Titlebook: Computational Intelligence Methods for Green Technology and Sustainable Development; Proceedings of the I Yo-Ping Huang,Wen-June Wang,Hoai-

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Multivariate Adaptive Regression Splines for Stability Number of Unsupported Conical Slopes in Anisy. Multivariate Adaptive Regression Splines (MARS) model?~?a machine learning approach, is adopted to build the close–form equation between input variables and output results, and also investigate the coupling effects among input variables by sensitive analysis. The artificial data for MARS model is

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Numerical Investigation on the Damage Extents of Plates Due to Repeated Slamming Loads,his paper deals with the damage to steel plates of actual marine structures caused by repeated impact pressures induced by slamming. The numerical analysis model was developed and presented in detail. In the calculations, based on the test model material, the strain hardening was defined using propo

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2367-3370 . Throughthorough research basing on both experimental and numerical methods, the authors feature either solutions for existing problems or optimization and improvement for performance of existing methods. The 978-3-031-19693-5978-3-031-19694-2Series ISSN 2367-3370 Series E-ISSN 2367-3389

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,Machine Learning in Classification of Parkinson’s Disease Using Electroencephalogram with Simon’s Cs to diagnose healthy people and PD. Research also indicated that removing noise from EEG signals was a crucial step, which helped to improve the result significantly. The classification result using linear Support Vector Machine gives the highest performance: 84.5% accuracy, 89.3% sensitivity, and

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Fusion of Segmentation and Classification for Improving Skin Disease Diagnosis,ntation task utilizes to extract only the damaged skin regions for disease diagnosis. Thusly, the advantage of the proposed method supports reducing the important data space and focuses on ROIs of the disease features for improving efficient diagnosis systems. The proposed method has been evaluated

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