scholarly journals THE ROLE OF INTELLIGENT INFORMATION SYSTEMS IN THE MODERN WORLD

2021 ◽  
Author(s):  
И.Р. Усамов ◽  
А.А. Албакова ◽  
А.А. Мустиев
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Intelligent Systems ◽  
Quality Of Services ◽  
Modern World ◽  
Intelligent Information Systems ◽  
Intelligent Information ◽  
The Moment

Статья посвящена рассмотрению роли интеллектуальных информационных систем в современном мире. Проведен анализ и рассмотрена сущность интеллектуальных систем, отрасли использования интеллектуальных систем, выделены проблемы внедрения интеллектуальных информационных систем и предложены механизмы решения проблем внедрения интеллектуальных информационных систем. Рассмотрены основные отрасли, где используются интеллектуальные информационные системы для повышения скорости производства и улучшения качества оказываемых услуг. Рассмотрены основные три проблемы искусственного интеллекта, которые не решены на данный момент, и которые в будущем могут вызвать мировой хаос. Предложены механизмы решения данных трех проблем. The article is devoted to the role of intelligent information systems in the modern world. The article analyzes and considers the essence of intelligent systems, the branches of using intelligent systems, identifies the problems of implementing intelligent information systems, and suggests mechanisms for solving the problems of implementing intelligent information systems. The main industries where intelligent information systems are used to increase the speed of production and improve the quality of services provided are considered. The main three problems of artificial intelligence, which are not solved at the moment, and which in the future can cause global chaos, are considered. Mechanisms for solving the set here problems areproposed.

The Central Role of Cognitive Computations in Human-Information Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Jessie Chin ◽  
Q. Vera Liao
Keyword(s):  
Information Systems ◽  
Cognitive Science ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Levels Of Abstraction ◽  
Intelligent Information Systems ◽  
Emergent Behaviour ◽  
Information Interaction ◽  
Intelligent Information

Cognitive science is a science of intelligent systems. This chapter proposes that cognitive science can provide useful perspectives for research on technology-mediated human-information interaction (HII) when HII is cast as emergent behaviour of a coupled intelligent system. It starts with a review of a few foundational concepts related to cognitive computations and how they can be applied to understand the nature of HII. It discusses several important properties of a coupled cognitive system and their implication to designs of information systems. Finally, it covers how levels of abstraction have been useful for cognitive science, and how these levels can inform design of intelligent information systems that are more compatible with human cognitive computations.

Intelligent information systems and artificial intelligence methods

2021 ◽  
Author(s):  
Aleksandr Andreychikov ◽  
Ol'ga Andreychikova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Information Science ◽  
Federal State ◽  
Construction Technology ◽  
Intelligent Information Systems ◽  
Engineering And Technology ◽  
Subject Areas ◽  
Intelligent Information ◽  
State Educational

The textbook discusses the methods of artificial intelligence and their application to solve problems from various subject areas. Methods of acquisition, representation and processing of knowledge in intelligent systems, as well as technologies for designing and implementing intelligent systems, are described. Special attention is paid to the application of intelligent systems for the selection of collective solutions, the design of complex systems( objects), the analysis and forecasting of the enterprise. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students enrolled in groups of training master's degree program "Management in technical systems", "Computer and information science", "computer science", "engineering and technology land transport", "engineering and construction technology", "Photonics, instrumentation, optical and biotechnical systems and technology", "aerospace engineering", "engineering and technologies of shipbuilding and water transport", and also in the areas of "automation of technological processes and productions", "mechatronics and robotics".

Models and intelligent systems

2020 ◽  
Author(s):  
Boris Odincov
Keyword(s):  
Information Systems ◽  
Intelligent Systems ◽  
Business Processes ◽  
Academic Disciplines ◽  
Intended Meaning ◽  
Intelligent Information Systems ◽  
New Concepts ◽  
Business Efficiency ◽  
Intelligent Information ◽  
Theoretical Foundations

The monograph consists of three chapters, the first of which outlines the theoretical foundations of intelligent information systems. Special attention is paid to the disclosure of the term "model" as the intended meaning depends on the understanding of the material. Introduces and examines the new concepts such as the associative and intuitive knowledge while in the creation of intellectual information systems are not used. The second Chapter contains the analysis of problems of development of artificial intelligence (AI), developed in two directions: classical and statistical. Discusses difficulties in the development of the classical approach, associated with identifying the meaning of words, phrases, text, and formulating thoughts. The analysis of problems arising in the play of imagination and insight, machine understanding of natural language texts, play, verbalization and reflection. The third Chapter contains examples of the development of intelligent information systems and technologies in practice of management of economic objects. Theoretical bases of construction of information robots designed to support the task hierarchy of the knowledge base and generating control regulations. The technology of their creation and application in the management of the business efficiency of enterprise business processes and its investment activities. Focused on researchers and developers, AI and intelligent information systems, as well as graduate students and faculty in related academic disciplines.

