Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks

Vladimir Lamehov; Evgeny Korovyakovskiy

doi:10.20295/2223-9987-2022-3-137-150

UDC

656.222.6

DESIGN ALGORITHM FOR FORECASTING MODEL OF TRANSPORT-LOGISTIC ACTIVITY ON THE BASIS OF NEURO-FUZZY NETWORKS Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks

АА Аа

Published in Bulletin of scientific research results · Pages 137–150 · Rubric: HIGH TECHNOLOGIES FOR TRANSPORT

DOI: https://doi.org/10.20295/2223-9987-2022-3-137-150

Received: 22.09.2022 Accepted: 22.09.2022 Published: 22.09.2022

Authors

Vladimir Lamehov

Evgeny Korovyakovskiy

Vladimir Lamehov

Emperor Alexander I St. Petersburg State Transport University Russian Federation

Evgeny Korovyakovskiy

Academic degree: candidate of technical sciences

Science rang: professor

Emperor Alexander I Petersburg State Transport University Russian Federation

ABSTRACT

Purpose: To consider the current situation in container transportation market of Leningrad Region. To show the need in the design of new forecasting models. To justify the use of neural fuzzy networks. To consider existing limitations of their application. To suggest the ways to build predictive neural fuzzy models for evaluating promising quantitative indicators of logistics activities. Methods: ANFIS, R-ANFIS, Fuzzy-Partitions, SCRG, GD, LSE, PSO, ABC, FA. Results: The necessity of adaptation of neural fuzzy networks for making forecasts in the field of logistics is pointed on, the structure of a promising model is proposed which takes into account the use and analysis of variety of methods on structural and parametric identification. The shortcomings of particular methods of structural and parametric identification, which affect the accuracy of being obtained forecasts, are indicated. Practical importance: The importance of design of accurate predictive models for key quantitative indicators of logistics activities is shown. The factors influencing the implementation of transport and logistics activities are given which of, reliable forecast is impossible in the situation of limited time and resources. For consideration, the article proposes the existing methods of parametric and structural identification of fuzzy neural networks. An algorithm for adapting existing methods to the use in a transport and logistics process is proposed.

KEYWORDS

Fuzzy neural networks, hybrid neural networks, parametric and structural identification methods, learning methods, container terminal, logistics, forecasting

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GOST

Lamehov V. A., Korovyakovskiy E. K. Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks // . 2022. pp. 137-150. DOI: https://doi.org/10.20295/2223-9987-2022-3-137-150. (Date of access 20.08.2026).

MLA

Vladimir Lamehov, Korovyakovskiy E. K.. "Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks." (2022): 137-150. DOI: https://doi.org/10.20295/2223-9987-2022-3-137-150.

APA

Lamehov V. A., Korovyakovskiy E. K. (2022). Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks. , 137-150. https://doi.org/10.20295/2223-9987-2022-3-137-150

Chicago

Vladimir Lamehov, Korovyakovskiy E. K.. "Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks." , no. (2022): 137-150. https://doi.org/10.20295/2223-9987-2022-3-137-150.

WIKI

{{cite journal | author = Lamehov V. A., Korovyakovskiy E. K. | title = Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks | journal = | year = 2022 | pages = 137-150 | doi = 10.20295/2223-9987-2022-3-137-150 }}

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DESIGN ALGORITHM FOR FORECASTING MODEL OF TRANSPORT-LOGISTIC ACTIVITY ON THE BASIS OF NEURO-FUZZY NETWORKS Design Algorithm for Forecasting Model of Transport-Logistic Activity on the Basis of Neuro-Fuzzy Networks

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