scholarly journals Framework of the Smart Finance and Accounting Management Model under the Artificial Intelligence Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yaping Chen
Keyword(s):  
Artificial Intelligence ◽  
Asset Management ◽  
Financial Management ◽  
Large Scale ◽  
Logical Structure ◽  
Evaluation Index System ◽  
Management Model ◽  
Value Analysis ◽  
Accounting Management ◽  
Enterprise Groups

With the establishment of modern enterprise systems and the emergence of some large-scale enterprise groups formed through asset reorganization, industry alliances, and cross-industry mergers, new requirements have been put forward for the financial management mode of enterprise groups. This article mainly studies the development of the smart accounting management model architecture under the artificial intelligence perspective. On the accounting sharing service platform, the accounting sharing center does not belong to the logistics branch of any region. Through the accounting sharing center, it provides unified and standardized accounting, asset management, currency revenue and expenditure, etc., for the branches of the logistics company. At the same time, in the network environment, the financial and accounting sharing platform is not unilaterally closed. As each branch under unified management, it has the power to feedback, suggest, and supervise the financial and accounting sharing platform. When testing, one only needs to focus on the external properties of the program, without considering the internal logical structure and internal characteristics of the program at all. The system under test is regarded as a sealed black box, and the boundary value analysis method, the equivalence class division method, and causality are used. Technical methods such as the graph method and error speculation method are tested at the system interface to detect whether the function of each test can receive and output the results correctly. The implementation of the accounting management model of accounting shared services must ensure that the evaluation results of related work are objective and accurate. It is necessary to ensure that the evaluation index system has a high degree of quantification. In the specific scoring, the full score system can be used to score points by experts to ensure the objectivity of the evaluation results and accuracy while improving the operability and enforceability of the evaluation work. The average value of the operating net profit margin is 0.088731, and the median value is 0.082263. The results show that artificial intelligence technology has greatly promoted the development of the smart accounting management model architecture.

scholarly journals Research on Financial Risks of Robo-Advisor Platforms

2020 ◽  
Vol 218 ◽  
pp. 01035
Author(s):  
Ruilin Liu
Keyword(s):  
Artificial Intelligence ◽  
Capital Market ◽  
Financial Management ◽  
Management Model ◽  
Financial Risks ◽  
Urgent Problem ◽  
Development Status ◽  
Internet Finance ◽  
Investment Process ◽  
Financial Technology

With the vigorous development of China’s Internet finance and financial technology, Roboadvisors have become more and more popular among investors. This new investment and financial management model that relies on Internet platforms, artificial intelligence, quantitative trading technologies will have a greater impact on the capital market once the financial risks caused. How to standardize the Robo-advisory platform, effectively control the financial risks in the investment process and protect the interests of investors is an urgent problem in the Robo-advisory industry. Firstly, this article analyzes the development status of domestic Robo-advisory platforms. Then it puts forward suggestions on how the Robo-advisory industry can face the dual pressures of survival and profit in the context of stricter supervision by analyzing various financial risks and causes of the platform. It aims to promote the sound development of the investment advisory market in the context of financial technology.

scholarly journals Financial Crisis Warning of Financial Robot Based on Artificial Intelligence

2020 ◽  
Vol 34 (5) ◽  
pp. 553-561
Author(s):  
Wenxia Li
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Financial Crisis ◽  
Financial Management ◽  
Evaluation Index System ◽  
Actual Application ◽  
Proposed Model ◽  
Fuzzy Neural ◽  
Artificial Neural Network Ann ◽  
Hierarchical Evaluation

Robotic process automation (RPA) financial robot provides a modern and intelligent tool for financial management, and financial business processing. Currently, more than 32% of financial applications are implemented by RPA financial robot. As an alternative of human in operation and judgment, the financial robot faces some inevitable risks in actual application. So far, there is a severe lack of theoretical or practical research into the risks or operational guarantees of RPA financial robot. To bridge the gap, this paper proposes a financial crisis warning model for financial robot based on artificial neural network (ANN), drawing on the merits of artificial intelligence (AI) like self-learning, self-adaptation, and self-adjustment. Specifically, a hierarchical evaluation index system (EIS) and the corresponding warning strategy were prepared for the financial crisis of RPA financial robot. Next, the financial crisis of RPA financial robot was evaluated both statically and dynamically. Then, antecedent and subsequent networks were merged into a fuzzy neural network (FNN) for predicting financial crisis of RPA financial robot. The proposed model was proved effective and accurate through experiments.

