Spatial Distribution of Poverty Clusters and Its Prediction Algorithms: A Visual Analytics Approach to Understanding the Disparities of Poverty Across Zones by Ngong'ho Bujiku Sende, Snehanshu Saha, Leon Fidele Ruganzu Uwimbabazi

“…Multidimensional poor and non-poor households were classified using the K-Means clustering algorithm, which demonstrated the highest performance among the nine clustering algorithms tested, effectively categorizing households into two clusters. …”
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Pediatric sepsis phenotypes for enhanced therapeutics: An application of clustering to electronic health records by Ioannis Koutroulis, Tom Velez, Tony Wang, Seife Yohannes, Jessica E. Galarraga, Joseph A. Morales, Robert J. Freishtat, James M. Chamberlain

“…Using feature sets used in related clustering studies, LCA and K‐means algorithms were used to derive 4 distinct phenotypic pediatric sepsis segmentations. …”
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Change Detection in Multitemporal High Spatial Resolution Remote-Sensing Images Based on Saliency Detection and Spatial Intuitionistic Fuzzy C-Means Clustering by Liang Huang, Qiuzhi Peng, Xueqin Yu

“…In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C-means (SIFCM) clustering is proposed. Firstly, the cluster-based saliency cue method is used to obtain the saliency maps of two temporal remote-sensing images; then, the saliency difference is obtained by subtracting the saliency maps of two temporal remote-sensing images; finally, the SIFCM clustering algorithm is used to classify the saliency difference image to obtain the change regions and unchange regions. …”
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An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm by Luis Fernando Grisales-Noreña, Vanessa Botero-Gómez, Rubén Iván Bolaños, Faustino Moreno-Gamboa, Daniel Sanin-Villa

“…This evaluation considered various metrics, including the best solution of each algorithm, the mean solution, the standard deviation, and the time consumed on average on each run.…”
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The Accuracy of Algorithms Used by Artificial Intelligence in Cephalometric Points Detection: A Systematic Review by Júlia Ribas-Sabartés, Meritxell Sánchez-Molins, Nuno Gustavo d’Oliveira

“…Convolutional neural networks (CNN)-based AI algorithms showed point localization accuracy ranging from 64.3 to 97.3%, with a mean error of 1.04 mm ± 0.89 to 3.40 mm ± 1.57, within the clinical range of 2 mm. …”
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Multicenter Evaluation of Machine-Learning Continuous Pulse Rate Algorithm on Wrist-Worn Device by Weixuan Chen, Rafael Cordero, Jessie Lever Taylor, Domenico R. Pangallo, Rosalind W. Picard, Marisa Cruz, Giulia Regalia

“…Bias, mean absolute error (MAE), mean absolute percentage error (MAPE), limits of agreement (LoA), and Pearson and Lin’s concordance correlation coefficients (⍴ and CCC) were also computed. …”
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Assessing the Validity of Computerized Algorithms for Determining Pulse Wave Velocity: A Clinical Study by Amira Tairi, Hasan Obeid, Saliha Addour, Mark Butlin, Alberto P. Avolio, Catherine Fortier, Mohsen Agharazii

“…The PWVComp-2nd and PWVSphyg-IT were 9.48 ± 3.25 m/s and 9.59 ± 3.25 m/s with a mean difference of 0.11 ± 0.66 m/s (p = 0.04). Conclusion: The present study shows that the difference between the two algorithms is negligible across a wide range of PTT and hence does not support the need for adjusting PWV according to the algorithm used for determining PTT. …”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…Validation against real-world data demonstrates improved prediction accuracy using metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). …”
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On Holt Winters Algorithm with Decomposition for Forecasting Financial Time Series with Complex Seasonal Patterns by منى نزيه على عبد البارى

“…The results of the study concluded that the Holt Winters Algorithm or triple exponential smoothing model is the best model since it produces the lowest Mean Absolute Percentage error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD) values which are 4,380, 244783 compared to 4, 385, 246837 for SES, and 5, 410, 270734 for DES, and thus can be used to predict the monthly stock returns of the Saudi Stock Index.…”
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Multi-Objective Portfolio Optimization: An Application of the Non-Dominated Sorting Genetic Algorithm III by John Weirstrass Muteba Mwamba, Leon Mishindo Mbucici, Jules Clement Mba

