Method for Automatic Analysis of Compliance of Settlements with Suppliers and Settlements with Customers by Neural Network Model of Forecast

Neskorodieva, Tatiana; Fedorov, Eugene

doi:10.1007/978-3-030-58124-4_15

Cited by 4 publications

(4 citation statements)

References 10 publications

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“…Today, scientists in all fields of activity pay considerable attention to artificial neural networks to perform forecasting processes [12,13,14,15]. At the same time, the development of tools for forecasting involves the implementation of processes of accumulation of information about the state of the system, analysis, and identification of patterns and trends in the forecast indicators [16].…”

Section: Analysis Of Published Data and Problem Settingmentioning

confidence: 99%

Improving the Efficiency of Search and Identification Projects of Missing People in Extraordinary Situations With Application It Technology

Rudynets,

Androshchuk

2023

NVDNTU

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Purpose. The purpose of the work is to analyze the existing projects of search and identification of missing people in emergency situations with the use of IT technologies and to establish ways of improving the effectiveness of the population protection system in emergency situations. Methodology. Special research methods were used to conduct the study: methods of collecting and summarizing information, critical analysis with elements of forecasting. Results. Information has been collected and summarized to improve the efficiency and effectiveness of projects aimed at finding victims in emergency situations, which helps facilitate communication, data collection, analysis and distribution of resources in order to provide them with timely qualified assistance. The effectiveness of the work of various services and organizations and the factors that depend on the time of searching for injured and missing people in emergencies and, accordingly, the ability to provide them with assistance in time, have been analyzed. The system of providing timely assistance in emergency situations is generalized, consisting of separate stages, each of which can act as a separate stage of one project or as a separate project. The study shows that the existing projects on the search and identification of missing people using IT technologies in Ukraine face a number of challenges and shortcomings that may limit their effectiveness. This assessment of the possibilities of existing projects aimed at finding victims of natural disasters implemented in Ukraine and establishing the ways to improve their effectiveness. High-tech solutions and innovative technologies have been characterized. The methods of identification of an undocumented person using IT technologies, identification of a person, which is the ultimate goal of the search, have also been analyzed. A SWOT analysis has been conducted, which showed that projects aimed at searching for victims of natural disasters with the use of IT technologies have a number of strengths and opportunities. Scientific novelty. The application of artificial intelligence (AI) with the use of machine learning and neural network technologies for forecasting the required time of work and resources in hybrid projects has been shown. Practical significance. Promising ways to increase the effectiveness of these projects are the creation of a single online platform for combining the efforts of coordinating actions between all project participants, performing database integration, expanding the surveillance network in cities and settlements, applying artificial intelligence (AI) and data analytics, applying telemedicine and medical records, integration with international databases.

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Section: Analysis Of Published Data and Problem Settingmentioning

confidence: 99%

Improving the Efficiency of Search and Identification Projects of Missing People in Extraordinary Situations With Application It Technology

Rudynets,

Androshchuk

2023

NVDNTU

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“…The analytical procedures used in the audit are currently based on data mining techniques [1,2]. In an automated audit system, the task of auditing expenses at the top level is decomposed into tasks of checking the sequence of displaying data of the middle level.…”

Section: Introductionmentioning

confidence: 99%

Method of Spectral Clustering of Payments and Raw Materials Supply for the Compliance Audit Planning

Neskorodieva

Fedorov

2021

RIC

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Context. The analytical procedures used in the audit are currently based on data mining techniques. The work solves the problem of increasing the efficiency and effectiveness of analytical audit procedures by clustering based on spectral decomposition. The object of the research is the process of auditing the compliance of payment and supply sequences for raw materials. Objective. The aim of the work is to increase the effectiveness and efficiency of the audit due to the method of spectral clustering of sequences of payment and supply of raw materials while automating procedures for checking their compliance. Method. The vectors of features are generated for the objects of the sequences of payment and supply of raw materials, which are then used in the proposed method. The created method improves the traditional spectral clustering method by automatically determining the number of clusters based on the explained and sample variance rule; automatic determination of the scale parameter based on local scaling (the rule of K-nearest neighbors is used); resistance to noise and random outliers by replacing the k-means method with a modified PAM method, i.e. replacing centroid clustering with medoid clustering. As in the traditional approach, the data can be sparse, and the clusters can have different shapes and sizes. The characteristics of evaluating the quality of spectral clustering are selected. Results. The proposed spectral clustering method was implemented in the MATLAB package. The results obtained made it possible to study the dependence of the parameter values on the quality of clustering. Conclusions. The experiments carried out have confirmed the efficiency of the proposed method and allow us to recommend it for practical use in solving audit problems. Prospects for further research may lie in the creation of intelligent parallel and distributed computer systems for general and special purposes, which use the proposed method for segmentation, machine learning and pattern recognition tasks.

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“…2022. № 2 (6) 65 слід використовувати точний інструментарій. На сьогодні використання нейронних мереж для вирішення задач планування у різних прикладних галузях набуває усе більшого поширення.…”

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“…Аналіз останніх досліджень і публікацій. Реалізацію процесів управління змістом та часом виконання робіт у проєктах регламентує низка міжнародних методологій, зокрема PMBOK, ІSО 21500, СРМ, CCPM [6,7,8,9]. Науковцями усього світу багато уваги приділено удосконаленню класичних міжнародних методологій управління змістом та часом виконання робіт у проєктах [10].…”

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Planning the Time of Performance of Works in Hybrid Projects

Tryhuba¹,

Kondysiuk²,

Koval³

et al. 2022

SM3P

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The aim of the work is to substantiate the approach to forecasting the time fund for work in hybrid projects, taking into account the changing nature and climatic components of the design environment based on the use of neural networks. The neural network architecture involves the use of a multilayer perceptron, teacher training, and the method of backpropagation. It is based on an algorithm that minimizes the prediction error by propagating error signals from the network outputs (predicted duration of naturally allowed forecasting the working time fund) to its inputs (values of the duration of naturally allowed forecasting the working time fund in previous days), in the direction opposite to the direct propagation of signals. Based on the prepared initial data, the training of an artificial neural network was performed, which ensured the creation of an artificial neural network that is able to predict the duration of naturally allowed time to perform work in a software environment written in Python. Studies based on neural network training show that when the number of epochs increases to more than 25,000, the error does not exceed 4.8%. To study the neural network, we used the statistical data of the summer months of 2020 on the naturally allowed forecasting the working time fund during certain days, which are typical for the conditions of the Volodymyr-Volynskyi district of the Volyn region. The obtained results indicate that the use of the proposed architecture of the artificial neural network gives a fairly accurate forecast and this is the basis for making quality management decisions on planning the content and timing of work in hybrid projects.

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Method for Automatic Analysis of Compliance of Settlements with Suppliers and Settlements with Customers by Neural Network Model of Forecast

Cited by 4 publications

References 10 publications

Improving the Efficiency of Search and Identification Projects of Missing People in Extraordinary Situations With Application It Technology

Improving the Efficiency of Search and Identification Projects of Missing People in Extraordinary Situations With Application It Technology

Method of Spectral Clustering of Payments and Raw Materials Supply for the Compliance Audit Planning

Planning the Time of Performance of Works in Hybrid Projects

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