Agricultural GDP exposure to drought and its machine learning-based prediction in the Jialing River Basin, China by Xinzhi Wang, Qingxia Lin, Zhiyong Wu, Yuliang Zhang, Changwen Li, Ji Liu, Shinan Zhang, Songyu Li

“…Finally, four machine learning methods (Bayesian, BiGRU, CLA, and MLP) were employed to predict hydrometeorological variables from 2021 to 2030, and the agricultural economic exposures to drought under five shared socioeconomic pathways (SSPs) were also predicted. …”
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Joint exposure to multiple air pollutants and residual cardiovascular risk in hypertension by Yalan Li, Wei Hong, Jingjing Wu, Jie Wang, Shiqi Liu, Hong Yuan, Jingjing Cai, Rujia Miao, Jiangang Wang, Yao Lu

“…The air pollution score analyses and Bayesian kernel machine regression suggested that combined exposure to multiple air pollutants had a positive association with the residual cardiovascular risk, and NO2 played a dominant role. …”
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Analysis and Prediction of the Interval Duration between the First and Second Accidents considering the Spatiotemporal Threshold by Fang Liu, Lanlan Zheng, Mingyang Li, Jinjun Tang

“…Traffic accident data set collected in Los Angeles city from February 2016 to June 2020 is used to validate prediction performance in this study. Bayesian method is applied to optimize the hyperparameters in the RF, while three evaluation indicators, including the Root Mean Squared Error (RMSE), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE), are used to estimate the prediction effect. …”
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Remaining Useful Life Prediction of High-Frequency Swing Self-Lubricating Liner by Xiuhong Hao, Shuqiang Wang, Mengfan Chen, Deng Pan

“…A degradation process model was established and the RUL was predicted online with the model parameter estimates based on the Bayesian updating strategy. Finally, examples were provided to elaborate the RUL prediction of the HSLL. …”
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Damage Detection of Refractory Based on Principle Component Analysis and Gaussian Mixture Model by Changming Liu, Di Zhou, Zhigang Wang, Dan Yang, Gangbing Song

“…Based on the proposed approach, the Gaussian mixture model was integrated with the Bayesian information criterion to group the AE signals into two damage categories, which accounted for 99% of all damage. …”
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Comparative safety profile of tyrosine kinase inhibitors in NSCLC: a network meta-analysis of hypertension and thrombotic risks by Mingming Tan, Chenwei Pu, Zhenzhen Wang, Chengwei Jin

“…BackgroundThis study examines the risks of hypertension and thrombotic events in NSCLC patients treated with Tyrosine Kinase Inhibitors (TKIs).ObjectiveTo compare the safety profiles of TKIs used in NSCLC treatment, focusing on hypertension and thrombotic risks.MethodsA comprehensive search identified randomized controlled trials evaluating the effects of TKIs in NSCLC patients. Bayesian network meta-analysis was employed to construct a comparative network of treatments.ResultsThirty studies involving 11,375 patients were included. …”
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Individual differences in event experiences and psychosocial factors as drivers for perceived linguistic change following occupational major life events by Wirtz Mason A., Pickl Simon, Pfenninger Simone E.

“…We analyzed survey data from 154 German-speaking adults in Austria who experienced (at least) one of these career-related MLEs. Results from Bayesian modeling showed that individual differences in event experiences (e.g., how stressful an MLE is perceived, how damaging an MLE is for one’s social status) alongside social factors such as varietal proficiency affect the degree of perceived MLE-related change in the sociolinguistic repertoire. …”
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Assessment and Classification of Service Learning: A Case Study of CS/EE Students by Han-Ying Kao, Yu-Tseng Wang, Chia-Hui Huang, Pao-Lien Lai, Jen-Yeu Chen

“…Furthermore, this study designs the knowledge model by Bayesian network (BN) classifiers and term frequency-inverse document frequency (TFIDF) for counseling students on the optimal choice of service learning.…”
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The Dynamic Effects of the Foreign Economic Shocks on the Korean Port Industry by Sung-A. Kim, Kapje Park, Chan-Ho Kim

“…This paper estimates the four foreign economic factors and the parameters of the model using the one-step Bayesian Gibbs sampling method. The findings of this study show that foreign economic activity statistically affects the freight volume of the Korean ports. …”
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Standardizing the Ignition Delay Time Measurements of Rapid Compression Machine: An Inverse Application of the Livengood–Wu Integral Method by Zhonghao Zhao, Yingtao Wu

