April 20, 2026

Saclung

The Future of Business, Today

Decision algorithm with fuzzy framework and evaluation of advanced financial management policy

Decision algorithm with fuzzy framework and evaluation of advanced financial management policy
  • Pavić, Z. & Novoselac, V. Notes on TOPSIS method. Int. J. Res. Eng. Sci. 1, 5–12 (2013).

    Google Scholar 

  • Wei, J. & Lin, X. The multiple attribute decision-making VIKOR method and its application. in Proceedings of the 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing 1–4 (IEEE, 2008).

  • Beccali, M., Cellura, M. & Mistretta, M. Decision-making in energy planning. Application of the electre method at regional level for the diffusion of renewable energy technology. Renew. Energy 28, 2063–2087 (2003).

    Google Scholar 

  • Zadeh, L. A. Fuzzy sets. Inf. Control 8, 338–353. (1965).

    Article 
    MATH 

    Google Scholar 

  • Gehrke, M., Walker, C. & Walker, E. Some comments on interval valued fuzzy sets. Structure 1 (1996).

  • Atanassov, K. T. Intuitionistic fuzzy sets. Fuzzy Sets Syst. 20, 87–96. (1986).

    Article 
    MATH 

    Google Scholar 

  • Kumar, P. S. AI-driven decision support system for intuitionistic fuzzy assignment problems 352–398 (2024).

  • Kumar, P. S. The theory and applications of the software-based PSK method for solving intuitionistic fuzzy solid transportation problems. in Perspectives and Considerations on the Evolution of Smart Systems 137–186 (IGI Global, 2023).

  • Atanassov, K. T. (1999) Interval valued intuitionistic fuzzy sets. In Intuitionistic Fuzzy Sets: Theory and Applications Atanassov KT (ed.) Studies in Fuzziness and Soft Computing. Physica-Verlag HD, Heidelberg pp. 139–177

  • Liaqat, M., Yin, S., Akram, M. & Ijaz, S. Aczel-alsina aggregation operators based on interval-valued complex single-valued neutrosophic information and their application in decision-making problems. J. Innov. Res. Math. Comput. Sci. 1, 40–66 (2022).

    Google Scholar 

  • Kumar, P. S. The PSK method for solving fully intuitionistic fuzzy assignment problems with some software tools 149–202 (2019).

  • Kumar, P. S. The Psk method: A new and efficient approach to solving fuzzy transportation problems. in Transport and logistics planning and optimization 149–197 (IGI Global, 2023).

  • Kumar, P. S. Algorithms for solving the optimization problems using fuzzy and intuitionistic fuzzy set. Int. J. Syst. Assur. Eng. Manag. 11, 189–222 (2020).

    Google Scholar 

  • Yager, R. R. Pythagorean fuzzy subsets. in Proceedings of the 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS) 57–61 (IEEE, 2013).

  • Cuong, B. C. & Kreinovich, V. Picture fuzzy sets-a new concept for computational intelligence problems. in Proceedings of the 2013 Third World Congress on Information and Communication Technologies (WICT 2013) 1–6 (IEEE, 2013).

  • Yager, R. R. Generalized orthopair fuzzy sets. IEEE Trans. Fuzzy Syst. 25, 1222–1230 (2016).

    Google Scholar 

  • Wang, H., Smarandache, F., Zhang, Y. & Sunderraman, R. Single valued neutrosophic sets Infinite study (2010).

  • Çakır, E. & Taş, M. A. Circular intuitionistic fuzzy decision making and its application. Expert Syst. Appl. 225, 120076 (2023).

    Google Scholar 

  • Irem, O. & Kahraman, C. A novel circular intuitionistic fuzzy AHP&VIKOR methodology: An application to a multi-expert supplier evaluation problem. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 28, 194–207 (2022).

    Google Scholar 

  • Alkan, N. & Kahraman, C. Circular intuitionistic fuzzy TOPSIS method: Pandemic hospital location selection. J. Intell. Fuzzy Syst. 42, 295–316 (2022).

    Google Scholar 

  • Otay, İ, Onar, S. Ç., Öztayşi, B. & Kahraman, C. A novel interval valued circular intuitionistic fuzzy AHP methodology: Application in digital transformation project selection. Inf. Sci. 647, 119407 (2023).

    Google Scholar 

  • Çakir, E., Taş, M. A. & Ulukan, Z. A new circular intuitionistic fuzzy MCDM: A case of Covid-19 medical waste landfill site evaluation. in Proceedings of the 2021 IEEE 21st international symposium on computational intelligence and informatics (CINTI) 000143–000148 (IEEE, 2021).