“…This study evaluates the effectiveness of the Non-dominated Sorting Genetic Algorithm III (NSGA-III) in comparison to the traditional Mean–Variance optimization method for financial portfolio management. …”
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Construction and Demolition Waste Generation Prediction by Using Artificial Neural Networks and Metaheuristic Algorithms by Ruba Awad, Cenk Budayan, Asli Pelin Gurgun

“…Different performance parameters, such as mean absolute error (MAE), mean square error (MSE), root mean squared error (RMSE), and the coefficient of determination (R²), are used to evaluate the effectiveness of the models developed. …”
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Prediction of contact resistance of electrical contact wear using different machine learning algorithms by Zhen-bing Cai, Chun-lin Li, Lei You, Xu-dong Chen, Li-ping He, Zhong-qing Cao, Zhi-nan Zhang

“…To reduce testing time and costs and quickly obtain the electrical contact performance of H62 brass alloy after wear caused by different factors, three algorithms (random forest (RF), support vector regression (SVR), and BP neural network (BPNN)) were used to train and test experimental results, resulting in a machine learning model suitable for predicting the stable mean resistance of H62 brass alloy after wear. …”
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Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…To validate the theoretical findings and study the applicability of the algorithms across diverse problem classes, extensive numerical experiments were conducted to calculate the main sensitivity indicators—Sobol’ global sensitivity indices. …”
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Video Refereeing Model of Soccer Match Based on Fuzzy Clustering and Cuckoo Optimization Algorithm by Ting Wang, Jinglong Geng, Jing Wang, Xiao Yan

“…The enhanced algorithm model, enhanced cuckoo-fuzzy C-mean algorithm model, cuckoo-fuzzy C-mean algorithm model, and fuzzy C-mean algorithm model had delineation effects of 0.80, 0.72, 0.70, and 0.61, in that order. …”
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On the issue of coordination of the activities of forces and means of organizations and institutions of the Federal Medical and Biological Agency of Russia and Rospotrebnadzor in e... by A. S. Samoilov, I. K. Romanovich, M. I. Grachev, Yu. A. Salenko, A. N. Barkovsky, V. S. Repin, L. S. Bogdanova

“…The article presents the main provisions of the draft document, which, after discussion and refinement, as the authors hope, this publication will contribute, draft of Concept can be submitted for approval. …”
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Performance Analysis of Conventional Beamforming Algorithm for Angle-of-Arrival Estimation under Measurement Uncertainty by Eun-Kyung Lee, Joon-Ho Lee

“…The performance of the conventional beamforming for angle-of-arrival (AOA) estimation algorithm under measurement uncertainty is analyzed. …”
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Research on building energy consumption prediction algorithm based on customized deep learning model by Zheng Liang, Junjie Chen

“…The suggested model’s performance has been assessed using evaluation metrics, resulting in a low Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), indicating superior accuracy relative to comparable studies. …”
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The Algorithm for Recognizing Superposition of Wave Aberrations from Focal Pattern Based on Partial Sums by Sergey G. Volotovsky, Pavel A. Khorin, Aleksey P. Dzyuba, Svetlana N. Khonina

“…Therefore, to overcome this drawback, an algorithm was developed that considers partial sums, which made it possible to increase the convergence range and achieve unambiguous recognition results for aberrations (root mean square does not exceed 10⁻⁸) described by superpositions of Zernike functions up to <i>n</i> = 5.…”
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Cooperative Scheduling of Imaging Observation Tasks for High-Altitude Airships Based on Propagation Algorithm by He Chuan, Qiu Dishan, Liu Jin

“…Firstly, the task set is divided by using k-core neighborhood growth cluster algorithm (K-NGCA). Then, a novel swarm intelligence algorithm named propagation algorithm (PA) is combined with the key node search algorithm (KNSA) to optimize the cruising path of each airship and determine the execution time interval of each task. …”
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An Algorithm for Simplifying 3D Building Models with Consideration for Detailed Features and Topological Structure by Zhenglin Li, Zhanjie Zhao, Wujun Gao, Li Jiao

“…Compared to the QEM algorithm and the other two comparison algorithms selected in this paper, the simplified model resulting from this algorithm exhibit a reduction in Hausdorff distance, mean error, and mean square error to varying degrees. …”
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