Abstract: This study aims at predicting the hourly mean wind speed using a Support Vector Machine (SVM) based on a regression (SVR) model. The SVM for regression is part of the machine learning ...

在创新驱动发展战略深入推进的当下，企业研发投入成为经济高质量发展的核心动力，而研发费用加计扣除、高新技术企业税收优惠等政策，既激发了企业创新活力，也催生了部分企业的研发操纵行为。这类通过虚增研发支出、调整会计处理方式套取政策红利的 ...

This work includes two high performance recognizers. The SVM based recognizer has an accuracy of 90%. It first applies projection-based algorithm to the input image, then use a pre-trained SVM model ...

This primary research paper emphasizes cross-validation, where data samples are reshuffled in each iteration to form randomized subsets divided into n folds. This method improves model performance and ...

Abstract: This paper presents a chatbot model designed to detect stress in users through simple yes-or-no questions. Utilizing a Support Vector Machine (SVM) algorithm, the model achieves high ...

Ischemic Stroke (IS) stands as a leading cause of mortality and disability globally, with an anticipated increase in IS-related fatalities by 2030. Despite therapeutic advancements, many patients ...

Due to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as ...

Hyperparameter tuning is a critical step in optimizing machine learning models for optimal performance. It involves selecting the best combination of hyperparameters, such as regularization strength, ...

Globally, the prevalence of mental health problems, especially depression, is at an all-time high. The objective of this study is to utilize machine learning models and sentiment analysis techniques ...

Support Vector Machines (SVM) are widely used in machine learning for classification and regression tasks. However, the performance of an SVM model depends heavily on its parameter settings, such as ...