  • Garg, H., Ünver, M., Olgun, M. & Türkarslan, E. An extended EDAS method with circular intuitionistic fuzzy value features and its application to multi-criteria decision-making process. Artif. Intell. Rev. 56, 3173–3204. (2023).

    Article 

    Google Scholar 

  • Karamoozian, A. & Wu, D. A hybrid risk prioritization approach in construction projects using failure mode and effective analysis. Eng. Constr. Archit. Manag. 27, 2661–2686 (2020).

    Google Scholar 

  • Karamoozian, A. & Wu, D. A hybrid approach for the supply chain risk assessment of the construction industry during the COVID-19 pandemic. IEEE Trans. Eng. Manag. 71, 4035–4050 (2022).

    Google Scholar 

  • Karamoozian, M. & Hong, Z. Using a decision-making tool to select the optimal industrial housing construction system in Tehran. J. Asian Archit. Build. Eng. 22, 2189–2208. (2023).

    Article 

    Google Scholar 

  • Karamoozian, A., Wu, D. & Luo, C. Risk assessment of renewable energy projects using a novel hybrid fuzzy approach. Int. J. Green Energy 20, 1597–1611. (2023).

    Article 

    Google Scholar 

  • Karamoozian, A., Luo, C. & Wu, D. Risk assessment of occupational safety in construction projects using uncertain information. Hum. Ecol. Risk Assess. Int. J. 29, 1134–1151. (2023).

    Article 
    CAS 

    Google Scholar 

  • Karamoozian, A., Wu, D. & Luo, C. Green supplier selection in the construction industry using a novel fuzzy decision-making approach. J. Constr. Eng. Manag. 149, 04023033. (2023).

    Article 

    Google Scholar 

  • Karamoozian, A., Wu, D., Lambert, J. H. & Luo, C. Risk assessment of renewable energy projects using uncertain information. Int. J. Energy Res. 46, 18079–18099. (2022).

    Article 

    Google Scholar 

  • Karamoozian, M. & Zhang, H. Obstacles to green building accreditation during operating phases: Identifying challenges and solutions for sustainable development. J. Asian Archit. Build. Eng. 24, 350–366. (2025).

    Article 

    Google Scholar 

  • Irvanizam, I., Nasution, M. K., Tulus, T. & Nababan, E. B. A hybrid decision support framework using MEREC-RAFSI with spherical fuzzy numbers for selecting banking financial aid recipients. IEEE Access (2025).

  • Phung, T. M., Tran, Q. N., Nguyen, N. H. & Nguyen, T. H. Financial decision-making power and risk taking. Econ. Lett. 206, 109999 (2021).

    Google Scholar 

  • Kirişci, M. An integrated decision-making process for risk analysis of decentralized finance. Neural Comput. Appl. 37, 6021–6051. (2025).

    Article 

    Google Scholar 

  • Kaur, T., Rani, K., Thakur, P. & Talwandi, N. S. Enhanced decision support system for financial risk assessment using hybrid fuzzy logic and machine learning. in Proceedings of the 2024 International Conference on Computational Intelligence and Computing Applications (ICCICA) Vol. 1, 97–102 (IEEE, 2024).

  • Available Version (via Google Scholar).

  • Kaya, S. K. A novel two-phase group decision-making model for circular supplier selection under picture fuzzy environment. Environ. Sci. Pollut. Res. Int. 30, 34135–34157. (2023).

    Article 
    PubMed 

    Google Scholar 

  • Kahraman, C. & Alkan, N. Circular intuitionistic fuzzy TOPSIS method with vague membership functions: supplier selection application context. Notes Intuitionistic Fuzzy Sets 27, 24–52 (2021).

    Google Scholar 

  • Some Q‐rung Orthopair Fuzzy Heronian Mean Operators in Multiple Attribute Decision Making – Wei – 2018 – International Journal of Intelligent Systems – Wiley Online Library Available online: (accessed on 25 December 2022).

  • Dejian, Y. & Yingyu, W. Interval-valued intuitionistic fuzzy heronian mean operators and their application in multi-criteria decision making. Afr. J. Bus. Manage. 6, 4158–4168 (2012).

    Google Scholar 

  • Liu, P., Liu, Z. & Zhang, X. Some intuitionistic uncertain linguistic heronian mean operators and their application to group decision making. Appl. Math. Comput. 230, 570–586 (2014).

