Cross-Temporal Remote Sensing Image Change Captioning: A Manifold Mapping and Bayesian Diffusion Approach for Land Use Monitoring by Qingshan Bai, Xiaohua Wang

“…This study proposes a cross-temporal remote sensing image change captioning (RSICC) model named CTM, which is constructed based on manifold mapping and Bayesian diffusion techniques. The primary objective of CTM is to enhance the accuracy and robustness of captioning changes in multitemporal remote sensing images (RSIs). …”
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Optimization Strategies for Urban Waterlogging Warning in Complex Environments: Based on Particle Swarm Optimization and Deep Neural Networks by Xiande Hu, Fenfei Gu

“…To better address these issues, this article combines particle swarm optimization (PSO) and deep neural networks (DNN) to explore the construction of early warning models in depth. …”
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Determining Point of Economic Cattle Milk Production through Machine Learning and Evolutionary Algorithm for Enhancing Food Security by Sonam Bhardwaj, Ayon Tarafdar, Manoj Baghel, Triveni Dutt, Gyanendra Kumar Gaur

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Intelligent model for forecasting fluctuations in the gold price by Mahdieh Tavassoli, Mahnaz Rabeei, Kiamars Fathi Hafshejani

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Asymptotic Behavior of the Bayes Estimator of a Regression Curve by Agustín G. Nogales

“…An important role in the demonstration of these results is the establishment of a probability space as an adequate framework to address the problem of estimating regression curves from the Bayesian point of view, putting at our disposal powerful probabilistic tools in that endeavor.…”
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Optimizing the learning rate for adaptive estimation of neural encoding models. by Han-Lin Hsieh, Maryam M Shanechi

“…Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. …”
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Skewed Multifractal Cross-Correlations Between Green Bond Index and Energy Futures Markets: A New Perspective Based on Change Point by Yun Tian, Zhihui Li, Jue Wang, Xu Wu, Huan Huang

“…This study is the first to use the Bayesian Estimator of Abrupt Change, Seasonality, and Trend (BEAST) algorithm to detect trend change points in the nexuses between the green bond index (Green Bond) and WTI of crude oil, gasoline, as well as natural gas futures. …”
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Assessment of the stock status for greenland halibut (<i>Reinhardtius hippoglossoides matsuurae</i>) in the Okhotsk Sea by V. V. Kulik, I. I. Glebov, N. L. Aseeva, R. N. Novikov

“…This new value is slightly higher than that one used by ICES for greenland halibut in the northeastern Atlantic (3.5 % for fishable biomass, its reduction to 2.5 % is discussed), but these values cannot be compared because of different habitat conditions and probably different growth rate of greenland halibut in the Okhotsk Sea and the Atlantic. Researches on the optimal level of greenland halibut exploitation should be continued; anyway, the new reference point of the target harvest rate has to be implemented immediately and to be used at least until correction of the age-length key for greenland halibut in the Okhotsk Sea. …”
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Comparative analysis of efficacy of different combination therapies of α-receptor blockers and traditional Chinese medicine external therapy in the treatment of chronic prostatitis... by Kaiyu Zhang, Yi Zhang, Shengwei Hong, Yutian Cao, Chengjiang Liu

“…With respect to the total effective rate, α-RBs+ needling was most likely to be the optimal treatment. Concerning National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) total score, α-RBs+ moxibustion+ auricular point sticking was most likely to be optimal treatment, the therapy ranking second was α-RBs+ needling, and the therapy ranking third was α-RBs+ moxibustion. …”
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Explicit and explainable artificial intelligent model for prediction of CO2 molecular diffusion coefficient in heavy crude oils and bitumen by Saad Alatefi, Okorie Ekwe Agwu, Ahmad Alkouh

“…Optimizing CO2 injection for enhanced oil recovery (EOR) requires a precise estimation of the CO2-diffusivity coefficient in porous media. …”
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Fleet Scheduling Optimization of Hazardous Materials Transportation: A Literature Review by Changxi Ma, Jibiao Zhou, Xuecai (Daniel) Xu, Fuquan Pan, Jin Xu

