Titlebook: ;

Detrusor-Muscle

书目名称Green Sustainability: Towards Innovative Digital Transformation影响因子(影响力)




书目名称Green Sustainability: Towards Innovative Digital Transformation影响因子(影响力)学科排名




书目名称Green Sustainability: Towards Innovative Digital Transformation网络公开度




书目名称Green Sustainability: Towards Innovative Digital Transformation网络公开度学科排名




书目名称Green Sustainability: Towards Innovative Digital Transformation被引频次




书目名称Green Sustainability: Towards Innovative Digital Transformation被引频次学科排名




书目名称Green Sustainability: Towards Innovative Digital Transformation年度引用




书目名称Green Sustainability: Towards Innovative Digital Transformation年度引用学科排名




书目名称Green Sustainability: Towards Innovative Digital Transformation读者反馈




书目名称Green Sustainability: Towards Innovative Digital Transformation读者反馈学科排名

根除

Interpolation und Approximation scenarios on ensuring financial security. It corresponds with current situations, taking into account forecast states for implementation of corrective actions in order to limit internal and external environment threats.

laxative

https://doi.org/10.1007/978-3-662-64110-1d services and analyzes the risk if the controls are not applied. In addition, the model will provide the user with various client-side controls as well as certain service level agreement (SLA) guiding parameters.

JIBE

Accede

hyperuricemia

hyperuricemia

Strategic Measures and Alternatives to Ensure the Financial Security of Machine-Building Enterprises scenarios on ensuring financial security. It corresponds with current situations, taking into account forecast states for implementation of corrective actions in order to limit internal and external environment threats.

障碍

钢笔记下惩罚

Machine Learning for Blood Donors Classification Model Using Ensemble Learningncludes data preprocessing and donor classification. Several ensemble models have been developed. The results show that the random forest model led to the best test set accuracy (96.3%), which beat other methods.

Morphine

A Review for Software Defect Prediction Using Machine Learning Algorithms and also prediction of software defects. In this paper, most research approaches concerning defect prediction problems are discussed. According to this study, it is observed that the genetic algorithm with the deep neural network, random forest, and artificial neural networks‘ techniques improve the accuracy of software defect prediction.