkmann, Gudrun Strauss, Josef Eitzinger, Sylvia Blümel

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