Multi-criteria decision-making for sound and vibration reduction platforms for financial and marketing optimization in energy

  • Alexey Mikhaylov orcid

    Financial Department, Financial University under the Government of the Russian Federation, Moscow 125993, Russia; Department of Informatics, Plekhanov Russian University of Economics, Moscow 117997, Russia; Department of Science, Baku Eurasian University, Baku AZ 1073, Azerbaijan
  • Murat Ikramov

    Department of Marketing, Tashkent State Economic University, Tashkent 100003, Uzbekistan
  • Nilufar Nabiyeva

    Department of International Tourism and Economics, Kokand University, Kokand 150700, Uzbekistan
  • Boris Sokolov

    Department of Credit Theory and Financial Management, Faculty of Economics, Saint Petersburg State University, Saint Petersburg 199034,Russia
  • Wenyi Zhang

    Department of Credit Theory and Financial Management, Faculty of Economics, Saint Petersburg State University, Saint Petersburg 199034,Russia
  • Valentin Nazarov

    Department of Marketing, Tashkent State Economic University, Tashkent 100003, Uzbekista
  • Mukhabbat Ergasheva

    Department of Marketing, Tashkent State Economic University, Tashkent 100003, Uzbekistan
  • Sardar Turaev

    Department of Marketing, Tashkent State Economic University, Tashkent 100003, Uzbekistan
  • Dilnoza Meilyeva

    Department of Marketing, Tashkent State Economic University, Tashkent 100003, Uzbekistan
  • Daria Dinets

    Department of Finance, Accounting, and Auditing, Peoples’ Friendship University of Russia named after Patrice Lumumba, Moscow 117198, Russia
  • Yuri Sotskov

    United Institute of Informatics Problems, National Academy of Sciences of Belarus, 220072 Minsk, Belarus
  • N. B. A. Yousif

    Department of Sociology, College of Humanities and Science, Ajman University, Ajman P.O. Box 346, United Arab Emirates; Humanities and Social Sciences Research Centre (HSSRC), Ajman University, Ajman P.O. Box 346, United Arab Emirates
Article ID: 3941
DOI: https://doi.org/10.59400/sv3941

(This article belongs to the Special Issue Intelligent Systems in Sound and Vibration Analysis)

Keywords: AI regulation; energy technology; big data; algorithmic bias; explainable AI (XAI); multi-criteria decision-making (MCDM); quantum fuzzy sets; neuro-behavioral analysis

Abstract

The integration of Artificial Intelligence (AI) in energy infrastructure has created a new class of specialized intermediaries for environmental control, yet their opaque decision-making poses regulatory challenges. This paper proposes a novel regulatory framework for specialized sound and vibration platform operators in the energy sector and introduces a multi-criteria decision-making (MCDM) methodology to support oversight. The methodology integrates expert neuro-behavioral data, captured via Facial Action Coding System (FACS), with a quantum picture fuzzy rough set extension and the DEMATEL (Decision-Making Trial and Evaluation Laboratory) method. The application is demonstrated through a case study of a 250 MW combined-cycle gas turbine power plant, where the goal is to select optimal noise and vibration control technologies. The analysis assesses five key technologies against compliance parameters: algorithmic transparency, data governance, system reliability, operational accountability, and consumer protection. The proposed Neuro-Quantum Picture Fuzzy Rough MCDM model achieved a forecast accuracy of 0.987 for system performance, substantially outperforming Long Short-Term Memory (LSTM (0.876)), Recurrent Neural Network (RNN (0.575)), and AutoRegressive Integrated Moving Average (ARIMA (0.551)). The primary contribution is to initiate professional dialogue on governing AI-driven energy intermediaries, balancing technological innovation with energy stability, security, and consumer welfare. The paper recommends a comprehensive regulatory framework for a new class of energy intermediaries for financial and marketing optimisation called specialised sound and vibration platform operators.

Published
2026-03-23
How to Cite
Mikhaylov, A., Ikramov, M., Nabiyeva, N., Sokolov, B., Zhang, W., Nazarov, V., Ergasheva, M., Turaev, S., Meilyeva, D., Dinets, D., Sotskov, Y., & Yousif, N. B. A. (2026). Multi-criteria decision-making for sound and vibration reduction platforms for financial and marketing optimization in energy . Sound & Vibration, 60(2). https://doi.org/10.59400/sv3941
Issue
Vol. 60 No. 2 (2026)
Section
Article

Copyright (c) 2026 Alexey Mikhaylov, Murat Ikramov, Nilufar Nabiyeva, Boris Sokolov, Wenyi Zhang, Valentin Nazarov, Mukhabbat Ergasheva, Sardar Turaev, Dilnoza Meilyeva, Daria Dinets, Yuri Sotskov, N. B. A. Yousif

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

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