scholarly journals Assessment of risks and threats to the development of artificial intelligence technologies

2021 ◽  
Vol 311 ◽  
pp. 06004
Author(s):  
Elena Shevchenko ◽  
Angelika Efremova ◽  
Dmitriy Titarenko ◽  
Aleksey Voloshin ◽  
Inga Artyukhova
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Human Activity ◽  
Intelligent Information Systems ◽  
Negative Results ◽  
Intelligent Information

The paper analyses the risks and threats caused by the development and implementation of artificial intelligence technologies. We believe that these risks and threats need research in the long term. Importantly, the use of intelligent information systems has a twofold effect: it can lead to both positive and negative results. The paper also considers the influence of artificial intelligence technologies on the various activities. It proposes a classification of risks and threats caused by the development and implementation of artificial intelligence technologies by the main spheres of human activity.

Conceptualizing the Use of Artificial Intelligence in Customer Relationship Management and Quality of Services

2022 ◽  
pp. 177-201
Author(s):  
Parag Shukla ◽  
Sofia Devi Shamurailatpam
Keyword(s):  
Artificial Intelligence ◽  
Customer Relationship Management ◽  
Relationship Management ◽  
Operational Efficiency ◽  
Customer Relationship ◽  
Quality Of Services ◽  
Comprehensive Model ◽  
Indian Banks

In this chapter, the authors have conceptualized a hypothetical comprehensive model of AI, CRM, and quality of services by banks given the underlying pull and push factors that determine the extent of AI adoption by the banks. This chapter shall also serve as a primer to demonstrate the effects of use of artificial intelligence in the Indian banks and is also aimed to encapsulate the restraining and facilitating forces that drive adoption of AI. This chapter examines the blooming development of artificial intelligence and its significance in the operational efficiency in terms of management of issues related to customers while accessing different products and services offered by banks. In other words, the use of artificial intelligence technologies can dramatically improve banks' ability to achieve four key outcomes: higher profits, at-scale personalization, rapid innovation cycles, strategic customer relationship management (CRM), and distinctive omni-channel experiences. The role of artificial intelligence (AI) is significant in the banking industry for operational efficiency.

scholarly journals Self-Organization and Adaptation in Intelligent Systems

1998 ◽  
Vol 2 (6) ◽  
pp. 177-177
Author(s):  
Nikola Kasabov ◽  
◽  
Robert Kozma ◽  
Keyword(s):  
Neural Networks ◽  
Information Systems ◽  
Intelligent Systems ◽  
Adaptive Systems ◽  
Hebbian Learning ◽  
Intelligent System ◽  
Self Organizing Maps ◽  
Intelligent Information Systems ◽  
Intelligent Information ◽  
Self Organizing

This special issue is devoted to one of the important topics of current intelligent information systems-their ability to adapt to the environment they operate in, as adaptation is one of the most important features of intelligence. Several milestones in the literature on adaptive systems mark the development in this area. The Hebbian learning rule,1) self-organizing maps,2,3) and adaptive resonance theory4) have influenced the research in this area a great deal. Some current development suggests methods for building adaptive neurofuzzy systems,5) and adaptive self-organizing systems based on principles from biological brains.6) The papers in this issue are organized as follows: The first two papers present material on organization and adaptation in the human brain. The third paper, by Kasabov, presents a novel approach to building open structured adaptive systems for on-line adaptation called evolving connectionist systems. The fourth paper by Kawahara and Saito suggests a method for building virtually connected adaptive cell structures. Papers 5 and 6 discuss the use of genetic algorithms and evolutionary computation for optimizing and adapting the structure of an intelligent system. The last two papers suggest methods for adaptive learning of a sequence of data in a feed-forward neural network that has a fixed structure. References: 1) D.O. Hebb, "The Organization of Behavior," Jwiley, New York, (1949). 2) T. Kohonen, "Self-organisation and associative memory," Springer-Verlag, Berlin, (1988). 3) T. Kohonen, "Self-Organizing Maps, second edition," Springer Verlag, (1997). 4) G. Carpenter and S. Grossberg, "Pattern recognition by self-organizing neural networks," The MIT Press, Cambridge, Massachusetts, (1991). 5) N. Kasabov, "Foundations of Neural Networks, Fuzzy Systems and Knowledge Engineering," The MIT Press, CA, MA, (1996). 6) S. Amari and N. Kasabov "Brain-like Computing and Intelligent Information Systems," Springer Verlag, Singapore, (1997).

