GIS-Based Landslide Susceptibility Mapping Using Frequency Ratio and Shannon Entropy Models in Dejen District, Northwestern Ethiopia by Abinet Addis

“…A GIS-based study has been carried out to map areas landslide susceptibility using both frequency ratio (FR) and Shannon entropy (SE) bivariate statistical models. A total of 270 landslides were identified and classified randomly into training landslides datasets (70%) and the remaining (30%) of landslides datasets were used for validation purpose. …”
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A Dynamic Intrusion Detection System Based on Multivariate Hotelling’s T2 Statistics Approach for Network Environments by Aneetha Avalappampatty Sivasamy, Bose Sundan

“…Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling’s T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. …”
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A Study on the Holding Capacity Safety Factors for Torpedo Anchors by Luís V. S. Sagrilo, José Renato M. de Sousa, Edison C. P. Lima, Elisabeth C. Porto, Jane V. V. Fernandes

“…This paper presents a study on the calibration of reliability-based safety factors for the design of torpedo anchors considering the statistical model uncertainty evaluated using results from experimental tests and their correspondent finite-element-based numerical predictions. …”
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A New Truncated Muth Generated Family of Distributions with Applications by Abdullah M. Almarashi, Farrukh Jamal, Christophe Chesneau, Mohammed Elgarhy

“…In recent years, the Muth distribution has been used for the construction of accurate statistical models, with applications in various applied fields. …”
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Advanced Genetic Algorithms for Optimal Battery Siting: A Practical Methodology for Distribution System Operators by Edward Alejandro Ortiz, Josimar Tello-Maita, David Celeita, Agustin Marulanda Guerra

“…By incorporating historical data on demand and network failures, the algorithm generates statistical models that inform the optimization process. …”
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Investigating the Feasibility of Statistically Measuring Anxiety using Wireless Electromyography Sensor via Wireless Personal Communication by Ikram-e-Khuda, Tahira Rafique, Maria Amjad, Syed Sheraz Ul Hasan Mohani

“…Analysis showed significant difference in EMG activity between stresses and unstressed states. The obtained statistical model thus provided a true measure of anxiety with linear coefficients that are statistically significant at 95% confidence interval (CI). …”
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Indoor Positioning in Wireless Local Area Networks with Online Path-Loss Parameter Estimation by Luigi Bruno, Paolo Addesso, Rocco Restaino

“…It is based on a Sequential Monte Carlo realization of the optimal Bayesian estimation scheme, whose functioning is improved by exploiting the Rao-Blackwellization rationale. Two key statistical models for RSS characterization are deeply analyzed, by presenting effective implementations of the proposed scheme and by assessing the positioning accuracy by extensive computer experiments. …”
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Unsupervised machine and deep learning methods for structural damage detection: A comparative study by Zilong Wang, Young‐Jin Cha

“…The key concept behind unsupervised novelty detection in this article is that only normal data from undamaged/baseline structural scenarios are required to train statistical models with these methods. Then, these trained models are used to identify abnormal testing data from damaged scenarios. …”
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Research on the Application of Reinforcement Learning in Traffic Flow Prediction by Hu Yiquan

“…However, traditional statistical models and prediction methods based on historical data exhibit many limitations when dealing with complex, dynamic, and nonlinear traffic flow data. …”
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Research on Monthly Runoff Forecast in Beijiang River Basin Based on Multi-model Ensemble Method by ZHONG Yixuan, LIAO Xiaolong, QUAN Xujian, YI Ling, CHEN Yan, LI Yuanyuan, XUE Jiao

“…The accuracy of the monthly runoff forecast plays a fairly important role in aspects such as optimal allocation of water resources,flood control and drought relief in a basin,water dispatching,and power generation optimization of reservoir groups.The commonly used methods for the monthly runoff forecast mainly include water balance models,mathematical statistics models,and artificial neural networks.Studies have shown that any single model cannot achieve the optimal monthly runoff forecast.Therefore,the multi-model ensemble method provides an effective way to eliminate model uncertainty and improve the accuracy of the monthly runoff forecast.Specifically,the research takes Pingshi,Lishi,Hengshi,and Shijiao stations in the Beijiang River Basin as the research object to analyze and compare the effects of the seasonal auto-regressive (SAR) model,two-parameter monthly water balance (TPMWB) model,and artificial neural network (ANN) model.Then,the multi-model ensemble method for the above-mentioned stations is proposed on the basis of the Bayesian model averaging (BMA) method.The research results reveal that compared with any of the three models,the multi-model ensemble method has significantly improved the accuracy of the monthly runoff forecast with a higher determination coefficient (DC) and a lower mean absolute percentage error (MAPE),and thus it can provide better support for decisions in dispatching in the basin.…”
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Modeling sickness absence data: A scoping review. by Tom Duchemin, Mounia N Hocine