“…To comprehensively understand the research progress of the fleet scheduling for hazardous materials, the study has summarized the corresponding research results from three aspects (a) hazardous materials transportation risk, (b) route optimization, and (c) fleet scheduling, and then pointed out potential problems from six aspects: (a) the coupling risk of the transport fleet; (b) the screening of time and space for the transport of hazardous materials; (c) the scheduling optimization for transport fleets; (d) taking insufficient account of transport risks fairness; (e) insufficient robustness of scheduling schemes; and (f) lacking of research results on fleet scheduling of transport in the context of antiterrorism. …”
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Detecting Schistosoma infections in endemic countries: a diagnostic accuracy study in rural Madagascar by Eva Lorenz, Ravo Razafindrakoto, Pia Rausche, Zaraniaina Tahiry Rasolojaona, Nantenaina Matthieu Razafindralava, Alexandre Zerbo, Yannick Höppner, Heidrun von Thien, Njary Rakotozandrindrainy, Cheick Oumar Doumbia, Philipp Klein, Jean-Marc Kutz, Paul L. A. M. Corstjens, Claudia de Dood, Pytsje T. Hoekstra, Govert J. van Dam, Anna Jaeger, Norbert Georg Schwarz, Egbert Tannich, Mala Rakoto Andrianarivelo, Raphael Rakotozandrindrainy, Rivo Andry Rakotoarivelo, Jürgen May, Tahinamandranto Rasamoelina, Daniela Fusco

“…Bayesian latent class models were used to assess diagnostic accuracies and disease prevalence. …”
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Reliability assessment of two production lines using joint progressively type-II censored XLindley samples by I. Elbatal, Ahmed Elshahhat, H. E. Semary, Mazen Nassar

“…The maximum likelihood method is applied to obtain point estimates for the unknown parameters and reliability functions, while Bayesian analysis is performed under the squared error loss function, employing the Markov Chain Monte Carlo technique to generate samples from the posterior distribution. …”
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Integrated Correction of Nonlinear Dynamic Drift in Terrestrial Mobile Gravity Surveys: A Comparative Study Based on the Northeastern China Gravity Monitoring Network by Zhaohui Chen, Jinzhao Liu

“…The innovative hybrid scheme combines local drift preprocessing (initial-point modeling, line fitting, variance-sum optimization) with global adjustment optimization, achieving the significant suppression of nonlinear drift errors. …”
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An Effective 3D Instance Map Reconstruction Method Based on RGBD Images for Indoor Scene by Heng Wu, Yanjie Liu, Chao Wang, Yanlong Wei

“…We integrate these point cloud segments into a global voxel map, updating each voxel’s class using color, distance constraints, and Bayesian methods to create an object-level instance map. …”
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Median interacted pigeon optimization-based hyperparameter tuning of CNN for paddy leaf disease prediction by Jasmy Davies, S. Sivakumari

“…Thus, a novel Median Interacted Pigeon-Inspired Optimization (MIPIO) is proposed, which optimizes CNN hyperparameters to enhance the accuracy of characterizing fungal infections and enable the recognition of antagonist interactions among virus species. …”
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Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

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Incorporating Risk in Operational Water Resources Management: Probabilistic Forecasting, Scenario Generation, and Optimal Control by Ties van derHeijden, Miguel Angel Mendoza‐Lugo, Peter Palensky, Nick van deGiesen, Edo Abraham

“…Recognizing the limitations of deterministic methods in the face of weather, energy system, and market uncertainties, we propose a scalable stochastic Model Predictive Control (MPC) framework that integrates probabilistic forecasting, scenario generation, and stochastic optimal control. We utilize Combined Quantile Regression Deep Neural Networks and Non‐parametric Bayesian Networks to generate probabilistic scenarios that capture realistic temporal dependencies. …”
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Posture configuration optimization method and system for folding booms of the pump truck under life extension control by Dong Qing, Su Youcheng, Xu Gening, She Lingjuan, Wang Ze

“…This configuration optimization yields the optimal boom posture for a specific pouring point. …”
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Unmasking insider threats using a robust hybrid optimized generative pretrained neural network approach by P. Lavanya, H. Anila Glory, Manuj Aggarwal, V. S. Shankar Sriram

“…The proposed approach is composed of an Adabelief Wasserstein Generative Adversarial Network (ABWGAN) with Expected Hypervolume Improvement (EHI) of hyperparameter optimization for adversarial sample generation and an L2-Starting Point (L2-SP) regularized pretrained Attention Graph Convolutional Network (AGCN) to detect insiders in the network infrastructure. …”
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