Design of a Dynamic Expert System for Analyzing the Impact of Climate Effects on Small and Medium Sized Enterprises
Main Article Content
Abstract
Growing climate instability is creating new challenges and risks for the resilience of small and medium-sized enterprises (SMEs). This article proposes a prototype architecture for a dynamic expert system comprising several key modules: a user interface, a knowledge base, a server application, and a dynamic data update module with real-time APIs. A distinctive feature of the system is the application of Z⁺-number calculus, implemented using the scikit-fuzzy library, which allows for accounting of graded confidence in evaluations. This approach provides more robust and adaptive risk assessments that are sensitive to changes in the quality of input data. Interactive visualization of the results is built upon OpenStreetMap. The system's methodology for self-adaptation of confidence measures based on historical data is described.
Article Details
References
2. Aliev R.A., Alizadeh A.V., Huseynov O.H. The arithmetic of discrete Z-numbers // Information Sciences. 2015. Vol. 290. P. 134–155.
3. Zeinalova L.M. Choquet aggregation based decision making under Z-information // ICTACT Journal on Soft Computing. 2014. Vol. 4, № 4. P. 819–824.
4. Burnashev R.A., Sergeev Y.V., Nazipova A.F. Metody granulyatsii nechetkikh vremennykh ryadov dlya analiza dannykh // Ontologiya proektirovaniya. 2025. T. 15, No. 3(57). P. 404-417. https://doi.org/10.18287/2223-9537-2025-15-3-404-417.
5. Enikeeva A.I., Burnashev R.A., Farahov R.R. Development of an Expert System Based on Fuzzy Logic for Pneumonia Diagnostics // Automatic Documentation and Mathematical Linguistics. 2024. Vol. 58, No. S4. P. S202–S215. https://doi.org/10.3103/S000510552470027X.
6. Enikeev A.I., Burnashev R.A., Vakhitov G.Z. Software tools and techniques for the expert systems building // Advances in Intelligent Systems and Computing. 2020. Vol. 1041. P. 191-199. https://doi.org/10.1007/978-981-15-0637-6_16
7. Poleshchuk O.M., Poyarkov N.G., Tumor S.V. Prinyatiye resheniy na osnove bayesovskogo podkhoda i Z-chisel // Lesnoy vestnik. 2019. T. 23, No. 4. S. 112–116. https://doi.org/10.18698/2542-1468-2019-4-112-116.
8. Poleshchuk O.M., Chernova T.V. Z - chisla i ikh novyye vozmozhnosti dlya modelirovaniya real'nogo mira // Sovremennyye problemy fiziko-matematicheskogo obrazovaniya: sbornik materialov VI Mezhdunarodnoy zaochnoy nauchno-prakticheskoy konferentsii, Orekhovo-Zuyevo, 12–13 dekabrya 2016 goda / Gosudarstvennyy gumanitarno-tekhnologicheskiy universitet. Orekhovo-Zuyevo: Gosudarstvennyy gumanitarno-tekhnologicheskiy universitet, 2016. P. 33–35.
9. Kostikova A.V., Tereliansky P.V., Shuvaev A.V. [i dr.] Expert Fuzzy Modeling of Dynamic Properties of Complex Systems // ARPN Journal of Engineering and Applied Sciences. 2016. Vol. 11, No. 17. P. 10601–10608.
10. Mozgachev A.V., Rybina G.V., Shantser D.I., Blokhin Y.M. Dinamicheskiye intellektual'nyye sistemy na osnove integrirovannykh ekspertnykh sistem // Pribory i sistemy. Upravleniye, kontrol', diagnostika. 2012. No. 5. S. 13–20.
11. Titov N.A., Makrushin S.V. Tekhnologiya sozdaniya domennoy bazy znaniy vopros-otvetnoy sistemy na osnove krupnomasshtabnoy universal'noy bazy znaniy // Computational Nanotechnology. 2022. V. 9, № 1. P. 115–124. https://doi.org/10.33693/2313-223X-2022-9-1-115-124.