SEARCH FOR A NEW MANAGEMENT MODEL FOR THE DEVELOPMENT, PRODUCTION AND IMPLEMENTATION OF WORLD-CLASS HYDROGEN TECHNOLOGIES

2020 ◽  
Vol 3 (7) ◽  
pp. 114-119
Author(s):  
V. F. UKOLOV ◽  
◽  
E. N. OZHIGANOV ◽  
Yu. V. RAGULINA ◽  
V. V. ARKHIPOV ◽  
...  
Keyword(s):  
Large Scale ◽  
The State ◽  
Type Structure ◽  
Management Model ◽  
World Class ◽  
Hydrogen Technologies

After the research, the authors came to the conclusion: it is necessary to get a new, interstate platform-type structure for the development, production and large-scale implementation of civil hydrogen technologies for various fields of activity and the state.

Large-Scale Application of Biofiltration Swale Runoff Management Practices

2007 ◽  
Vol 2 (2) ◽  
Author(s):  
William C. Lucas
Keyword(s):  
Large Scale ◽  
Management Practices ◽  
Peak Flow ◽  
Low Impact Development ◽  
Urban Runoff ◽  
Management Model ◽  
Check Dams ◽  
Runoff Reduction ◽  
Impervious Area ◽  
Hydrologic Responses

Retaining rainfall where it lands is a fundamental benefit of Low Impact Development (LID). The Delaware Urban Runoff Management Model (DURMM) was developed to address the benefits of LID design. DURMM explicitly addresses the benefits of impervious area disconnection as well as swale flow routing that responds to flow retardance changes. Biofiltration swales are an effective LID BMP for treating urban runoff. By adding check dams, the detention storage provided can also reduce peak rates. This presentation explores how the DURMM runoff reduction approach can be integrated with detention routing procedures to project runoff volume and peak flow reductions provided by BMP facilities. This approach has been applied to a 1,200 unit project on 360 hectares located in Delaware, USA. Over 5 km of biofiltration swales have been designed, many of which have stone check dams placed every 30 to 35 meters to provide detention storage. The engineering involved in the design of such facilities uses hydrologic modeling based upon TR-20 routines, as adapted by the DURMM model. The hydraulic approach includes routing of flows through the check dams. This presentation summarizes the hydrological network, presents the hydrologic responses, along with selected hydrographs to demonstrate the potential of design approach.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

Prospects for Cooperation Between Russia and the Republic of Korea in the Fields of Big Data, Network and Artificial Intelligence for the Development of the Digital Economy

2021 ◽  
Vol 65 (8) ◽  
pp. 51-60
Author(s):  
Yujeong Kim
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Large Scale ◽  
Technology Development ◽  
Technological Development ◽  
Digital Economy ◽  
Republic Of Korea ◽  
Data Network ◽  
Leading Position ◽  
The Government

Today, each country has interest in digital economy and has established and implemented policies aimed at digital technology development and digital transformation for the transition to the digital economy. In particular, interest in digital technologies such as big data, 5G, and artificial intelligence, which are recognized as important factors in the digital economy, has been increasing recently, and it is a time when the role of the government for technological development and international cooperation becomes important. In addition to the overall digital economic policy, the Russian and Korean governments are also trying to improve their international competitiveness and take a leading position in the new economic order by establishing related technical and industrial policies. Moreover, Republic of Korea often refers to data, network and artificial intelligence as D∙N∙A, and has established policies in each of these areas in 2019. Russia is also establishing and implementing policies in the same field in 2019. Therefore, it is timely to find ways to expand cooperation between Russia and Republic of Korea. In particular, the years of 2020and 2021marks the 30th anniversary of diplomatic relations between the two countries, and not only large-scale events and exchange programs have prepared, but the relationship is deepening as part of the continued foreign policy of both countries – Russia’s Eastern Policy and New Northern Policy of Republic of Korea. Therefore, this paper compares and analyzes the policies of the two countries in big data, 5G, and artificial intelligence to seek long-term sustainable cooperation in the digital economy.

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