scholarly journals Engineering Financial Performance Evaluation of Wireless Network Based on Intelligent Neural Network Model

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xiaoling Xu ◽  
Jianghao Song

Under the global economy, enterprises in the financial industry are facing plenty of opportunities and severe challenges. Aimed at providing a reference enterprise performance evaluation system for related enterprises, the proposed model helps enterprises to learn and sort out their own performance evaluation system according to this structure. A prediction model of BP neural network (BPNN) based on the wireless network is studied as the performance data prediction algorithm. Firstly, the feasibility of this algorithm is analysed through prediction training. Secondly, the proposed neural network algorithm is compared with the traditional algorithm for data prediction. It turns out that this neural network prediction algorithm based on wireless communication is not only universal to the prediction data but also superior to the traditional prediction algorithm in both error gap and relative average error compared with other traditional algorithms. On this basis, the particle swarm optimization (PSO) algorithm is also used to evaluate the performance indicators of three enterprises, and accurate numerical values are obtained to express the corresponding results. Therefore, it is concluded that the subalgorithm can be applied to the enterprise performance evaluation team in the financial industry.

2014 ◽  
Vol 667 ◽  
pp. 60-63
Author(s):  
Wei Guo ◽  
Zhen Ji Zhang

A performance evaluation system of finance transportation projects is mainly researched, in which the sub-module of the highway projects evaluation, waterway projects evaluation, Passenger stations projects evaluation, Energy saving projects evaluation are incorporated. In addition, the expert knowledge are inserted in the system, the multi-layer neural network and fuzzy-set theory are used to implement Performance Evaluation system of Finance invest Transportation Projects, and the feasibility and effectiveness of the evaluation system are finally verified by practice.


2004 ◽  
Vol 8 (2) ◽  
pp. 208-213
Author(s):  
Noriyuki Aibe ◽  
Ryosuke Mizuno ◽  
Masanori Nakamura ◽  
Moritoshi Yasunaga ◽  
Ikuo Yoshihara

2004 ◽  
Vol 8 (2) ◽  
pp. 208-213 ◽  
Author(s):  
Noriyuki Aibe ◽  
Ryosuke Mizuno ◽  
Masanori Nakamura ◽  
Moritoshi Yasunaga ◽  
Ikuo Yoshihara

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Honglin Fu

This paper uses a multidimensional big data matrix model to optimize the analysis and conduct a systematic construction of the enterprise performance evaluation system. The adoption of new research methods and perspectives to promote the study of the use of performance information is of great significance to achieve the effectiveness, science, and sustainability of corporate performance management. To solve the problem of objectivity and scientificity of performance information use, this part attempts to analyze performance information use from the perspective of the multidimensional big data matrix, focusing on the techniques and methods in the process of promoting performance information use from the multidimensional big data matrix and tries to construct a system model of enterprise performance information use from two dimensions: the use of performance information sources and the use of performance information results. Based on multiple theoretical hypotheses, a theoretical and empirical basis is provided for the division of demand dimensions of enterprise performance evaluation system. Through social capital theory, three dimensions of network social capital, cognitive social capital, and structural social capital are hypothesized, and the logistic regression method is applied for empirical study. The results show that these three dimensions have significant effects on the knowledge demand of enterprise performance evaluation systems. It is verified that the multidimensional big data matrix can enhance the quality of performance information sources and improve the objectivity of performance information. In the performance information source use dimension, the analysis verified that the collection and preprocessing technology of big data can realize the automation, real-time, and diversification of information collection and preprocessing, and enhance the objectivity of performance information. Big data helps to improve the quality and effectiveness of performance information results use. In the dimension of using performance information results, the distributed computing and analysis processing technology of big data can assist the decision support system, and the use of information can be shifted from micromanagement to decision support, to realize the scientific use of performance information and improve the quality of enterprise management decisions.


2020 ◽  
Vol 4 (1) ◽  
pp. 55
Author(s):  
Yuhao Gong

In order to further improve the enterprise performance evaluation system, it is necessary to study the application value of EVA management system in China's listed companies. Based on the data of ICBC from 2016 to 2018, this paper uses EVA method to evaluate and analyze it.


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