scholarly journals Enterprise Performance Management following Big Data Analysis Technology under Multisource Information Fusion

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Zhengna Qin ◽  
Haojie Liao ◽  
Ling Chen ◽  
Lei Zhang
Keyword(s):  
Big Data ◽  
Performance Management ◽  
Information Fusion ◽  
High Efficiency ◽  
Enterprise Management ◽  
Enterprise Performance ◽  
Fusion Model ◽  
Fusion Algorithm ◽  
Maximum Acceleration ◽  
Index Weight

With the development of the Internet, big data collection, analysis, and processing are flourishing. The study aims to explore the performance management of power enterprises based on multisource information fusion and big data. First, the application of big data to enterprise management is analyzed. Second, the multisource information fusion method is introduced, and the multisource information fusion model is implemented. Finally, the fuzzy language algorithm is used to evaluate the performance management of power enterprises. The results show that the proposed multisource information fusion algorithm has high efficiency in evaluating enterprise performance management. The evaluation result is closer to the actual value than other algorithms, and the maximum acceleration ratio can reach 7, indicating that the algorithm is suitable for processing big data. The performance evaluation shows that enterprises pay most attention to the quality of their products; the weight reached 0.414; and the index weight difference is large. This study promotes the reform of the performance management mode and improves the management efficiency of enterprises through the proposed enterprise performance management strategy. It provides a great reference for the application of big data and information fusion technology.

The KPI Evaluation Method of Logistics Service in Railway Logistics Enterprises

2014 ◽  
Vol 933 ◽  
pp. 930-934
Author(s):  
Xiao Liu ◽  
Xiao Ning Zhu
Keyword(s):  
Performance Management ◽  
Evaluation Method ◽  
Enterprise Performance ◽  
Logistics Service ◽  
Logistics Enterprises ◽  
Index Weight

To improve the level of enterprise performance management and logistics service,this paper proposed the KPI evaluation method of logistics service in railway logistics enterprises. By analyzing the strategic target of railway logistics enterprises logistics service, I decomposed the railway logistics enterprises strategic target to get the key evaluation indicators system of the logistics service in railway logistics enterprises, and used AHP to determine the index weight. Finally, I used the percentage method to evaluate the logistics service of railway logistics enterprises.

scholarly journals Analysis on Innovation Countermeasures of Human Resource Performance Management of Pesticide Enterprises in the Era of Big Data

2020 ◽  
Vol 9 (7) ◽  
pp. 210
Author(s):  
Changzhi Li ◽  
Zhongcheng Pan ◽  
Jing Weng ◽  
Pumin Li
Keyword(s):  
Big Data ◽  
Resource Management ◽  
Human Resource Management ◽  
Performance Management ◽  
Human Resource ◽  
Technological Development ◽  
Rapid Development ◽  
Enterprise Management ◽  
Digital Era ◽  
Big Data Technologies

In today’s rapid development of network technology, big data has been more and more applied. In the information and digital era, technological development is constantly promoting the reform and progress of the industry. In enterprise management, more and more big data technologies and concepts are applied. In terms of the application of big data in human resource management performance, the relevant technology is applied to human resource performance management has brought a new mode, which plays a prominent role in improving the efficiency of human resource performance management. However, there are still some problems in practical application. This paper, taking pesticide enterprises as an example, studies the problems and countermeasures of human resource management in such enterprises in the era of big data, so as to provide some ideas for guiding relevant enterprises to make good use of big data in human resource performance management.

scholarly journals Full-Vector Signal Acquisition and Information Fusion for the Fault Prediction

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Lei Chen ◽  
Jie Han ◽  
Wenping Lei ◽  
Yongxiang Cui ◽  
Zhenhong Guan
Keyword(s):  
Data Acquisition ◽  
Information Fusion ◽  
Prediction Method ◽  
Fault Prediction ◽  
Vibration Measurement ◽  
Signal Acquisition ◽  
Vector Data ◽  
Fusion Model ◽  
Fusion Algorithm ◽  
Full Vector

Fault prediction is the key technology of the predictive maintenance. Currently, researches on fault prediction are mainly focused on the evaluation of the intensities of the failure and the remaining life of the machine. There is lack of methods on the prediction of fault locations and fault characters. To satisfy the requirement of the prediction of the fault characters, the data acquisition and fusion strategies were studied. Firstly, the traditional vibration measurement mechanism and its disadvantages were presented. Then, the full-vector data acquisition and fusion model were proposed. After that, the sampling procedure and information fusion algorithm were analyzed. At last, the fault prediction method based on full-vector spectrum was proposed. The methodology is that of Dr. Bently and Dr. Muszynska. On the basis of this methodology, the application study has been carried out. The uncertainty of the spectrum structure can be eliminated by the designed data acquisition and fusion method. The reliability of the diagnosis on fault character was improved. The study on full-vector data acquisition system laid the technical foundation for the prediction and diagnosis research of the fault characters.

