Application Of Artificial Intelligence Technology Research Articles

Applications of artificial intelligence methods in the energy sector

The article describes the relevance of application of artificial intelligence technologies in the energy sector. The theoretical and practical research was conducted to summarize and substantiate the classification of artificial intelligence methods used in the energy sector. It includes three groups of methods. The analysis of domestic and foreign practice of applying artificial intelligence methods in the energy sector allowed for the identification of energy tasks that can improve the efficiency of energy enterprises. The artificial intelligence technologies should be used along with energy transformation, digital transformation, and integration of energy sectors. These processes are described in the article. A deep analysis of the application of artificial intelligence methods and tasks in the energy sector was conducted and examples of applications of artificial intelligence technologies were provided.

Research on the Application of Artificial Intelligence Technology in the Field of Network Security

Research on the Application of Artificial Intelligence Technology in the Field of Network Security

Методологические инструменты управления орошением с искусственным интеллектом

Purpose: to develop the concept of irrigation management systems using integrated artificial intelligence technologies. Materials and methods. The working hypothesis of the research was the assumption of the priority of the cluster application of artificial intelligence technologies in solving urgent problems of irrigation management. At the same time, the basis of the information-computing unit of the irrigation control system should be deterministic algorithms using proven solutions. Results. Within the framework of the proposed concept, a neural network can be used as the basis for solving a problem, or it can only be used to adapt the parameters of the models used. The impact points of traditional, deterministic - analytical irrigation management systems and artificial intelligence technologies are determined by the need to adapt parameters, fine-tune the coefficients of the methodological tools used. At the same time, the scope of application of artificial intelligence in solving problems of irrigation management is quite wide. Artificial intelligence technologies can be used to solve the problems of irrigation planning and operational management, image recognition in satellite monitoring of soil moisture, interpolation of soil moisture data by area, forecasting the soil moisture profile. An algorithm using artificial intelligence technologies to improve the reliability of forecasting the total water consumption of irrigated crops in the regional and landscape aspect is developed by research. The proposed algorithm allows the system to self-learn and refine the regional values of bioclimatic coefficients, with respect to cumulative influence of local factors. Conclusions: a concept has been developed and new scientific approaches have been proposed to effectively solve the problem of adapting the parameters of methodological irrigation management tools at the level of an irrigated field, and even taking into account intra-field variability.

ИСПОЛЬЗОВАНИЕ ТЕХНОЛОГИЙ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА ДЛЯ РЕШЕНИЯ МАРКЕТИНГОВЫХ ЗАДАЧ

The introduction of artificial intelligence technologies into the marketing system can create significant competitive advantages for the company, increase efficiency, productivity and stimulate revenue growth. The article discusses the application of artificial intelligence technologies in modern marketing. The analysis and comparison of various tools implemented on the basis of artificial intelligence with the tasks of marketing and improving the efficiency of the business as a whole is also carried out.

Research on the application of artificial intelligence technology to promote the high-quality development path of manufacturing industry

At present, in the new round of scientific and technological development, artificial intelligence brings development opportunities for the upgrading of traditional industries and the cultivation of emerging industries, which is conducive to the upgrading of economic structure to achieve high-quality development. How to promote the application of AI technology in the manufacturing scene of manufacturing enterprises to promote the improvement of product quality of manufacturing enterprises? This paper analyzes the present situation of artificial intelligence application and put forward six major scenarios the artificial intelligence in manufacturing industry, promote the digital transformation of manufacturing enterprises from sales C2S level to deepen the manufacturing C2M level, through artificial intelligence to promote the manufacturing industry chain upgrade, improve the quality of export products, improve the export competitiveness of China's manufacturing industry. By analyzing the problems existing in the application of artificial intelligence in China, targeted suggestions and countermeasures are put forward.