“…We followed the PRISMA methodology for scoping reviews and searched Medline, World of Science, Science Direct, Psycinfo and EconLit for publications using statistical modeling for explaining or predicting sick leave at the individual level. …”
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Effect of Covid-19 Pandemic on Recreational Awareness and Quality of Life by Mehmet Demirel, Alper Kaya, Davut Budak, Mustafa Sabır Bozoğlu, Yusuf Er

“…Since the data did not have a normal distribution, that is, non-parametric distribution, besides descriptive statistical models, Mann Whitney U, Kruskal Wallis test, and correlation analysis were applied. …”
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Modeling the effect of extrusion parameters on density of biomass pellet using artificial neural network by Abedin Zafari, Mohammad Hossein Kianmehr, Rahman Abdolahzadeh

“…The ANN model was found to have higher predictive capability than the statistical model.…”
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Capacity Estimation of the Very Short-Range Electromagnetic Underwater Channel Based on Measurements by Jesús López-Fernández, Unai Fernández-Plazaola, Jose F. Paris

“…Because of water movement, the nonstatic position of the vehicle when the transmission occurs means that the channel is regarded as randomly time-variant. A statistical model is proposed and the ergodic capacity is calculated for a 7 MHz bandwidth channel at distances ranging from 0.5 m to 5 m as well as for different values of transmitter power. …”
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An Analysis of Space Inequalities in Utilization of Urban in Abadan Services Oil by sadegh besharatifar, kohdadd mobinizadeh

“…For data collection using documentary and field methods, using service and socio-economic indicators as well as using quantitative models and statistics models Space is in the year 1397. The purpose of the research is to analyze and evaluate the spatial inequalities in utilization of urban services in Abadan oil. …”
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Uncertainty Quantification for a Hydraulic Fracture Geometry: Application to Woodford Shale Data by Batoul M. Gisler

“…The good agreement between the statistical model and field observations shows that the probability density curve can provide a reliable insight into the optimal proppant size.…”
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The pressure of academic stress and self-efficacy among student by Ilham Khairi Siregar, Permata Sari, Mohamad Rizal Pautina, Ryan Hidayat Rafiola

“…The sampling technique used is proportional to stratified soak sampling. The statistical model used in this study is the Pearson correlation. …”
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Developing Roadway Safety Models for Winter Weather Conditions Using a Feature Selection Algorithm by Bryce Hallmark, Jing Dong

“…When developing statistical models using such large-scale multivariate datasets, one of the challenges is to determine which explanatory variables should be included in the model. …”
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Depth-corrected multi-factor dissection of chromatin accessibility for scATAC-seq data with PACS by Zhen Miao, Jianqiao Wang, Kernyu Park, Da Kuang, Junhyong Kim

“…To address these problems, we present a zero-adjusted statistical model, Probability model of Accessible Chromatin of Single cells (PACS), that allows complex hypothesis testing of accessibility-modulating factors while accounting for sparse and incomplete data. …”
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Analytical Quality by Design approach in development and optimization of HPLC method for assay of angiotensin – converting enzyme inhibitor in tablets by Veronika Popovska Jakimovska, Ana Atanasova, Filip Gogu, Maja Stevanoska, Emilija Arsovska Popovska, Packa Antovska, Suzana Trajkovic Jolevska, Jasmina Tonic Ribarska

“…The aim of this study was to implement a software which uses experimental design plans as an efficient and fast tool for development of method for quantitative determination of content of ACE inhibitor in tablets. Using statistical models in method development and optimization, the effect of each factor on responses of interest were calculated and the data were used to find the optimal chromatographic conditions. …”
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