Smart City Gnosys
Smart city article details
| Title | A New Fuzzy Model Of Multi-Criteria Decision Support Based On Bayesian Networks For The Urban Areas' Decarbonization Planning |
|---|---|
| ID_Doc | 3040 |
| Authors | Mrówczyńska M.; Skiba M.; Leśniak A.; Bazan-Krzywoszańska A.; Janowiec F.; Sztubecka M.; Grech R.; Kazak J.K. |
| Year | 2022 |
| Published | Energy Conversion and Management, 268 |
| DOI | http://dx.doi.org/10.1016/j.enconman.2022.116035 |
| Abstract | The study introduces a framework for forecasting and decision-making in multi-criteria processes and proposes their application in the decarbonization of urban areas. Optimizing the multi-criteria decision-making process is an integrated set of information-processing-decision activities in which actual data, expert knowledge using fuzzy inference rules, Geographic Information System, and Bayesian networks are combined. Using proposed tools leads to designing a new approach to improving the energy efficiency of cities and reducing CO2 emissions using renewable energy. The integration of modern computational methods leads to rational planning of environmentally friendly and energy-conscious smart cities by the provisions of the Fit for 55 packages. The effectiveness of the proposed approach has been demonstrated in the example of three scenarios considering different types of renewable energy sources that can be implemented in urban areas. The success probability of decarbonizing these areas was calculated for defined quarters of the city of Zielona Góra with different parameters. Thereby the usefulness of the method was confirmed. Significantly, the likelihood of a successful deployment of photovoltaics (PV) in urban areas was estimated at 55.25% and for heat pumps at 28.79%. The proposed method enables a clear interpretation of the results, which may be the basis for urban energy efficiency planning. © 2022 The Author(s) |
| Author Keywords | Bayesian network; Cities' sustainable development; Energy policy scenarios; Fuzzy Analytical Hierarchy Process; Geographic Information System; Renewable energy sources |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
24883  | 0.871 | Otay İ.; Çevik Onar S.; Öztayşi B.; Kahraman C. | Evaluation Of Sustainable Energy Systems In Smart Cities Using A Multi-Expert Pythagorean Fuzzy Bwm & Topsis Methodology | Expert Systems with Applications, 250 (2024) |
| 50508 | 0.862 | Lai Y. | Smart City Space Simulation Based On Multidimensional Sensing Networks And Green Energy Intelligent Decision Support | Results in Engineering, 27 (2025) |
| 57354 | 0.86 | Alsattar H.A.; Qahtan S.; Mourad N.; Zaidan A.A.; Deveci M.; Jana C.; Ding W. | Three-Way Decision-Based Conditional Probabilities By Opinion Scores And Bayesian Rules In Circular-Pythagorean Fuzzy Sets For Developing Sustainable Smart Living Framework | Information Sciences, 649 (2023) |
| 36592 | 0.86 | Kutty A.A.; Kucukvar M.; Onat N.C.; Ayvaz B.; Abdella G.M. | Measuring Sustainability, Resilience And Livability Performance Of European Smart Cities: A Novel Fuzzy Expert-Based Multi-Criteria Decision Support Model | Cities, 137 (2023) |
| 6987 | 0.856 | Yang L. | Ai-Based Classification Model For Low-Energy Buildings: Promoting Sustainable Economic Development Of Smart Cities With Spherical Fuzzy Decision Algorithm | IEEE Access, 13 (2025) |
| 14323 | 0.853 | Krishankumar R.; Pamucar D.; Cavallaro F.; Ravichandran K.S. | Clean Energy Selection For Sustainable Development By Using Entropy-Based Decision Model With Hesitant Fuzzy Information | Environmental Science and Pollution Research, 29, 28 (2022) |
| 48111 | 0.852 | Krishankumar R.; Sangeetha V.; Rani P.; Ravichandran K.S.; Gandomi A.H. | Selection Of Apt Renewable Energy Source For Smart Cities Using Generalized Orthopair Fuzzy Information | 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (2020) |