Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (Neuro-Fuzzy Network) Method in Forest Degradation (Case Study: Sari County) by somayeh mehrabadi

“…The mean squared error (MSE) was used to evaluate the performance of models, which was 0.0535, 0.0704, and 0.0908 for the perceptron neural network in the Levenberg-Marquardt, Bayesian regularization, and scaled conjugate gradient algorithms, respectively. …”
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Data Mining Mycobacterium tuberculosis Pathogenic Gene Transcription Factors and Their Regulatory Network Nodes by Guangxin Yuan, Yu Bai, Yuhang Zhang, Guangyu Xu

“…Linear model-experience Bayesian statistics using the Limma package in R combined with t-tests were applied for nonspecific filtration of the expression profile data, and the differentially expressed human genes were determined. …”
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PK/PD-Guided Strategies for Appropriate Antibiotic Use in the Era of Antimicrobial Resistance by Tetsushu Onita, Noriyuki Ishihara, Takahisa Yano

“…Third, we explore clinical applications, including nomogram-based dosing strategies, Bayesian estimation, and emerging artificial intelligence applications, for real-time dose optimization. …”
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Coping with Complexity When Predicting Surface Roughness in Milling Processes: Hybrid Incremental Model with Optimal Parametrization by Gerardo Beruvides, Fernando Castaño, Rodolfo E. Haber, Ramón Quiza, Alberto Villalonga

“…The second study also corroborates that hybrid incremental model plus simulated annealing is better than a Bayesian network and a multilayer perceptron for correctly predicting the surface roughness.…”
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Quantifying Uncertainty in State Estimation: The MoK-FoBS Method via Interval Analysis by Yuting Chen, Ning Zhou, Ziang Zhang

“…The Bayesian framework is conventionally adopted in power system static state estimation (SSE) to quantify uncertainty via probability density functions (PDFs). …”
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Location Estimation in a Smart Home: System Implementation and Evaluation Using Experimental Data by Youcef Rahal, Hélène Pigot, Philippe Mabilleau

“…This paper proposes a solution to localize the occupant thanks to Bayesian filtering and a set of anonymous sensors disseminated throughout the house. …”
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Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification by Mhd Saeed Sharif, Maysam Abbod, Abbes Amira, Habib Zaidi

“…The first methodology is a competitive neural network (CNN), whereas the second one is based on learning vector quantisation neural network (LVQNN). Furthermore, Bayesian information criterion (BIC) is used in this system to assess the optimal number of classes for each PET data set and assist the ANN blocks to achieve accurate analysis by providing the best number of classes. …”
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A comparative study of interpolation methods for the development of ore distribution maps by Mahinaz M. Shawky

“…A comparative study between four different geostatistical interpolation techniques: Ordinary Kriging (OK), Simple Kriging (SK), Universal Kriging (UK) and Empirical Bayesian Kriging (EBK); and four deterministic techniques: Inverse Distance Weighting (IDW), Global Polynomial Interpolation (GPI), Radial Basis Function (RBF), and Local Polynomial Interpolation (LPI) were applied. …”
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Fitness landscapes of human microsatellites. by Ryan J Haasl, Bret A Payseur

“…Using a random forests approach to approximate Bayesian computation, we fit these models to carefully chosen microsatellites genotyped in 200 humans from a diverse collection of eight populations. …”
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A conceptual replication of an implicit test of grammatical gender effects on inanimate concepts by Devyani Mahajan, Frank H. Durgin

“…The results of both studies provided evidence against the grammatical-gender hypothesis. Bayesian tests of both studies strongly favored the null hypothesis that there were no grammatical gender effects on implicit measures of perceived potency.…”
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Exploring the Influence of Vicarious Experiences in Teaching with Digital Technology on Pre-Service Science Teachers’ Digitalization-Related Affective-Motivational Dispositions by Alexander Aumann, Robert Grassinger, Holger Weitzel

