A Study on the Classification of Atopic Dermatitis by Spectral Features of Hyperspectral Imaging by Eun Bin Kim, Yoo Sang Baek, Onseok Lee

“…Although the overall accuracy was lower than existing RGB images, the t-distributed stochastic neighbor embedding results showed that the severity groups were well distinguished. …”
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A novel aggregated coefficient ranking based feature selection strategy for enhancing the diagnosis of breast cancer classification using machine learning by E. Sreehari, L. D. Dhinesh Babu

“…Later, we employed models such as decision trees, support vector machines, k-nearest neighbors, random forests, stochastic gradient descent, and Gaussian naive bayes to determine the type of cancer. …”
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A Fast Optimization Method for Reliability and Performance of Cloud Services Composition Application by Zhao Wu, Naixue Xiong, Yannong Huang, Qiong Gu, Chunyang Hu, Zhongbo Wu, Bo Hang

“…The optimization for reliability and performance of cloud services composition application, which is a typical stochastic optimization problem, is confronted with severe challenges due to its randomness and long transaction, as well as the characteristics of the cloud computing resources such as openness and dynamic. …”
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Assessment of economic efficiency of hydrogen production using wind and solar energy by Oleg V. Marchenko, Sergei V. Solomin

“…In an autonomous power supply system, due to the use of “excess” electricity from renewable energy sources operating in stochastic mode, the costs of hydrogen production are minimal. …”
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Medicines for the management of overweight and obesity: A systematic review with network meta-analysis by Gabriela Masiero Marcon, Jhonatan Mendes Paiva, Mariana Delariva Sakiyama, Fernanda Stumpf Tonin, Fernando Fernandez-Llimos, Suzane Virtuoso, Andreia Cristina Conegero Sanches

“…Abstract To synthesize the evidence about pharmacologic treatment of obesity and overweight and to define the options with the best risk-benefit using the stochastic analysis of multicriteria acceptability (SMAA). …”
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Machine Learning and Multi-Omics Integration to Reveal Biomarkers and Microbial Community Assembly Differences in Abnormal Stacking Fermentation of Sauce-Flavor <i>Baijiu</i> by Shuai Li, Yueran Han, Ming Yan, Shuyi Qiu, Jun Lu

“…Additionally, ecological models reveal the bacterial community assembly in abnormal fermentations was influenced by stochastic factors, while the fungal community assembly was influenced by deterministic factors. …”
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The control strategy for distributed energy storage devices using fully diffusion strategy by Zejian Liu, Ping Yang, Xu Lin, Ziwei Fan, Cencen Hong

“…Diffusion strategy allows adjacent nodes to diffuse and cooperate information in real-time, and it includes a stochastic gradient term. Thus, diffusion strategy can achieve a higher convergence rate and lower mean-square-error than consensus strategies. …”
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MOVIMENTO BROWNIANO: APLICAÇÃO EM ESTRATÉGIAS DE BUSCA by Matheus Dias Carvalho, Ricardo de Carvalho Falcão, Antonio Marcos de Oliveira Siqueira

“…In addition, the ideas of feed, metabolic rate and stochastic restart to the walker were added, features that have been gaining ground recently in the study of random processes. …”
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Noise in ecosystems: A short review by B. Spagnolo, D. Valenti, A. Fiasconaro

“…Noise, through its interaction with the nonlinearity of the living systems, can give rise to counter-intuitive phenomena such as stochastic resonance, noise-delayed extinction, temporal oscillations, and spatial patterns. …”
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Performance Optimization of Cloud Data Centers with a Dynamic Energy-Efficient Resource Management Scheme by Yu Cui, Shunfu Jin, Wuyi Yue, Yutaka Takahashi

“…To analyze the end-to-end performance of the cloud system’s service with the proposed scheme, we establish a hybrid queueing system composed of three stochastic submodels by using a matrix-geometric solution. …”
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Graph Evaluation and Review Technique for Emergency Logistics Distribution in Complex Environment by Lin Lu, Liguo Yang, Xiaochun Luo

“…After that, the effectiveness of GERT stochastic network in the process of emergency distribution is verified by an example of a logistics distribution route, which provides decision-making basis for relevant departments. …”
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Exploitation of Documented Historical Floods for Achieving Better Flood Defense by Slobodan Kolaković, Julius Fabian, Sándor Kovács, Ljubomir Budinski, Matija Stipić

