Design and validation of an artificial neural network based on analog circuits

Gencer, Fikret Basar; Xhafa, Xhesila; Inam, Benan Beril; Yelten, Mustafa Berke

doi:10.1007/s10470-020-01713-x

Cited by 5 publications

(1 citation statement)

References 25 publications

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“…ese funds can be used to develop basic education with higher social return. erefore, we say that private higher education is a quasi-public product between public products and private products, and a public welfare undertaking that reflects the national interests [9]. Based on its public welfare and quasipublic product attributes, the supply of private higher education products should be shared by the government, market, and society.…”

Section: Literature Reviewmentioning

confidence: 99%

Prediction of Higher Education Cost and Analysis of Sharing Ability Based on Artificial Neural Network

Xia

Yue

Niu

et al. 2022

Security and Communication Networks

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In order to explore how to realize the cost prediction and sharing ability of higher education, this paper proposes an analysis of the cost prediction and sharing ability of higher education based on artificial neural network. This method explores how to realize the cost prediction of higher education through the key technical problems and solutions of information recommendation based on artificial neural network. The research shows that the ability of college education cost prediction and sharing based on artificial neural network is 61% higher than that of traditional cost prediction and sharing. With the help of BP neural network algorithm, the accuracy of cost prediction can be maintained above 90%. It is proved that the artificial neural network algorithm can effectively improve the cost forecasting, financial system, and cost management system of colleges and universities.

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Section: Literature Reviewmentioning

confidence: 99%