    MathSciNet 
    MATH 

    Google Scholar 

  • Zhang, H., Zhang, R., Huang, H. & Wang, J. Some picture fuzzy dombi heronian mean operators with their application to multi-attribute decision-making. Symmetry 10, 593. (2018).

    Article 
    ADS 
    MATH 

    Google Scholar 

  • Hussain, A., Ullah, K., Pamucar, D., Haleemzai, I. & Tatić, D. Assessment of solar panel using multiattribute decision-making approach based on intuitionistic fuzzy aczel alsina heronian mean operator. Int. J. Intell. Syst. 2023, e6268613. (2023).

    Article 

    Google Scholar 

  • Mishra, A. R. et al. Interval-valued fermatean fuzzy heronian mean operator-based decision-making method for urban climate change policy for transportation activities. Eng. Appl. Artif. Intell. 124, 106603 (2023).

    Google Scholar 

  • Peng, H., Wang, J. & Cheng, P. A linguistic intuitionistic multi-criteria decision-making method based on the frank heronian mean operator and its application in evaluating coal mine safety. Int. J. Mach. Learn. Cybern. 9, 1053–1068 (2018).

    CAS 

    Google Scholar 

  • Bernardo, A. E., Chowdhry, B. & Goyal, A. Assessing project risk. J. Appl. Corp. Financ. 24, 94–100. (2012).

    Article 

    Google Scholar 

  • Calculating ROI for Service Design Improvements: A Case Study Approach | by Ricardo Faria—Sr Service & Experience Designer | Medium Available online: (accessed on 14 May 2025).

  • Liquid Assets—Definition, Examples, Vs Fixed Assets Available online: (accessed on 14 May 2025).

  • Yu, D. Intuitionistic fuzzy geometric heronian mean aggregation operators. Appl. Soft Comput. 13, 1235–1246 (2013).

    Google Scholar 

  • Li, Z. & Wei, G. Pythagorean fuzzy heronian mean operators in multiple attribute decision making and their application to supplier selection. Int. J. Knowl. Based Intell. Eng. Syst. 23, 77–91 (2019).

    CAS 

    Google Scholar 

  • Liu, P. & Chen, S.-M. Group decision making based on heronian aggregation operators of intuitionistic fuzzy numbers. IEEE Trans. Cybern. 47, 2514–2530 (2016).

    PubMed 

    Google Scholar 

  • Sabir, Z., Umar, M., Salahshour, S. & Saeed, T. A reliable neural network procedure for the novel sixth-order nonlinear singular pantograph differential model. Mod. Phys. Lett. B 39(12), 2450473 (2025).

    CAS 

    Google Scholar 

  • Sabir, Z., Khansa, S., Baltaji, G. & Saeed, T. A Bayesian regularization neural network procedure to solve the language learning system. Knowl.-Based Syst. 310, 112997 (2025).

  • Sabir, Z., Kotob, I. A., Sheikh, L. A. & Saeed, T. A novel computational approach-based hyperbolic tangent sigmoid deep neural network for the hepatitis B virus model. Int. J. Geom. Methods Mod. Phys. 22(04), 2450315. (2025).

    Article 
    MathSciNet 

    Google Scholar 

  • Umar, M., Sabir, Z., Raja, M. A. Z., Amin, F., Saeed, T. & Sanchez, Y. G. Design of intelligent computing solver with Morlet wavelet neural networks for nonlinear predator–prey model. Appl. Soft Comput. 134 (2023). https://doi.org/10.1016/j.asoc.2022.109975.

  • Bhat, S. A., Sabir, Z., Raja, M. A. Z., Saeed, T. & Alshehri, A. M. A novel heuristic Morlet wavelet neural network procedure to solve the delay differential perturbed singular model. Knowl.-Based Syst. 292, 111624 (2024).

  • Sabir, Z., Saeed, T., Guirao, J. L., Sánchez, J. M. & Valverde, A. A swarming Meyer wavelet computing approach to solve the transport system of goods. Axioms 12(5), 456 (2023).

    Google Scholar 

  • Saeed, T., Guirao, J. L. G., Sabir, Z., Alsulami, H. H. & Sánchez, Y. G. A computational approach to solve the nonlinear biological prey–predator system. Fractals 30(10), 2240267. (2022).

