{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T08:47:46Z","timestamp":1778575666906,"version":"3.51.4"},"reference-count":47,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>This article develops an innovative and intelligent method for analysing the criminal community\u2019s influence on risk-forming parameters based on an analysis of regional economic processes. The research motivation was the need to create an intelligent method for quantitative assessment and risk control arising from the interaction between regional economic processes and criminal activity. The method includes a three-level mathematical model in which the economic activity dynamics are described by a modified logistic equation, taking into account the criminal activity\u2019s negative impact and feedback through the integral risk. The criminal activity itself is modelled by a similar logistic equation, taking into account the economic base. The risk parameter accumulates the direct impact and delayed effects through the memory core. To numerically solve the spatio-temporal optimal control problem, a neural network based on the convolutional architecture was developed: two successive convolutional layers (N1 with 3 \u00d7 3 filters and N2 with 3 \u00d7 3 filters) extract local features, after which two 1 \u00d7 1 convolutional layers (FC1 and FC2) form a three-channel output corresponding to the control actions UE, UC, and UI. The loss function combines the supervised component and the residual terms of the differential equations, which ensures the satisfaction of physical constraints. The computational experiment showed the high accuracy of the model: accuracy is 0.9907, precision is 0.9842, recall is 0.9983, and F1-score is 0.9912, with a minimum residual loss of 0.0093 and superiority over alternative architectures in key metrics (MSE is 0.0124, IoU is 0.74, and Dice is 0.83).<\/jats:p>","DOI":"10.3390\/a18080523","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T15:34:53Z","timestamp":1755531293000},"page":"523","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Intelligent Method for Generating Criminal Community Influence Risk Parameters Using Neural Networks and Regional Economic Analysis"],"prefix":"10.3390","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8009-5254","authenticated-orcid":false,"given":"Serhii","family":"Vladov","sequence":"first","affiliation":[{"name":"Department of Scientific Activity Organization, Kharkiv National University of Internal Affairs, 27, L. Landau Avenue, 61080 Kharkiv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lyubomyr","family":"Chyrun","sequence":"additional","affiliation":[{"name":"Department of Applied Mathematics, Ivan Franko National University of Lviv, 1, University Street, 79000 Lviv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8695-8807","authenticated-orcid":false,"given":"Eduard","family":"Muzychuk","sequence":"additional","affiliation":[{"name":"Research Laboratory on the Problems of Legal Support of Police Activities and Combating Crime, Kharkiv National University of Internal Affairs, 27, L. Landau Avenue, 61080 Kharkiv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6417-3689","authenticated-orcid":false,"given":"Victoria","family":"Vysotska","sequence":"additional","affiliation":[{"name":"Department of Information Systems and Networks, Lviv Polytechnic National University, 12, Bandera Street, 79013 Lviv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9676-0180","authenticated-orcid":false,"given":"Vasyl","family":"Lytvyn","sequence":"additional","affiliation":[{"name":"Department of Information Systems and Networks, Lviv Polytechnic National University, 12, Bandera Street, 79013 Lviv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tetiana","family":"Rekunenko","sequence":"additional","affiliation":[{"name":"Department of Education Quality Assurance, Kharkiv National University of Internal Affairs, 27, L. Landau Avenue, 61080 Kharkiv, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Andriy","family":"Basko","sequence":"additional","affiliation":[{"name":"Department of Postgraduate and Doctoral Studies, Zaporizhzhia National University, 66, University Street, 69063 Zaporizhzhia, Ukraine"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"100056","DOI":"10.1016\/j.jeconc.2024.100056","article-title":"Unravelling the Organisation of Ivorian Cyberfraudsters: Criminal Networks or Organised Crime?","volume":"3","author":"Azi","year":"2024","journal-title":"J. Econ. 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