S-47-3: APPLICATION OF AI FOR SCREENING CARDIOVASCULAR DISEASE

Recent advancements in information technologies and computer science brought dramatic changes not only in the field of business but also in the field of medicine. By analyzing big data using artificial intelligence techniques, especially deep learning, computers now have similar or even better diagnostic performance than trained physicians in medical image interpretation. In addition to their speed, reproducibility, and tirelessness, these artificial intelligence programs are starting to reveal their possibility to find hidden information from medical images. For example, studies have shown that not only present arrhythmias but also the presence of myocardial dysfunction and latent arrhythmias can be found in a body-surface ECG. Given the extremely high prevalence of hypertension worldwide, screening the cardiovascular risk in all patients with hypertension has not been realistic so far. However, such artificial intelligence may become a wider and more ubiquitous tool for the general screening of cardiovascular risk. Furthermore, big data generated from digital tools surrounding our daily life, such as laptops, smartphones, and smartwatches may provide further information regarding healthy or risky lifestyles, with which the risk stratification can be personalized. Thus, the current achievement in the application of artificial intelligence technologies in medicine and future perspective in regard to cardiovascular risk screening in patients with hypertension will be summarized in the talk.

«ОТРАСЛИ. УСТОЙЧИВОСТЬ» – ПРОГРАММНАЯ МОДЕЛЬ ДЛЯ НЕЧЕТКОГО АНАЛИЗА ЭКОНОМИЧЕСКОЙ УСТОЙЧИВОСТИ ОТРАСЛЕЙ

The aim of this article is to describe the implementation of the new “Industry. Resilience” software program for fuzzy modeling of industries and provide a brief overview of the scientific methods employed in the program. The “Industry. Resilience” program utilizes the following basic technologies in industry modeling: • Matrix aggregate calculator; • Structuring of industry indices using weighted average technologies; • Industry R-lenses; • Algorithms for intelligent data filtering; • Strategic matrix 4x6 in dynamic execution. Through the modeling conducted in the program, it is demonstrated that an industry maintains its economic resilience under the fulfillment of three basic conditions: a) preserving a minimum net profitability of 5–7%; b) achieving an asset turnover rate of at least 1.5 times per year; c) receiving government credit through supplier factoring, resulting in a financial leverage ratio of approximately 1.6. Together, these conditions are expected to yield a return on equity (ROE) of around 20% annually, ensuring significant private capital attraction to the industry, particularly with the provision of additional government guarantees for capital protection (a real option for businesses). The application of artificial intelligence technologies to economic analysis of industries (including their resilience) has already yielded impressive scientific results, but the main achievements are anticipated in the future with the accumulation of data and knowledge across a wide range of economic entities.

Research and Application of Artificial Intelligence Technology in the Teaching of Ice and Snow Sports Mixed Courses in Universities

Research and Application of Artificial Intelligence Technology in the Teaching of Ice and Snow Sports Mixed Courses in Universities

Retracted: Application of Artificial Intelligence Technology in Music Education Supported by Wireless Network

Retracted: Application of Artificial Intelligence Technology in Music Education Supported by Wireless Network

Retracted] Construction and Case Analysis of Sensor News Whole Chain Production Model Based on Artificial Intelligence Technology

In the current era of data explosion, people’s media have access to a large amount of information through the Internet. How to generate effective and realistic news and let interested people accept it is a hot topic in the current news media industry. The continuous development of sensor technology and the application of artificial intelligence technology enable the directional push of intelligent sensor news to be realized. Intelligent sensor media uses sensor technology to monitor and collect information and then combines artificial intelligence and big data to process the information. After obtaining effective media information, it will be pushed in a targeted way and tracked for analysis. By analyzing the current situation and difficulties of sensor news, this paper seeks for an effective combination of artificial intelligence technology and sensor news and establishes a whole process directional push model for sensor news production and thermal tracking analysis. This model is pioneering and practical in the media field. In order to further verify the effectiveness of the model, the important application field of sensor news is selected as the simulation research object, and the specific selection and layout of sensors, the data analysis obtained by sensors, the push of environmental news, and the thermal tracking analysis are simulated. The results show that through data analysis, news editing, and targeted push of water pollution environmental news, the news has gained a certain degree of attention among the main design media. The popularity index is estimated based on the number of likes and comments forwarded by the current mainstream Internet media platforms (Toutiao, Tiktok, and Weibo). The environmental pollution news thermal index of the sensor reached the highest thermal index score of 12 on the 26th day after the activity. On the Weibo client, the message reached the highest heat index of 14 points on the 28th. The simulation analysis of actual cases further illustrates the advantages of this design framework.