    Article 
    ADS 

    Google Scholar 

  • Sabir, Z., Zahoor Raja, M. A., Guirao, J. L. G. & Saeed, T. Design of mayer wavelet neural networks for solving functional nonlinear singular differential equation. Math. Probl. Eng. 2022, 1–11 (2022). https://doi.org/10.1155/2022/1213370.

  • Saeed, T., Sabir, Z., Alhodaly, M. S., Alsulami, H. H. & Sánchez, Y. G. An advanced heuristic approach for a nonlinear mathematical based medical smoking model. Results Phys. 32, 105137 (2022).

    Google Scholar 

  • Sabir, Z., Raja, M. A. Z., Guirao, J. L. & Saeed, T. Meyer wavelet neural networks to solve a novel design of fractional order pantograph Lane-Emden differential model. Chaos Solitons Fract. 152, 111404 (2021).

    MathSciNet 
    MATH 

    Google Scholar 

  • Umar, M., Sabir, Z., Raja, M. A. Z., Amin, F., Saeed, T. & Guerrero-Sanchez, Y. Integrated neuro-swarm heuristic with interior-point for nonlinear SITR model for dynamics of novel COVID-19. Alex. Eng. J. 60(3), 2811–2824 (2021).

  • Sabir, Z., Guirao, J. L. G., Saeed, T. & Erdoğan, F. Design of a novel second-order prediction differential model solved by using adams and explicit runge-kutta numerical methods. Math. Probl. Eng. 2020, 1–7. (2020).

    Article 
    MathSciNet 
    MATH 

    Google Scholar 

  • Guirao, J. L. G., Sabir, Z. & Saeed, T. Design and numerical solutions of a novel third-order nonlinear emden-fowler delay differential model. Math. Probl. Eng. 2020, 1–9. (2020).

    Article 
    MATH 

    Google Scholar 

  • Abdelkawy, M. A., Sabir, Z., Guirao, J. L. G. & Saeed, T. Numerical investigations of a new singular second-order nonlinear coupled functional Lane-Emden model. Open Phys. 18(1), 770–778. (2020).

    Article 

    Google Scholar 

  • Sabir, Z., García Guirao, J. L. & Saeed, T. Solving a novel designed second order nonlinear Lane-Emden delay differential model using the heuristic techniques. Chaos Solitons Fract. 152, 111405 (2021).

    Google Scholar 

  • Sabir, Z. et al. Neuro-Swarm heuristic using interior-point algorithm to solve a third kind of multi-singular nonlinear system. Math. Biosci. Eng. 18(5), 5285–5308 (2021).

    MathSciNet 
    PubMed 
    MATH 

    Google Scholar 

  • Hussain, S., Zeb, A., Rasheed, A. & Saeed, T. Stochastic mathematical model for the spread and control of Corona virus. Adv. Differ. Equ. 2020(1), 574. (2020).

    Article 
    MathSciNet 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Solving a Novel Designed Second Order Nonlinear Lane–Emden Delay Differential Model Using the Heuristic Techniques Available online: (accessed on 14 April 2025).

  • Neuro-Swarm Heuristic Using Interior-Point Algorithm to Solve a Third Kind of Multi-Singular Nonlinear System Available online: (accessed on 14 April 2025).

  • Hussain, S., Zeb, A., Rasheed, A. & Saeed, T. Stochastic mathematical model for the spread and control of corona virus. Adv. Differ. Equ. 2020, 574. (2020).

    Article 
    MathSciNet 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Azeem, W. et al. Analysis of einstein aggregation operators based on complex intuitionistic fuzzy sets and their applications in multi-attribute decision-making. MATH 8, 6036–6063. (2023).

    Article 

    Google Scholar 

  • Garg, H., Ali, Z., Mahmood, T., Ali, M. R. & Alburaikan, A. Schweizer-sklar prioritized aggregation operators for intuitionistic fuzzy information and their application in multi-attribute decision-making. Alex. Eng. J. 67, 229–240 (2023).

    Google Scholar 

  • Rani, D. & Garg, H. Multiple attributes group decision-making based on trigonometric operators, particle swarm optimization and complex intuitionistic fuzzy values. Artif. Intell. Rev. 56, 1787–1831 (2023).

    Google Scholar 

  • Khan, M. R., Raza, A. & Khan, Q. Multi-attribute decision-making by using intuitionistic fuzzy rough aczel-alsina prioritize aggregation operator. J. Innov. Res. Math. Comput. Sci. 1, 96–123 (2022).

    Google Scholar 

  • link

    Copyright © All rights reserved. | Newsphere by AF themes.