articles
| Widespread use of web-based systems in business, marketing, e-learning, etc. makes it necessary to take into account and analyze the information needs of the user in order to optimize interaction with him. One of the main problems of creating adaptive web-based systems is the task of classifying information resources (pages) of the portal describing the offered product or service, for the subsequent formation of the user profile and personalized recommendations of services. Data mining and machine learning methods can be used to solve this problem. The article presents a new approach to creating adaptive web-based information systems using the reinforcement learning algorithms to classify information resources and to form personalized recommendations to users based on their preferences. An adaptive approach is proposed and justified, based on the use of Reinforcement Learning procedures, which allows you to automatically find the most effective strategies for the correct classification of the site's resources and the formation of user groups with the same type of requests and preferences. The proposed scheme allows you to create procedures for evaluating and ranking information resources of the system based on the analysis of user behavior on the site online. The reinforcement learning algorithms used make it possible to evaluate the relevance of each page of the site to the requests and preferences of the users from different categories in order to optimize the structure and content of the site, as well as to build an effective system of recommendations in accordance with the user's interests to be able to choose the most suitable products or services. Continue... | |
| The author of this article represents his own work DVCompute Simulator, which is a collection of general-purpose programming libraries for discrete event simulation. The aim of the research was to create a set of simulators in the Rust language, efficient in terms of speed of execution, based on a unified approach and destined for different simulation modes. The simulators implement such modes as ordinary sequential simulation, nested simulation and distributed simulation. The article describes that nested simulation is related to Theory of Games, while distributed simulation can be used for running large-scale simulation models on supercomputers. It is shown how these different simulation modes can be implemented based on the single approach that combines many paradigms: the event-oriented paradigm, the process-oriented one, blocks similar to the GPSS language and even partially agent-based modeling. The author's approach is based on using the functional programming techniques, where the simulation model is defined as a composition of computations. The results of testing two modules are provided, where the modules support both the optimistic and conservative methods of distributed simulation. Continue... | |
| The relevance of the topic considered in the article lies in solving problematic issues of identifying rare events in imbalance conditions in training sets. The purpose of the study is to analyze the capabilities of a classifier’s ensemble trained on different imbalanced data subsets. The features of the heterogeneous segments state analysis of the Internet of Things network infrastructure based on machine learning methods are considered. The prerequisites for the unbalanced data emergence during the training samples formation are indicated. A solution based on the use of a classifier’s ensemble trained on various training samples with classified events imbalance is proposed. The possibility analysis of using unbalanced training sets for a classifier’s ensemble averaging of errors occurs due to the collective voting procedure, is given. An experiment was carried out using weak classifying algorithms. The estimation of features values distributions in test and training subsets is carried out. The classification results are obtained for the ensemble and each classifier separately. An imbalance is investigated consists in the events number ratios violation a certain type within one class in the training data subsets. The data absence in the training sample leads to an increase in the scatter effect responses is averaged by an increase in the model complexity including various classifying algorithms in its composition. The proposed approach can be applied in information security monitoring systems. A proposed solution feature is the ability to scale and combine it by adding new classifying algorithms. In the future, it is possible to make changes during operation to the classification algorithms composition, it makes possible to increase the indicators of the identifying accuracy of a potential destructive effect. Continue... | |
| In this paper, we evaluate the crypto resistance of known cryptographic methods and methods based on the use of noise-like signals, similar in properties to "limited" white noise and used to spread spectrum of transmitted messages, to the destructive effect of "viewing transmitted data" (decipher), based on the search of code structures (brute force), in the case of quantum computers. It’s established that the required value of the number of code structures (key space), taking into account the constantly improving and developing computing power of quantum computers, for the next few years should be considered a value of 1032 of the number of code structures (key space) and higher, providing crypto resistance for a minimum of 3 years. It’s shown that the Grover algorithm is similar to the destructive effect of "viewing transmitted data" (decipher), based on a complete search of all code structures (brute force) using modern super- computers. It’s established that well-known symmetric cryptographic methods can potentially be used in the post-quantum era and methods based on noise-like signals potentially, provided they are detected and aware of the methods underlying them (without knowledge of the key), cannot be applied in the post-quantum era. According to the authors, a promising approach in the post-quantum era for information security issues is the use of chaotic signals. Continue... | |
| This article considers the urgent scientific and practical task of developing analytical tools to justify the choice and transformation of a business model for an economic organization in a rapidly changing business environment. The mathematical apparatus of cognitive modelling is proposed to use to solve this problem, which makes it possible, based on the analysis of cause- effect relationships between the most significant conditions and factors affecting the economic efficiency and competitiveness of doing business, to improve the reasonableness and reduce the subjectivity of the decisions made by its owners and top managers. An algorithm to justify the choice of a business model for an organization based on the construction and analysis of fuzzy cognitive maps (FCM) of business models is proposed. A common list of business factors (concepts) and a set of causality relations between each pair of concepts has been defined, and a basic FCM of the business model is developed as the basis for constructing FCM models of specific businesses. An example of the application of the developed toolkit in a strategic analysis of the conditions and factors of an organization undertaking the production of furniture, carried out to justify a change in competitive strategy and the associated transformation of the business model, is considered. The analysis has been performed using specialized cognitive modelling software developed at the department of information technologies in economics and management, branch of the National Research University Moscow Power Engineering Institute in Smolensk. The proposed toolkit improves methods and algorithms for intelligent decision-making support in the management of economic and social objects and can find practical application in the strategic management of commercial organizations in various fields, as well as be used by professional consultants in the preparation of recommendations for business model change. Continue... | |
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№ 4(94)
31 august 2021 year
Rubric: Performance management Authors: Chernovalova M., Kakatunova T., Vlasova E., Volkova I. |
The effectiveness of design solutions largely depends on the promptness of processing a large amount of data from various sources, which determines the feasibility of using information decision support systems (IDSS) in the field of project management. The peculiarities of information processes in project management greatly complicate or even make it impossible to implement in practice methods for constructing analytical, as well as probabilistic and statistical dependencies between the characteristics of the modeled project management system and the indicators of its internal and external environment. In this regard, as an algorithmic support for IDSS for project management, it is promising to use precedent methods for analyzing information based on knowledge about similar situations previously observed in the practice of project management, and representing knowledge in the form of ontologies. Analysis of practical situations in the field of project management makes it possible to substantiate the expediency of organizing a monitoring procedure for the IDSS knowledge base, based on the results of which decisions on its adaptation are made. The article proposes the main ways of this adaptation: changing the structure and basic elements (first of all, concepts) of ontologies; clarification of the structure of the description of current situations and, therefore, precedents. The developed algorithm for monitoring the IDSS knowledge base on project management for the analysis and identification of typical situations of the feasibility of changing it is described. The algorithm is distinguished by the possibility of developing recommendations on the modification of ontologies based on a fuzzy classification of search results and using precedents relevant to current situations. A procedure is proposed for changing the structure of the description of precedents, taking into account the results of assessing the indices of the fuzzy correspondence of the characteristics of the existing precedents to the characteristics of the project being implemented. A description of a computer program that implements the proposed algorithm and its components, as well as the results of its application are given. Continue... |