Research on the Construction of Professional Competence of University Librarians in the Era of Artificial Intelligence

Artificial intelligence is an important feature and development trend of today's era, which has had a profound impact and challenge on various industries, including libraries as important institutions of knowledge service. The application of artificial intelligence technology provides new opportunities and possibilities for libraries, and also puts forward new requirements and expectations for the professional competence of librarians. Starting from the challenges and opportunities faced by librarians in the era of artificial intelligence, this article analyzes the connotation and composition of the professional competence of librarians, explores the goals, contents and approaches of professional competence construction for librarians in the era of artificial intelligence, and aims to provide references for improving the professional quality and service level of librarians and promoting the innovative development of library services.

DuFNet: Dual Flow Network of Real-Time Semantic Segmentation for Unmanned Driving Application of Internet of Things

The application of unmanned driving in the Internet of Things is one of the concrete manifestations of the application of artificial intelligence technology. Image semantic segmentation can help the unmanned driving system by achieving road accessibility analysis. Semantic segmentation is also a challenging technology for image understanding and scene parsing. We focused on the challenging task of real-time semantic segmentation in this paper. In this paper, we proposed a novel fast architecture for real-time semantic segmentation named DuFNet. Starting from the existing work of Bilateral Segmentation Network (BiSeNet), DuFNet proposes a novel Semantic Information Flow (SIF) structure for context information and a novel Fringe Information Flow (FIF) structure for spatial information. We also proposed two kinds of SIF with cascaded and paralleled structures, respectively. The SIF encodes the input stage by stage in the ResNet18 backbone and provides context information for the feature fusion module. Features from previous stages usually contain rich low-level details but high-level semantics for later stages. The multiple convolutions embed in Parallel SIF aggregate the corresponding features among different stages and generate a powerful global context representation with less computational cost. The FIF consists of a pooling layer and an upsampling operator followed by projection convolution layer. The concise component provides more spatial details for the network. Compared with BiSeNet, our work achieved faster speed and comparable performance with 72.34% mIoU accuracy and 78 FPS on Cityscapes Dataset based on the ResNet18 backbone.

Conceptual basis of Development and Application of Artificial Intelligence Technologies in Forecasting Economic Processes

Conceptual basis of Development and Application of Artificial Intelligence Technologies in Forecasting Economic Processes

Prospects for the development and application of artificial intelligence technologies in Russia

The paper examines the prospects for the design and introduction of artificial intelligence technologies in Russia’s economic system. Based on official rankings of the globe’s leading organizations and the tools of economic and mathematical modeling, we have assessed the impact of artificial intelligence technologies on the level of competitiveness of the national economy. The obtained results indicate a rather strong impact of artificial intelligence technologies on the level of competitiveness of the national economy. We have also analyzed the current level of development of artificial intelligence technologies in the Russian Federation, and pointed out significant risks and threats caused by the introduction of these technologies. The development of artificial intelligence technologies can lead to the fact that, at some point, human capital might cease to be necessary in the economy; simply put, human capital will become an unnecessary factor in economic development. In order for humanity to cope with the challenges, driven by the development of artificial intelligence technologies, the implementation of intelligent information systems should not be thoughtless; their implementation should be reasonable and extremely careful. Furthermore, we suggest how to make the use of artificial intelligence technologies in Russia’s economy more efficient. The conclusion is that, first of all, Russia should develop artificial intelligence technologies in relation to the real sector of the economy in order to increase the competitiveness of domestic goods and services and achieve the goal of import substitution. Artificial intelligence technologies should aim at improving the performance of the public health service.

