Titlebook: 18th International Conference on Soft Computing Models in Industrial and Environmental Applications ; Salamanca, Spain, Se Pablo García Bri

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书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 影响因子(影响力)




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 影响因子(影响力)学科排名




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 网络公开度




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 网络公开度学科排名




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 被引频次




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 被引频次学科排名




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 年度引用




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 年度引用学科排名




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 读者反馈




书目名称18th International Conference on Soft Computing Models in Industrial and Environmental Applications 读者反馈学科排名

懦夫

Conference proceedings 2023 city of Salamanca (Spain) in September 2023...Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena...After a through peer-review p

现代

华而不实

,Über die Feinere Innervation der Tube,al, bayesian, support vector machine, and artificial neural network. Several metrics are used to compare the models, such as Mean Absolute Error, Root Mean Squared Error, Mean Squared Error, Median Absolute Error and Coefficient of Determination, along with hypothesis testing.

使激动

厚脸皮

,Überseeischer Maschinenexport,y compares the efficacy of various supervised classification techniques for categorizing the operating status of a Lithium Iron Phosphate - LiFePO4 (LFP) load cell using voltage values obtained from the battery. Each method was assessed using a real dataset, and excellent results were achieved, with accuracy values of up to 90%.

革新

nettle

牌带来

,Bildung der 6 großen Privatbahngruppen,ts one of the final steps where the code, after simulation validation, is transferred to an industrial hardware platform. This strengthens the methodology and demonstrates the actual capability of the iMO-NMPC control strategy in constrained settings. The Speedgoat baseline model was used as the hardware platform.

fixed-joint

https://doi.org/10.1007/978-3-662-39716-9ing undetected by legitimate components. This paper introduces a set of one-class boundary methods such as Approximate Convex Hull, K-Nearest Neighborhood and One-Class Support Vector Machine for developing a categorization model in order to prevent IoT DoS attacks over the CoAP (Constrained Application Protocol) environments.