“…Establishing Base Flood Elevation for a stream network corresponding to a big catchment is feasible by interdisciplinary approach, involving stochastic hydrology, river hydraulics, and computer aided simulations. …”
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Predictive modelling of hexagonal boron nitride nanosheets yield through machine and deep learning: An ultrasonic exfoliation parametric evaluation by Jerrin Joy Varughese, Sreekanth M․S․

“…A suite of machine learning regression models including Adaptive Boosting (AdaBoost) Regressor, Random Forest (RF) Regressor, Linear Regressor (LR), and Classification and Regression Tree (CART) Regressor, was employed alongside a deep neural network (DNN) architecture optimized using various algorithms such as Adaptive Moment Estimation (Adam), Root Mean Square Propagation (RMS Prop), Stochastic Gradient Descent (SGD), and Limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS). …”
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Characterization of Neural Interaction During Learning and Adaptation from Spike-Train Data by Liqiang Zhu, Ying-Cheng Lai, Frank C. Hoppensteadt, Jiping He

“…., Neural Computations 15 ,2359 (2003)] a general procedure to detect and quantify the causalinteractions among neurons, which is based on the method ofdirected transfer function derived from a class of multivariate,linear stochastic models. The procedure was applied to spiketrains from neurons in the primary motor cortex of the monkeybrain during adaptation, where monkeys were trained to learn a newskill by moving their arms to reach a target under externalperturbations. …”
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Very Short-Term Blackout Prediction for Grid-Tied PV Systems Operating in Low Reliability Weak Electric Grids of Developing Countries by Benson H. Mbuya, Aleksandar Dimovski, Marco Merlo, Thomas Kivevele

“…Furthermore, the efficacy analysis of the short-term blackout prediction of the formulated RF, ASD, and RF-ASD regression and classification algorithms was compared. Considering the stochastic nature of blackouts, their performance was found to be fair in short-term blackout predictions of the test site’s weak grid using limited input data from the point of coupling of the user. …”
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Pattems and models of flowering of some Gampanulaceae Juss. species by E. S. Fomin, T. I. Fomina

“…Observation data were processed by standard statistical methods and used to construct stochastic computer models of flowering shoots, while omissions in data were restored by using the maximum likelihood method. …”
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XAI-Enhanced Machine Learning for Obesity Risk Classification: A Stacking Approach With LIME Explanations by Mohammad Azad, Md Faraz Kabir Khan, Sameh Abd El-Ghany

“…Our proposed model employs an ensemble approach, specifically a stacking algorithm, where the base estimators include the Light Gradient Boosting Machine (LGBM) classifier, the Logistic Regression (LR) classifier, and the Random Forest (RF) Classifier, and the Stochastic Gradient Descent (SGD) classifier is selected as the final estimator. …”
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Differences in Biogeographic Patterns and Mechanisms of Assembly in Estuarine Bacterial and Protist Communities by Weiyue Zhang, Yunlei Zhang, Zhizhuo Shao, Yi Sun, Hongjun Li

“…In addition, the two community assemblages were shown to be dominated by deterministic and stochastic processes, respectively. Furthermore, our results emphasized the influence of the local species pool on microbial communities and the fact that, at larger scales, geographic factors played a more significant role than environmental factors in driving microbial community variation. …”
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Research on optimal arrangement strategy of top coal caving support sensors based on vibration characteristics of coal and gangue by WANG Yao, YANG Shanguo, WU Mingke, MENG Bin, YANG Zheng, LIU Houguang

“…Thirdly, the extracted features were visualized by <italic>t</italic>-distributed stochastic neighbor embedding （<italic>t</italic>-SNE） dimensionality reduction, and five features which were sensitive to the distinction between coal and gangue signals were selected as target features. …”
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A Decomposed-Ensemble Prediction Framework for Gate-In Operations at Container Terminals by Yifan Shen, Beng Xuan, Hongtao Hu, Yansong Wu, Ning Zhao, Zhen Yang

“…These contributions are expected to improve terminal operational efficiency, reduce resource wastage, and better adapt to the highly stochastic gate-in operation environment.…”
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