Research of Selective and Incremental Information Fusion Method Based on Bayesian Network

2013 ◽  
Vol 397-400 ◽  
pp. 2060-2063
Author(s):  
Li Wei Zhang ◽  
Jing Zhang ◽  
Yan Sun
Keyword(s):  
Decision Making ◽  
Bayesian Network ◽  
Information Fusion ◽  
Relevant Information ◽  
Fusion Method ◽  
Fusion Model ◽  
Fusion Algorithm ◽  
Information Selection ◽  
Incremental Information ◽  
Better Than

This paper presents a selective incremental information fusion method based on Bayesian network, so that the fusion algorithm can actively select the most relevant information and decision-making, and can make the fusion model to adapt to the dynamic changes in the external environment, and sensor information selection, fusion, decision-making integrated in the framework of Bayesian network . The experimental results show that this method is better than the traditional method.

Research on Information Fusion of Two New DLL Discriminator Algorithms

2014 ◽  
Vol 543-547 ◽  
pp. 1223-1226
Author(s):  
Jian Cao ◽  
Cong Yan
Keyword(s):  
Neural Network ◽  
Expert System ◽  
Information Fusion ◽  
Fuzzy Neural Network ◽  
Theoretical Method ◽  
Fusion Model ◽  
Fusion Algorithm ◽  
Feature Level Fusion ◽  
Fuzzy Neural ◽  
Level Fusion

After information fusion model has been established, the feature-level fusion algorithm based on fuzzy neural network and expert system is proposed, in which the expert system has been embedded into fuzzy neural network so that it could choose the membership function and adjust the network structure. At the same time, for code tracking loop, two new code phase discriminator algorithms based on DLL structure is proposed. Evidence theory has been applied to achieve the decision-making level fusion. The performances of the two algorithms were studied by using theoretical method and experimental method with analog IF signal data and actual IF signal data respectively. Then, the results of feature-level fusion have been taken as the evidences to construct the frame of discernment. The research results show that the process of information fusion has abilities of adapting and self-learning.

scholarly journals Using Big Data Fuzzy K-Means Clustering and Information Fusion Algorithm in English Teaching Ability Evaluation

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Chen Zhen
Keyword(s):  
Big Data ◽  
Information Fusion ◽  
Clustering Algorithm ◽  
Measurement Data ◽  
Weighted Average ◽  
Weighting Factor ◽  
Fusion Algorithm ◽  
English Teaching ◽  
Teaching Ability ◽  
Ability Evaluation

Aiming at the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, an English teaching ability evaluation algorithm based on big data fuzzy K-means clustering and information fusion is proposed. Firstly, the author uses the idea of K-means clustering to analyze the collected original error data, such as teacher level, teaching facility investment, and policy relevance level, removes the data that the algorithm considers unreliable, uses the remaining valid data to calculate the weighting factor of the modified fuzzy logic algorithm, and evaluates the weighted average with the node measurement data and gets the final fusion value. Secondly, the author integrates the big data information fusion and K-means clustering algorithm, realizes the clustering and integration of the index parameters of English teaching ability, compiles the corresponding English teaching resource allocation plan, and realizes the evaluation of English teaching ability. Finally, the results show that using this method to evaluate English teaching ability has better information fusion analysis ability, which improves the accuracy of teaching ability evaluation and the efficiency of teaching resources application.

MODERN PROBLEMS OF ACCOUNTING AND ANALYTICAL ENSURING FINANCIAL RESULTS MANAGEMENT

2020 ◽  
Author(s):  
Yuliia Peniak ◽  
◽  
Nataliia Horokhovatska ◽  
Keyword(s):  
Performance Management ◽  
Enterprise Management ◽  
Goods And Services ◽  
Financial Condition ◽  
General Evaluation ◽  
Net Profit ◽  
Business Entities ◽  
Results Management ◽  
Main Components ◽  
The Impact

The main purpose of any enterprise in the market economy is to obtain high financial results. One of the main conditions for the effective functioning of the enterprise is ability to generate profit in the amount that will create the financial basis for further development and expansion of the enterprise, comply with social and material needs, ensure competitiveness in the market of goods and services. The need for accounting and analytical management of financial results stems from needs of owners, the state and employees in information that will enable them to identify patterns and trends in financial results, identify and assess the main factors influencing the process of their creation, distribution and usage, identify reserves and thus increase the level of profitability. Despite the significant scientific contribution in the field of research of financial results of the enterprises, the issue of improvement aims to the accounting and analytical maintenance of management of financial results of the enterprise remains actual. That is why the purpose of the study is to substantiate the theoretical and practical aspects and develop approaches to improving the mechanism of formation of accounting and analytical support for the management of financial results of the enterprise. Accounting and analytical management of financial results of the enterprise is a set of interconnected elements of production and management system, activities carried out by the subject of management, creation of a certain structure, as well as collection, accumulation, storage and analysis of information necessary for effective operation of the enterprise. The main components of the study of accounting and analytical support of financial performance management are the formation of methods of analysis, control and forecasting of financial results, which requires specification of the components of the analytical and controlled process within the organizational and information model. Namely, the formation of reliable information about the financial condition of the enterprise, the analysis of economic indicators of the enterprise is of great importance in the system of general evaluation of business entities. Their research makes it possible to assess the dynamics of the structure of income and expenses, to determine the impact of factors on the company's profit from various activities, as well as to find reserves to increase the net profit of enterprises. Thus, the improvement of accounting and analytical support of enterprise management is based on the use of modern forms, methods and principles that place new demands on the formation of unbiased, complete, timely, clear and useful accounting and analytical information about the enterprise and its financial results.

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