Research and Implementation of Mobile Internet Management Optimization and Intelligent Information System Based on Smart Decision

The way by which artificial intelligence is implemented is similar to the thinking process of the human brain. People obtain information about external conditions through five senses, namely, vision, hearing, smell, taste, and touch, and, through the further processing of the brain, it forms meaningful decision-making elements. Then, through the process of analysis and reasoning, further decisions are made. In the information age, the application of intelligent management information systems in various fields has promoted the modernization and intelligence of social development. From the perspective of intelligent decision-making, this paper analyzes the requirements of intelligent information systems and designs an intelligent information system based on mobile Internet management optimization, including system management optimization, and proposes an environment-based layer, network transport layer, and the three-tier system architecture of the smart service application layer. Finally, this paper considers the problem of data fusion after system expansion. According to the existing fuzzy fusion algorithm, a weight-based fuzzy fusion algorithm is proposed. The simulation analysis shows that the algorithm can be effectively applied in intelligent information systems.

Methods of formalized quality assessment of intelligent transport systems

The purpose of the paper is to identify the main problems of creating software systems with a given level of reliability for intelligent transport systems. Considering the importance of this approach and the gained experience, the paper discusses design solutions to ensure software reliability in the development process. The paper is based on domestic and foreign experience of software design for intelligent information systems, which include transport systems. The issues of achieving a given level of software reliability during the control process are considered taking into account the continuation of the development process. It also reflects efforts to model and evaluate the reliability of software systems by considering the most common types of software reliability assessment models during development, as well as to predict the reliability during maintenance. The emphasis is upon detecting and correcting software errors.

Knowledge Modeling in Troubleshooting

Introduction. The article describes the approach to solving the problem of complex technical system troubleshooting based on expert knowledge modeling. Intelligent information systems are widely used to solve the problems of diagnostics of multilevel systems including combine harvesters. The formal description of the subject domain knowledge is the framework for building the knowledge base of these systems. The sequence of creating an expert system knowledge base in accordance with production rules is considered. Materials and Methods. The approach is founded on the fault function table. As the object of diagnostics, one of the subsystems of the combine harvester electric equipment “opening the hopper roof flaps” is considered. The basis for constructing a sequence of elementary checks is a system of logical equations describing both the serviceable and possible faulty states of the subsystem. Results. A structural logic model is developed. As a result of analyzing the fault function table, the sets of elementary checks are determined. Four criteria have been used to analyze the weight of these checks. The authors have determined optimal sequence of checks and have developed a decision tree, which allows finding the cause of the malfunction and is the basis for creating the knowledge base of an intelligent information system. A fragment of the knowledge base is given. Discussion and Conclusion. The proposed approach of expert knowledge modelling increases the efficiency of the unit for troubleshooting of the intelligent decision support system. It makes possible to structure the base of expertise and establishing the optimal sequence of elementary checks. This allows determining the optimal sequence of application of the knowledge base production rule that makes it possible to reduce the time of restoring the serviceability of combines.

Information technologies in commerce

The textbook discusses the technologies of the digital economy in commerce: visualization systems, virtual and mixed reality technologies, risk management, budgeting and planning, service-oriented enterprise architecture. The use of intelligent information systems in the work of the enterprise and for forecasting sales, scoring, combating fraud in the banking sector and trade; wireless information networks of 4G and 5G standards, Internet of Things networks, mobile technologies in the work of retail and wholesale enterprises is shown. Meets the requirements of the federal state educational standards of higher education of the latest generation. For students of higher educational institutions studying in the field of training "Trade business".

