Design and application of a wavelet neural network program for evaluation of goodwill value in corporate intellectual capital

Yuan, Bei; Wang, Fusheng; Di, Bao

doi:10.3166/isi.23.5.185-200

Cited by 5 publications

(3 citation statements)

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“…Under this background, this paper focuses on the application of artificial intelligence in college students' autonomous learning [4]. It introduces the implicit knowledge base based on artificial neural network, describes the neural network model and the neural network algorithm process, uses the forgetting curve to establish a knowledge forgetting mathematical model [5], and finally carries out programming design of the English autonomous learning system with Visual Studio computer programming technology, SQL server database and B/S system architecture. Through detailed analysis of system requirements, overall structure, database requirements and system flows, this paper specifies the functional module settings and each component of the system [6].…”

Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence in Autonomous English Learning among College Students

Han¹

2019

Int. J. Emerg. Technol. Learn.

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To improve the English proficiency of college students, this paper attempts to promote autonomous English learning among these students using artificial intel-ligence technology. Specifically, the principles, features and application fields of artificial intelligence were introduced in details, and the requirements, structure, database and processes of autonomous English learning systems were discussed at length. On this basis, the backpropagation (BP) neural network, a typical artifi-cial intelligence technique, was selected to design the modules of the autonomous English learning system for college students. The proposed system was then im-plemented in integrated open environment of Visual Studio, the architecture of the browser/server system and the SQL Server database on the Windows platform. The results show that the proposed system provides college students with intelli-gent and open self-evaluation tests and effective learning feedbacks. The research findings shed new light on improving the English learning of college students and reliving the pressure on college English teachers.

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Section: Introductionmentioning

confidence: 99%

Application of Artificial Intelligence in Autonomous English Learning among College Students

Han¹

2019

Int. J. Emerg. Technol. Learn.

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“…In general, the majority of scientists Manzaneque et al [5], Yuan et al [6], Agostini et al [7] treat the intellectual capital management system of an innovation-oriented system as something that, by its nature, a management system should bring, namely, a certain result. The results of intellectual activity have a high level of novelty in the processes of formation and development of intellectual capital, which is associated with the socio-psychological characteristics of the individual, and the distinctive features of her thinking.…”

Section: Literature Reviewmentioning

confidence: 99%

A Model for Countering the Information and Technical Threats of Intellectual Capital Management of Innovation-Oriented Systems in the Engineering Sector

Yemelyanov¹,

Ніконенко²,

Sytnyk³

et al. 2022

ISI

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The modern economy is characterized by a sharp increase in the role of non-material factors (information and knowledge) in ensuring the competitiveness of individual enterprises and institutions, as well as national economies as a whole. Under these conditions, the ability to create, use and increase intellectual capital is the basis for the economic growth of engineering business entities. The main purpose of the study is to model the counteraction to the main threats of intellectual capital for innovation-oriented systems in the engineering sector of the economy. The relevance of the study is given by the fact that the formation and use of technical, economic, industrial, and other types of knowledge, the totality of which forms intellectual capital, is becoming an urgent problem for modern systems tuned to innovative development. The threats to managing the intellectual capital of innovation-oriented systems are now the most significant, since the achievement of the ultimate goals of the system itself depends on the efficiency of the use of intellectual capital. Taking this into account, intellectual capital is becoming a real and valuable target of criminal encroachments today, which requires scientists to form a clear model for countering these goals. The research methodology involves the use of mathematical methods of information support for the process of counteracting the negative impact of threats. According to the results of the study, we presented the modeling process. As a result, a model was built to counteract the main threats of intellectual capital for innovation-oriented systems in the engineering sector of the economy. Further research requires the construction of a mathematical mechanism for responding to new challenges to the intellectual capital management system for innovation-oriented systems.

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“…These methods estimate the parameters of the future TFS with accurate forecast models. The typical models include linear ones like time series method [1][2][3][4], Kalman filtering [5][6][7][8] and exponential smoothing, as well as nonlinear ones like wavelet analysis [10][11][12] and chaos theory [13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Forecast of Traffic Flow State During Large Competition Events

Li¹

2020

RIA

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The forecast of traffic flow state (TFS) is the key to the effective control of roads, especially during large competition events. To enhance the accuracy of TFS forecast, this paper puts forward a way to predict the TFS on the peripheral roads of large competition events, which is based on support vector regression (SVR) and parameter optimization. Firstly, the tensor recovery algorithm was adopted to fill up the missing data. Then, the simulated annealing (SA) algorithm was applied to optimize the SVR parameters like the penalty factor, and the insensitive loss. Next, a TFS forecast model for the road section near large venues was established based on the SVR and the optimized parameters. The example analysis shows that the parameter optimization improved the accuracy of the SVR forecast model, making the predicted results closer to the actual data. The proposed model greatly facilitates the management and control of road traffic during large competition events.

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Design and application of a wavelet neural network program for evaluation of goodwill value in corporate intellectual capital

Cited by 5 publications

References 0 publications

Application of Artificial Intelligence in Autonomous English Learning among College Students

Application of Artificial Intelligence in Autonomous English Learning among College Students

A Model for Countering the Information and Technical Threats of Intellectual Capital Management of Innovation-Oriented Systems in the Engineering Sector

Forecast of Traffic Flow State During Large Competition Events

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