2022 Survey on the Developmental Trend of Smart eHealth in Taiwan

<p>世界衛生組織不僅將智慧醫療（eHealth）定義為資通訊科技在醫療及健康領域的應用 ，亦認為數位科技（Digital technologies）有助於推進全民健康覆蓋以及健康福祉相關的永續發展目標 ，衛生福利部第九期醫療網，亦將創造具韌性且智能的醫療照護體系訂為總目標之一。財團法人醫院評鑑暨醫療品質策進會持續於本（2022）年度進行全國醫院智慧醫療發展問卷普查。在疫情影響下，視訊診療、數位學習系統及遠距教學等導入比率較高，而環境管理智慧化導入則相較門急住診等應用要來得低。AI技術的應用是醫學中心未來一年的發展重點，非醫學中心則放在資訊安全。醫院政策、醫療人員需求及衛生政策分別為前三項推動的關鍵因素，差別在於地區醫院更看重醫院政策與衛生政策。</p> <p> </p><p>The World Health Organization defined eHealth as “the use of information and communications technology in support of health and health-related fields”, and it considered digital technologies conducive to promoting universal health coverage as well as to sustainable development goals related to health and welfare. The ninth phase of the medical network of the Ministry of Health and Welfare has established one of its overall goals as establishing a healthcare system that is resilient and smart. As in the past, in 2022, the Joint Commission of Taiwan continued to conduct a census of the development of eHealth in medical institutions in Taiwan. Affected by the COVID-19 pandemic, video teleconferencing for disease diagnosis and treatment, digital learning systems, and distant teaching have been more widely introduced compared to the application of environmental smart management in outpatient clinics, emergency departments, and inpatient clinics. In the following year, the application of artificial intelligence technology will be a key development point for medical centers; by contrast, the focus of non-medical centers will be information security. The top three key factors for promoting eHealth among medical institutions will be hospital policies, medical personnel demands, and health policies, with the only difference being that local community hospitals will focus more on hospital policies and health policies.</p> <p> </p>

Application of Artificial Intelligence Technology in Power System Stability Assessment

In order to realize power system stability assessment, the author studies a deep Convolutional neural network algorithm for power system operation stability assessment. Combining short-term simulation with neural network prediction to reduce the time required for transient stability analysis can be used in various simulation analysis scenarios. A deep Convolutional neural network algorithm is used to improve the performance of the security system. A deep Convolutional Neural Network (CNN) is used to construct a multi-layer and multi-column neural network to evaluate the stability of electrical networks. The system significantly improves the efficiency of evaluating specific faults, particularly enhancing the specificity of evaluation judgments, and reducing the additional maintenance workload caused by providing stability warnings for the operation status of faultless power grids. The experimental results indicate that, the system has shown certain advantages in terms of sensitivity to the judgment of various types of faults mentioned above, especially improving the sensitivity to other faults with unknown causes, which is 10.8 percentage points higher than the previous system. The smallest difference in the improvement of sensitivity indicators is the sensitivity to ground faults. The previous system reached 95.4%, while this system increased by 3.9 percentage points to 99.3%. It is proved that the deep CNN is applicable to the task of power system operation stability assessment.