An Electric Fish-Based Arithmetic Optimization Algorithm for Feature Selection

With the widespread use of intelligent information systems, a massive amount of data with lots of irrelevant, noisy, and redundant features are collected; moreover, many features should be handled. Therefore, introducing an efficient feature selection (FS) approach becomes a challenging aim. In the recent decade, various artificial methods and swarm models inspired by biological and social systems have been proposed to solve different problems, including FS. Thus, in this paper, an innovative approach is proposed based on a hybrid integration between two intelligent algorithms, Electric fish optimization (EFO) and the arithmetic optimization algorithm (AOA), to boost the exploration stage of EFO to process the high dimensional FS problems with a remarkable convergence speed. The proposed EFOAOA is examined with eighteen datasets for different real-life applications. The EFOAOA results are compared with a set of recent state-of-the-art optimizers using a set of statistical metrics and the Friedman test. The comparisons show the positive impact of integrating the AOA operator in the EFO, as the proposed EFOAOA can identify the most important features with high accuracy and efficiency. Compared to the other FS methods whereas, it got the lowest features number and the highest accuracy in 50% and 67% of the datasets, respectively.

The problem of loss of solutions in the task of searching similar documents: Applying terminology in the construction of a corpus vector model

This article considers the problem of finding text documents similar in meaning in the corpus. We investigate a problem arising when developing applied intelligent information systems that is non-detection of a part of solutions by the TF-IDF algorithm: one can lose some document pairs that are similar according to human assessment, but receive a low similarity assessment from the program. A modification of the algorithm, with the replacement of the complete vocabulary with a vocabulary of specific terms is proposed. The addition of thesauri when building a corpus vector model based on a ranking function has not been previously investigated; the use of thesauri has so far been studied only to improve topic models. The purpose of this work is to improve the quality of the solution by minimizing the loss of its significant part and not adding “false similar” pairs of documents. The improvement is provided by the use of a vocabulary of specific terms extracted from the text of the analyzed documents when calculating the TF-IDF values for corpus vector representation. The experiment was carried out on two corpora of structured normative and technical documents united by a subject: state standards related to information technology and to the field of railways. The glossary of specific terms was compiled by automatic analysis of the text of the documents under consideration, and rule-based NER methods were used. It was demonstrated that the calculation of TF-IDF based on the terminology vocabulary gives more relevant results for the problem under study, which confirmed the hypothesis put forward. The proposed method is less dependent on the shortcomings of the text layer (such as recognition errors) than the calculation of the documents’ proximity using the complete vocabulary of the corpus. We determined the factors that can affect the quality of the decision: the way of compiling a terminology vocabulary, the choice of the range of n-grams for the vocabulary, the correctness of the wording of specific terms and the validity of their inclusion in the glossary of the document. The findings can be used to solve applied problems related to the search for documents that are close in meaning, such as semantic search, taking into account the subject area, corporate search in multi-user mode, detection of hidden plagiarism, identification of contradictions in a collection of documents, determination of novelty in documents when building a knowledge base.

THE ROLE OF INTELLIGENT INFORMATION SYSTEMS IN THE MODERN WORLD

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.

Analysis of Metrics for Intelligent Information Systems

The problem of constructing metrics is crucial for solving the problem of quantitative evaluation of both systems of objects of arbitrary nature as a whole and the relationships that describe the connections between the components of these systems. Modern information systems simulate subject areas that contain objects and systems of complex structure. The network model is most appropriate for describing the world around it: it reflects objects and systems of objects of arbitrary nature that interact with each other. In fact, any system can be described using a network model. Hierarchical models should be singled out as a kind of network models of complex systems. Hierarchical models are very widespread and are used in various fields — in biology, sociology, economics, technology, management, etc. — each industry has a set of its own hierarchical models. The paper analyzes metrics suitable for evaluating intelligent information systems, in particular — systems that are based on ontologies, non-relational (hierarchical) databases, non-normalized (nested) relationships.

Development of domain thesaurus as a set of ontology concepts with use of semantic similarity and elements of combinatorial optimization

We consider use of ontological background knowledge in intelligent information systems and analyze directions of their reduction in compliance with specifics of particular user task. Such reduction is aimed at simplification of knowledge processing without loss of significant information. We propose methods of generation of task thesauri based on domain ontology that contain such subset of ontological concepts and relations that can be used in task solving. Combinatorial optimization is used for minimization of task thesaurus. In this approach, semantic similarity estimates are used for determination of concept significance for user task. Some practical examples of optimized thesauri application for semantic retrieval and competence analysis demonstrate efficiency of proposed approach.