scholarly journals ПРО ПРИРОДНИЙ ТА ШТУЧНИЙ ІНТЕЛЕКТ КІБЕРНЕТИЧНИХ СИСТЕМ

2019 ◽  
pp. 4-18
Author(s):  
Серій Ілліч Доценко
Keyword(s):  
Artificial Intelligence ◽  
Information Systems ◽  
Brain Activity ◽  
Artificial Intelligence System ◽  
Functional Systems ◽  
Intelligence System ◽  
Intelligent Information Systems ◽  
Cybernetic System ◽  
Intelligent Information ◽  
Quantitative Definition

It is proposed as part of the concept of the “cybernetic system” to distinguish the following components: - cybernetic systems impervious to information, as a control system; - cybernetic systems permeable to information: intelligent functional systems based on natural intelligence; Intelligent information systems based on artificial intelligence. From an analysis of the content of the concept of “artificial intelligence,” it follows that at present there is no unambiguous definition of the content of this concept. Almost all authors agree that artificial intelligence should be similar to human intelligence. From an analysis of the content of the concept of “natural intelligence,” it follows that its basis is the central regularity of the integrative activity of the brain. It is proposed to define thinking as the possibility of representing things in measure, and intelligence as the ability to implement the process of measuring things. The measure is the presentation of a thing in the form of a dialectical unity of concepts general (qualitative definition) – single (quantitative definition). It is shown that the main problem that has not been solved so far for artificial neural networks is the problem of the formation of a capable mathematical model of a natural neuron based on the central regularity of integrative brain activity. The second problem requiring its solution is the need to teach the artificial intelligence system to "measure" things, as well as their properties. Without mastering this ability, no artificial intelligence system can implement the actions that characterize the activity of the natural neural network. The third problem is the need to train the artificial intelligence system to remember the previous experience. Manipulating knowledge is possible only by applying the laws of natural intelligence. Therefore, to form the knowledge base, experts are involved as a source of knowledge and knowledge engineers, as specialists in the extraction of knowledge from experts. Moreover, between the concepts of “data” and “information”, as well as “information” and “knowledge”, there is a dialectical connection in the form of “single” – “general”. Intelligent information technology can be the basis for the implementation of cybernetic systems permeable to information: intelligent functional systems; intelligent information systems. The fundamental task that needs to be solved is the task of establishing the composition and content of the concept of “unit of knowledge”.

scholarly journals Does Emotional Intelligence Contribute to Quality of Strategic Decisions? The Mediating Role of Open Innovation

2021 ◽  
Vol 7 (2) ◽  
pp. 130
Author(s):  
Haitham M. Alzoubi ◽  
Ramsha Aziz
Keyword(s):  
Decision Making ◽  
Emotional Intelligence ◽  
Open Innovation ◽  
Strategic Decisions ◽  
Mediating Role ◽  
Intelligent Information Systems ◽  
Top Managers ◽  
Intelligent Information

Purpose—The purpose of this research is to explore the direct relationship between the emotional intelligence of top management and the quality of strategic decisions they take for their companies. This relationship is further examined by the mediating role of open innovation in the context of intelligent information systems that can impact the way top managers take decisions. This research adopted a survey design as cross-sectional data were taken through questionnaires from top management of the UAE national banks. A final sample size of 213 questionnaires completed by managers was obtained and analyzed. As predicted, there was a strong, positive relationship between managers’ emotional intelligence and the quality of their strategic decisions. Open innovation has revolutionized the way top managers of banks take decisions that are later transformed into policies. Decision-makers are required to possess the skill of decision-making by being vigilant of their surroundings. Hence, they have emotional intelligence and intelligent information systems (IIS) only enhances the trait. IIS is the glorified version of open innovation that further contributes to the decision-making process and the quality of decisions. This research is one of a kind as no one has explored these dimensions of emotional intelligence in the UAE.

scholarly journals A conceptual approach to assessing the cluster potential of regions based on the use of intelligent information systems

2021 ◽  
Vol 19 (4) ◽  
pp. 693-717
Author(s):  
Irina R. RUIGA ◽  
Evgeniya S. KOVZUNOVA
Keyword(s):  
Information Systems ◽  
Policy Development ◽  
Federal District ◽  
Expert Assessment ◽  
Cluster Policy ◽  
Conceptual Approach ◽  
Intelligent Information Systems ◽  
Intelligent Information

Subject. This article discusses the role of intelligent information systems in assessing the cluster potential of regions. Objectives. The article aims to develop methodological tools to assess the cluster potential of regions applying intelligent information systems, and test them using the Siberian Federal District regions as a case study. Methods. For the study, we used econometric and expert assessment methods. Results. The article proposes a stepwise algorithm for assessing the cluster potential of regions, taking into account the appropriate methodological and mathematical apparatus. It presents a cumulative indicator of the development potential of cluster groups. Conclusions. The proposed methodological, and information and analysis tools can serve as a basis for decision-making on cluster policy development at the regional level.

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