“…The algorithm applies the Livengood–Wu integral method inversely and adopts a Bayesian approach to optimize the correlation parameters. …”
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More on mobility and sedentism: Changes in adaptation from Upper Paleolithic to Incipient Jomon, Tanegashima Island, southern Japan. by Kazuki Morisaki, Fumie Iizuka, Masami Izuho, Mark Aldenderfer

“…Our study evaluates long-term change in hunter-gatherer mobility on Tanegashima Island from the Upper Paleolithic to Incipient Jomon (ca.36,000-12,800 cal BP). Based on Bayesian age modelling, we performed diachronic analyses on lithic toolkit structure, lithic reduction technology, lithic raw material composition, and occupation intensity. …”
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Nonoperative treatment efficacy prognosis in acute small bowell obstruction by S. G. Shapovalyants, S. Ye. Larichev, Z. A. Zhemukhova, N. A. Soldatova, I. A. Smirnov

“…According to the designed integrated prognostic system with application of Bayesian statistical methods patients have been distributed into three prognostic groups. …”
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Competing Risks in Accelerated Life Testing: A Study on Step-Stress Models with Tampered Random Variables by Hanan Haj Ahmad, Ehab M. Almetwally, Dina A. Ramadan

“…Maximum-likelihood estimates for model parameters and tampering coefficients are derived from SSLT data, and some confidence intervals are presented based on the Type-II censoring scheme. Furthermore, Bayesian estimation is applied to the parameters, supported by appropriate prior distributions. …”
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Segmentation of the Sensor Data Stream in Pervasive Smart Environments by Vahid Ghasemi, Mohammad Javadian, Sajad Hayati

“…In the proposed method a feature vector is calculated for each sensor event in the data stream using a Bayesian approach, and the sequence of such vectors is hired in a difference of convex cost function. …”
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Software Defect Prediction For Quality Evaluation Using Learning Techniques Ensemble Stacking by Muhammad Romadhona Kusuma, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…The results showed that the ensemble stacking approach with a combination of Gradient Boosting, Ada Boost, Decision Tree, Bayesian Ridge, and LightGBM meta learner algorithms provided high accuracy with R2 score reaching 0.97, MAE of 0.037, and MSE of 0.006. …”
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A review on inverse analysis models in steel material design by Yoshitaka Adachi, Ta‐Te Chen, Fei Sun, Daichi Maruyama, Kengo Sawai, Yoshihito Fukatsu, Zhi‐Lei Wang

“…Key models discussed include the convolutional neural network–artificial neural network‐coupled model, which employs convolutional neural networks for feature extraction; the Bayesian‐optimized generative adversarial network–conditional generative adversarial network model, which generates diverse virtual microstructures; the multi‐objective optimization model, which concentrates on process–property relationships; and the microstructure–process parallelization model, which correlates microstructural features with process conditions. …”
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The Cognitive Footprint of Medication Use by Marta Suárez Pinilla, Charlotte R. Stoner, Martin Knapp, Parashkev Nachev, Martin Rossor

“…The cognitive footprint of a medication seeks to quantify the impact of its cognitive effects based on magnitude, duration, and interaction with other factors, evaluated across the exposed population. Methods Bayesian multivariable regression analysis of retrospective population‐based cross‐sectional cohorts. …”
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Intelligent Topical Sentiment Analysis for the Classification of E-Learners and Their Topics of Interest by M. Ravichandran, G. Kulanthaivel, T. Chellatamilan

“…The investigation illustrated in this paper is of threefold which are listed as follows: (1) lexicon based sentiment polarity of tweet messages; (2) the bigram cooccurrence relationship using naïve Bayesian; (3) the bigram item response theory (BIRT) on various topics. …”
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Nonlinear Programming to Determine Best Weighted Coefficient of Balanced LINEX Loss Function Based on Lower Record Values by Fuad S. Al-Duais, Mohammed Alhagyan

“…Comparisons are made between Bayesian estimators (SE, BSE, LINEX, and BLINEX) and maximum likelihood estimator via Monte Carlo simulation. …”
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Elephant Sound Classification Using Deep Learning Optimization by Hiruni Dewmini, Dulani Meedeniya, Charith Perera

“…Notably, our investigation reveals that the proposed ElephantCallerNet achieves an impressive accuracy of 89% in classifying raw audio directly without converting it to spectrograms. Leveraging Bayesian optimization techniques, we fine-tuned crucial parameters such as learning rate, dropout, and kernel size, thereby enhancing the model’s performance. …”
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