“…Data were collected pre- and post-intervention and analyzed using Bayesian Path Analysis to examine the relationships between the constructs. …”
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Into the latent space of capacitive sensors: interpolation and synthetic data generation using variational autoencoders by Miguel Monteagudo Honrubia, Francisco Javier Herraiz-Martínez, Javier Matanza Domingo

“…For this reason, this paper proposes a search method based on Bayesian Optimization that automatically explores the latent space. …”
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Optimization of Clinical Nursing Management System Based on Data Mining by Yongxia Chen

“…Therefore, this research is based on the framework of the hospital’s existing clinical care system, using data mining technology to improve the Bayesian algorithm and data preprocessing, optimizes the design of functional modules in the clinical nursing management system, and optimizes the patient information management, medical order management, medical order execution management, basic information and expense management, nursing execution process management, system and data management, barcode management, physical sign management, WAP information management, and other subsystems in the clinical nursing information management system. …”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…Fine-tuning the hyperparameters with the help of Bayesian optimization to obtain the best model performance is another important thing that we do in our model. …”
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Introduction risk of fire ants through container cargo in ports: Data integration approach considering a logistic network. by Shota Homma, Daisuke Murakami, Shinya Hosokawa, Koji Kanefuji

“…A relationship between locations based on logistics connectivity is assumed rather than the spatial correlation based on the geographical distance used in the past. Hierarchical Bayesian models integrating data through the network were implemented for two fire ant species (Solenopsis invicta and Solenopsis geminata) observed in Japanese ports. …”
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Comparative effectiveness of non-pharmacological therapies for postoperative cognitive dysfunction: Protocol for a systematic review and network meta-analysis. by Kexin Wu, Qiongnan Bao, Jun Huang, Shanshan Sun, Yaqin Li, Xinyue Zhang, Manze Xia, Zhenghong Chen, Jin Yao, Wanqi Zhong, Zihan Yin, Fanrong Liang

“…The risk of bias will be assessed using the revised Risk of Bias Assessment Tool. Pairwise and Bayesian network meta-analyses will be performed using RevMan, STATA, and Aggregate Data Drug Information System statistical software. …”
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Computational analysis of SARS-CoV-2, SARS-CoV, and MERS-CoV genome using MEGA by Vipan Kumar Sohpal

“…In this paper, the genomic data accessed from National Center for Biotechnology Information (NCBI) through Molecular Evolutionary Genetic Analysis (MEGA) for statistical analysis. Firstly, the Bayesian information criterion (BIC) and Akaike information criterion (AICc) are used to evaluate the best substitution pattern. …”
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Spatiotemporal Trends and Distributions of Malaria Incidence in the Northwest Ethiopia by Teshager Zerihun Nigussie, Temesgen T. Zewotir, Essey Kebede Muluneh

“…The data were analyzed using count regression spatiotemporal models under the Bayesian setups, and parameters were estimated using integrated nested Laplace approximations (INLA). …”
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Should a Sentinel Node Biopsy Be Performed in Patients with High-Risk Breast Cancer? by Kenneth D. Westover, M. Brandon Westover, Eric P. Winer, Andrea L. Richardson, J. Dirk Iglehart, Rinaa S. Punglia

“…However, patients at high risk for nodal involvement based on clinical characteristics may remain at unacceptably high risk of axillary disease even after a negative SLN biopsy result. A Bayesian nomogram was designed to combine the probability of axillary disease prior to nodal biopsy with customized test characteristics for an SLN biopsy and provides the probability of axillary disease despite a negative SLN biopsy. …”
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Genetic diversity of Tulipa suaveolens Roth populations in Volgograd Province by T. A. Kritskaya, A. S. Kashin

“…Total subdivision of populations (FST) was 0.257; total gene flow (Nm) between populations was 0.723. According to Bayesian analysis and clustering with both UPGMA and Neighbor Joining methods, all the studied T. suaveolens samples from Volgograd Province make up a large genetic group: within that group none of the potential subgroups may be associated with a particular place of collecting. …”
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