Network education platform in flipped classroom based on improved cloud computing and support vector machine

2020 ◽  
pp. 1-11
Author(s):  
Leng Jing ◽  
Zhu Bo ◽  
Qingxiang Tian ◽  
Wei Xu ◽  
Jiaoxue Shi
Keyword(s):  
Support Vector Machine ◽  
Cloud Computing ◽  
Flipped Classroom ◽  
Support Vector ◽  
Network Education ◽  
Education Platform

scholarly journals Stock Market Prediction using Machine Learning and Cloud Computing

2019 ◽  
Vol 8 (09) ◽  
pp. 24847-24850
Author(s):  
Nirbhay Narkhede
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Cloud Computing ◽  
Crucial Role ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Computational Power ◽  
The World ◽  
A Company ◽  
Risky Business

In the world with increasing globalization , where money places a crucial role in determining the expansion and earnings of a company trading places a very crucial role. Multiple companies invest millions and billions of dollars in other countries with an expectation to make profits. In such a risky business Predicting the movement of the market can help companies or individual in making good decisions and can prevent severe loses. In this research paper we will discuss how we can use the computational power of the computer on cloud along with the machine learning algorithms to predict the closing values of the stocks which is a big challenge otherwise. For this purpose we will use Python as our programming language which supports a lot of ML based Libraries. The models we will be using are SVM(Support Vector Machine) , Linear Regression , Random Forest, XGBoost ,LSTM for deep learning

Research on Multilayer Security Audit Research Based on Attack Graph in Cloud Computing

2014 ◽  
Vol 644-650 ◽  
pp. 3408-3411
Author(s):  
Lin Bin Wen
Keyword(s):  
Cloud Computing ◽  
Cloud Model ◽  
Rapid Development ◽  
Colleges And Universities ◽  
It Industry ◽  
Network Education ◽  
The Road ◽  
Service Application ◽  
Education Platform ◽  
Computational Ability

Cloud computing, the future development direction of the IT industry, has the profound influence of cloud computing applications, which is bound to the field of higher education, the construction of university network education resources platform is the integration of all kinds of educational resources of colleges and universities, and to provide fast and convenient resource storage, sharing, learning and computational ability. This article is from the university network education platform of cloud computing based on the advantages of the proposed strategy, construction of information resources of University under the cloud computing environment. This is how the cloud model construction resources platform of network education in Colleges and universities. With the rapid development of Internet, people from all walks of life to and gradually mature "cloud computing" model of combining the road to seek an opportunity. However, in the field of education, the application of cloud computing is scanty. Research on the current college network education situation and abuse with according to the characteristics of cloud computing, advantages, and puts forward the conception of network education platform based on cloud computing, and further demonstrates its feasibility. It is the high time to improve the transplantation and service application pattern of cloud computing in the field of education.

The Support Vector Machine Fault Diagnosis Algorithm Based on Cloud Computing

2014 ◽  
Vol 687-691 ◽  
pp. 761-765
Author(s):  
Chang Hong Zhang ◽  
Si Jia Cheng ◽  
Shu Hao Cao
Keyword(s):  
Support Vector Machine ◽  
Cloud Computing ◽  
Fault Diagnosis ◽  
Large Scale ◽  
Support Vector ◽  
Machine Fault Diagnosis ◽  
Diagnosis Method ◽  
Diagnosis Algorithm ◽  
Machine Fault ◽  
The Way

The paper puts forward the way to solve the problem of SVM training on the large scale firstly, Then perform the experiment to verify the feasibility of scheme. In the last section, SVM fault diagnosis method based on the Mapreduce is put forward.

Resource Scheduling Optimization Model in Cloud Computing Environment

2014 ◽  
Vol 687-691 ◽  
pp. 1645-1648
Author(s):  
Chun Yan Kang ◽  
Tie Jun Shi
Keyword(s):  
Support Vector Machine ◽  
Cloud Computing ◽  
Computational Complexity ◽  
Support Vector ◽  
Computing Environment ◽  
Scheduling Optimization ◽  
Cloud Computing Environment ◽  
Computing Model ◽  
Resource Index ◽  
Different Levels

In the process of cloud computing, the dynamic hierarchical resource index is researched, and the independent confusion cloud computing is studied. This problem has become the focus of data processing. Therefore, it needs to establish improved dynamic layered resource index independent confuse cloud computing model. According to the theory of support vector machine, all of the resources are taken with dynamical layered processing, different levels of resources are taken with the independent confusion cloud computing. The experiment results show that, this algorithm is taken for the dynamic layered resource cloud computing, calculation efficiency can be improved, computational complexity and redundancy are reduced, meet the practical demands of dynamic hierarchical resource index independent confused cloud computing. It has good application value in the cloud computing application.

A Practical Fault Tolerance Approach in Cloud Computing Using Support Vector Machine

2020 ◽  
pp. 45-49
Author(s):  
Gajendra Sharma ◽  
Keyword(s):  
Machine Learning ◽  
Support Vector Machine ◽  
Cloud Computing ◽  
Fault Tolerance ◽  
Learning Algorithm ◽  
Supervised Machine Learning ◽  
Support Vector ◽  
Machine Learning Algorithm ◽  
Tolerance Approach ◽  
Systematic Solution

Fault tolerance is an important issue in the field of cloud computing which is concerned with the techniques or mechanism needed to enable a system to tolerate the faults that may encounter during its functioning. Fault tolerance policy can be categorized into three categories viz. proactive, reactive and adaptive. Providing a systematic solution the loss can be minimized and guarantee the availability and reliability of the critical services. The purpose and scope of this study is to recommend Support Vector Machine, a supervised machine learning algorithm to proactively monitor the fault so as to increase the availability and reliability by combining the strength of machine learning algorithm with cloud computing.

Study of Higher Institutes Platform Based on Cloud Computing

2014 ◽  
Vol 644-650 ◽  
pp. 6301-6304
Author(s):  
Xiao Chuan Feng
Keyword(s):  
Cloud Computing ◽  
Cloud Model ◽  
Rapid Development ◽  
Colleges And Universities ◽  
It Industry ◽  
Network Education ◽  
The Road ◽  
Service Application ◽  
Education Platform ◽  
Computational Ability

Cloud computing, the future development direction of the IT industry, has the profound influence of cloud computing applications, which is bound to the field of higher education, the construction of university network education resources platform is the integration of all kinds of educational resources of colleges and universities, and to provide fast and convenient resource storage, sharing, learning and computational ability. This article is from the university network education platform of cloud computing based on the advantages of the proposed strategy, construction of information resources of University under the cloud computing environment. This is how the cloud model construction resources platform of network education in Colleges and universities. With the rapid development of Internet, people from all walks of life to and gradually mature "cloud computing" model of combining the road to seek an opportunity. However, in the field of education, the application of cloud computing is scanty. Research on the current college network education situation and abuse with according to the characteristics of cloud computing, advantages, and puts forward the conception of network education platform based on cloud computing, and further demonstrates its feasibility. It is the high time to improve the transplantation and service application pattern of cloud computing in the field of education. The main works of this paper are as follows: firstly, the domestic and foreign network education to analyze the situation, reasons and problems existing in domestic university network education problems.

Sign in / Sign up

Export Citation Format

Share Document