Логістика 5.0: синергія штучного інтелекту та людини в контексті сталого розвитку

The emergence of ChatGPT in late 2022 brought unprecedented technological changes in many areas of business and society, raising the level of interest in generative artificial intelligence (AI) technology to a whole new level. The use of AI has become especially relevant in the field of logistics, where the need to optimize processes and reduce costs has always been high. The article analyzes the current trends in the development and application of artificial intelligence technologies in the field of logistics. The main challenges associated with the introduction of AI in logistics are outlined, including: the biased attitude of customers to interaction with AI; responsible generation of requests to AI in compliance with data privacy rules; the need to develop digital competence, etc. The conception of «Logistics 5.0», in which a person and artificial intelligence act as equal elements of the logistics system, is considered. The following main aspects of Logistics 5.0 are analyzed in the context of sustainable development: human-centeredness, viability, and sustainable development. Human-centeredness in Logistics 5.0 assumes that the human is central to the logistics system, and there is also a rethinking of the Human – Machine (H2M) interaction in general. Viability in Logistics 5.0 is the ability of the logistics system to exist (function) under any conditions, which is achieved through stability, flexibility, and adaptability. Sustainable development in Logistics 5.0 involves the functioning and development of current logistics systems while maintaining opportunities for future generations to meet their needs. The paper details three key aspects of sustainability for AI and for Logistics 5.0 – environmental sustainability, economic well-being, and social justice. It is concluded that there is a need to develop ethical principles and a legal framework for regulating the use of AI in logistics to ensure their contribution to sustainable development.

Research on the Application of Artificial Intelligence Technology in Electrical Automation Control

Research on the Application of Artificial Intelligence Technology in Electrical Automation Control

ЗАСТОСУВАННЯ ШТУЧНОГО ІНТЕЛЕКТУ У СИСТЕМІ УПРАВЛІННЯ ПІДПРИЄМСТВОМ

The article examines the issue of using artificial intelligence in the enterprise management system. The relevance of the use of artificial intelligence in the enterprise management system is manifested in its ability to transform and optimize key aspects of business. It is emphasized that the application of artificial intelligence technologies has become an integral part of successful business in the modern world. The integration of these technologies into the activities of enterprises helps to ensure competitive advantages and rise to a new level of competitiveness. Therefore, it is important for enterprises to be aware of the possibilities and prospects of integrating artificial intelligence technologies into their business and quickly adapt them to achieve success. As a conclusion, it is said that artificial intelligence is a powerful tool for implementation in business process management systems. This tool automates processes, increases efficiency, reduces costs and improves the quality of decision-making. However, it is important to consider the shortcomings and limitations associated with the availability of quality data and the integration of systems. The use of artificial intelligence requires careful planning and analysis, but can be a key success factor in business process management. In general, artificial intelligence has become an integral part of the modern world and can be successfully used in business process management systems. Its advantages include the ability to analyze large volumes of data, identify complex dependencies, and make objective decisions based on algorithms. Artificial intelligence automates routine management tasks, freeing up human resources for complex tasks that require creative thinking and a strategic approach. One of the successful examples of using AI in business process management is an image recognition system and machine learning for product quality control. This system recognizes product defects with high accuracy and speed, reducing the number of defects and increasing product quality. The use of AI also reduces costs, improves decision-making processes and promotes innovative development.

Are small farms sustainable and technologically smart? Evidence from Poland, Romania, and Lithuania

Abstract Sustainable development of farms is determined by many factors and, in recent years, significance of modern technologies and artificial intelligence (AI) has been pointed out, especially in terms of beneficial effects on economic performance and natural resources. Therefore, there is a need to answer the question about the application of AI technologies in small-scale farms, especially those with a relatively high level of sustainability. In order to obtain the information, a survey in Poland, Romania and Lithuania was carried out. Among the respondents, the 20 most sustainable farms in each country were selected using the CRITIC-TOPSIS method. Next, in-depth interviews were conducted to explore attitudes, behaviour and knowledge of AI.. The results show that small-scale farms in selected countries do not apply artificial intelligence. Although owners recognise and appreciate the benefits of AI, they are not convinced to implement this technology in their own business, they are not completely uncritical about using AI tools in the practice. The main obstacles are: low level of knowledge, misconception of the price of innovation or lack of capital for buying more advanced technology, low interest in implementing innovative solutions due the small scale of production or habituation to traditional production methods.