Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. …”
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Investigation of Artificial Intelligence Techniques for the Management of Cataract Disease: A Systematic Review by Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan

“…Deep learning techniques, decision trees, and Bayesian algorithms were involved in cataract management. Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. …”
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Interpretable machine learning approaches for predicting prostate cancer by using multiple heavy metal exposures based on the data from NHANES 2003–2018 by Zu-Ming You, Yuan-Sheng Li, Fan-Shuo Meng, Rui-Xiang Zhang, Chen-Xi Xie, Zhijiang Liang, Ji-Yuan Zhou

“…The synergistic effect analysis further identified blood Pb, urinary Sb, and urinary Cs as the major contributing factors. The predictive model established in this study can provide valuable strategies for the prevention and the control of PCA.…”
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Compressive strength prediction of fly ash/slag-based geopolymer concrete using EBA-optimised chemistry-informed interpretable deep learning model by Yang Yu, Iman Munadhil Abbas Al-Damad, Stephen Foster, Ali Akbar Nezhad, Ailar Hajimohammadi

“…The CNN architecture includes two convolution layers, global max-pooling, and two fully connected layers, with 11 input variables and a single output for CS prediction. To optimise model accuracy, the enhanced bat algorithm (EBA) is designed for metaparameter tuning. …”
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Optimizing maize germination forecasts with random forest and data fusion techniques by Lili Wu, Yuqing Xing, Kaiwen Yang, Wenqiang Li, Guangyue Ren, Debang Zhang, Huiping Fan

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A Multi-granularity Heterogeneous Ensemble Model for Point and Interval Forecasting of Carbon Prices by Di Sha, Xianyi Zeng, Kim-Phuc Tran, Lin Xia, Ruolin Wang

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A Discrete Grey Seasonal Model with Fractional Order Accumulation and Its Application in Forecasting the Groundwater Depth by Kai Zhang, Lifeng Wu, Kedong Yin, Wendong Yang, Chong Huang

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SELECTION OF RECIPIENTS FOR HEART TRANSPLANTATION BASED ON URGENCY STATUS by O. A. Sujayeva, M. I. Davidovitch, S. G. Sudzhaeva, Y. P. Оstrovsky

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Research on Tracking Control of Unmanned Mine Trucks Based on Adaptive Preview by HUANG Yaoran, LIU Zhicong, KANG Yuanrong

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Applying PageRank to Team Ranking in Single-Elimination Tournaments: Evidence from Taiwan’s High School Baseball by Yu-Chia Hsu, Wen-Jie Zhang

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An extension of the Spiegelhalter-Knill-Jones method for continuous covariates in clinical decision making by Bart K. M. Jacobs, Tafadzwa Maseko, Lutgarde Lynen, Aquiles Rodrigo Henriquez-Trujillo, Jozefien Buyze

Subjects: “…Prediction…”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

Subjects: “…Arrhythmia prediction…”
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Proposed Long Short-Term Memory Model Utilizing Multiple Strands for Enhanced Forecasting and Classification of Sensory Measurements by Sotirios Kontogiannis, George Kokkonis, Christos Pikridas

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DeepInvesting: Stock market predictions with a sequence-oriented BiLSTM stacked model – A dataset case study of AMZN by Ashkan Safari, Mohammad Ali Badamchizadeh

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Application of user preference mining algorithms based on data mining and social behavior in brand building by Yuhan Dong

“…In actual simulation experiments, its prediction results for the user’s brand preference index are accurate, with an error of only 0.11, and the algorithm has extremely high ratings among industry insiders. …”
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Advanced Machine Learning Methodology for Earthquake Magnitude Forecasting Using Comprehensive Seismic Data by Subhieh El-Salhi, Bashar Igried, Sari Awwad

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KPLS Optimization With Nature-Inspired Metaheuristic Algorithms by Jorge Daniel Mello-Roman, Adolfo Hernandez

“…It was solved using nature-inspired metaheuristic algorithms: the genetic algorithm, particle swarm optimization, grey wolf optimization and the firefly algorithm. …”
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Development of AI in the Caribbean: algorithms, challenges and recommendations by Amir Mohammed, Sheikh Ahad Ahmad

“…Central to AI systems are algorithms that discover patterns and make predictions, eliminating the need for meticulous programming. …”
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Fuzzy Guiding of Roulette Selection in Evolutionary Algorithms by Krzysztof Pytel

“…This paper presents, discusses, and tests a novel method for guiding roulette selection in evolutionary algorithms. The new method uses fuzzy logic and incorporates information from both current and historical generations to predict the best scheme for the selection process. …”
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Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series by Vasilii A. Gromov, Philip S. Baranov

“…The resulting strategy demonstrates accurate results for both benchmark and real-world time series, with the number of predicted steps exceeding that of any other published algorithm.…”
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