12. Davydenko I.T. Semantic models, method and tools of knowledge bases coordinated development based on reusable components // Otkrytyye semanticheskiye tekhnologii proektirovaniya intellektual'nykh sistem. 2018. No. 8. P. 99–119.
13. Bochkarev A.M. Effektivnost' ispol'zovaniya informatsionnykh platform razrabotki klient-servernykh prilozheniy dlya informatsionnykh sistem promyshlennykh predpriyatiy // Finansovyy biznes. 2021. № 4(214). P. 17–19.
14. Grinyuk D.A., Sukhorukova I.G., Oliferovich N.M. Ispol'zovaniye algoritmov approksimatsii dlya sglazhivaniya trendov izmeritel'nykh preobrazovateley // Trudy BGТU. Seriya 3: Fiziko-matematicheskiye nauki i informatika. 2017. № 2(200). P. 82–87.
15. Bi L., Cao W., Hu W., Wu M. A Dynamic-Attention-Based Heuristic Fuzzy Expert System for the Tuning of Microwave Cavity Filters // IEEE Transactions on Fuzzy Systems. 2022. Vol. 30, No. 9. P. 3695–3707. https://doi.org/10.1109/tfuzz.2021.3124643.
16. Livio J., Hodhod R. AI Cupper: A Fuzzy Expert System for Sensorial Evaluation of Coffee Bean Attributes to Derive Quality Scoring. IEEE Transactions on Fuzzy Systems.2018. Vol. 26 (6). P. 3418–3427. https://doi.org/10.1109/TFUZZ.2018.2832611.
17. Samanta S., Pratama M., Sundaram S. Bayesian Neuro-Fuzzy Inference System for Temporal Dependence Estimation. IEEE Transactions on Fuzzy Systems. 2021. Vol. 29 (9). P. 2479–2490. https://doi.org/10.1109/TFUZZ.2020.3001667.
18. Giiven M.K., Passino K.M. Avoiding exponential parameter growth in fuzzy systems. IEEE Transactions on Fuzzy Systems. 2001. Vol. 9 (1). P. 194–199 https://doi.org/10.1109/91.917125.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Presenting an article for publication in the Russian Digital Libraries Journal (RDLJ), the authors automatically give consent to grant a limited license to use the materials of the Kazan (Volga) Federal University (KFU) (of course, only if the article is accepted for publication). This means that KFU has the right to publish an article in the next issue of the journal (on the website or in printed form), as well as to reprint this article in the archives of RDLJ CDs or to include in a particular information system or database, produced by KFU.
All copyrighted materials are placed in RDLJ with the consent of the authors. In the event that any of the authors have objected to its publication of materials on this site, the material can be removed, subject to notification to the Editor in writing.
Documents published in RDLJ are protected by copyright and all rights are reserved by the authors. Authors independently monitor compliance with their rights to reproduce or translate their papers published in the journal. If the material is published in RDLJ, reprinted with permission by another publisher or translated into another language, a reference to the original publication.
By submitting an article for publication in RDLJ, authors should take into account that the publication on the Internet, on the one hand, provide unique opportunities for access to their content, but on the other hand, are a new form of information exchange in the global information society where authors and publishers is not always provided with protection against unauthorized copying or other use of materials protected by copyright.
RDLJ is copyrighted. When using materials from the log must indicate the URL: index.phtml page = elbib / rus / journal?. Any change, addition or editing of the author's text are not allowed. Copying individual fragments of articles from the journal is allowed for distribute, remix, adapt, and build upon article, even commercially, as long as they credit that article for the original creation.
Request for the right to reproduce or use any of the materials published in RDLJ should be addressed to the Editor-in-Chief A.M. Elizarov at the following address: amelizarov@gmail.com.
The publishers of RDLJ is not responsible for the view, set out in the published opinion articles.
We suggest the authors of articles downloaded from this page, sign it and send it to the journal publisher's address by e-mail scan copyright agreements on the transfer of non-exclusive rights to use the work.