Molecular fuzzy least squares optimization-based decision making with entropy expert weighting for transparent solar panel installation investments

Kou, G.; Din¸cer, H.; Y¨uksel, S.; Demir, C.; Eti, S.

doi:10.22111/ijfs.2025.9246

Document Type : Research Paper

Authors

¹ School of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu 611130, China

² School of Digital Media Engineering and Humanities, Hunan University of Technology and Business, Changsha 410205, China

³ School of Business, Istanbul Medipol University, Istanbul, Turkey

⁴ Department of Economics and Management, Khazar University, Baku, Azerbaijan

⁵ Clinic of Economics, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan

⁶ DepartmenClinic of Economics, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijant

⁷ IMU Vocational School, Istanbul Medipol University, Istanbul, Turkey

https://doi.org/10.22111/ijfs.2025.9246

Abstract

The performance of transparent solar panel projects is affected by both technological and environmental and economic
factors. However, the most important items should be identified for the efficient use of limited resources and effective
risk management. There are few studies in the literature determining these factors. Because of this situation, businesses
cannot direct their resources correctly and cannot create an effective strategy. A molecular fuzzy decision-making system
is created to determine the most successful alternative investment policies for these projects to satisfy this gap in the
literature. Various techniques are integrated in this model to reach the most effective solutions, such as molecular
fuzzy sets to handle uncertainties, q-learning algorithm to weight experts, least square optimization (LSO) to calculate
criteria weights and multi-objective particle swarm optimization (MOPSO) to rank investment strategies. The main
contribution of this study is proposing an innovative molecular fuzzy decision-making model that manages uncertainties
more effectively to select the most appropriate investment strategies for transparent solar panel investments. Considering
molecular fuzzy sets allows for more accurate modelling of uncertainties and subjective evaluations. The results show
that the most critical investment criterion for transparent solar panel investments is the regional solar radiation level.

Keywords

References

[1] M. Abdoos, H. Rashidi, P. Esmaeili, H. Yousefi, M. H. Jahangir, Forecasting solar energy generation in the Mediterranean
region up to 2030–2050 using convolutional neural networks (CNN), Cleaner Energy Systems, 10 (2025),
100167. https://doi.org/10.1016/j.cles.2024.100167

[2] J. Abu Qadourah, S. Alnusairat, Integrating aesthetics and sustainability: Evaluating the aesthetic perception of
photovoltaic installation on the apartment building fa¸cade in Jordan, Archnet-IJAR, 2025. https://doi.org/10.
1108/ARCH-02-2024-0038

[3] B. A. Akgul, M. S. Ozyazici, M. F. Hasoglu, Estimation of optimal tilt angles and solar radiation collected by fixed
and tracking solar panels for the Mediterranean region, Turkey Indian Journal of Physics, 98 (2024), 1187-1200.
https://doi.org/10.1007/s12648-023-02894-7

[4] M. Almadhhachi, I. Seres, I. Farkas, Harnessing solar power with aesthetic innovation: An in-depth study on
spherical and hemispherical photovoltaic configurations, Energy Science and Engineering, 12(5) (2024), 1888-1901.
https://doi.org/10.1002/ese3.1717

[5] A. S. Andrade-Arias, G. Kabir, M. Mirmohammadsadeghi, A. Gunasekaran, A. Elizondo-Noriega, Exploring public
perspectives on solar energy adoption in Mexico, Renewable and Sustainable Energy Reviews, 212 (2025), 115410.
https://doi.org/10.1016/j.rser.2025.115410

[6] E. Aramendia, P. E. Brockway, P. G. Taylor, et al., Estimation of useful-stage energy returns on investment for
fossil fuels and implications for renewable energy systems, Natural Energy, 9 (2024), 803-816. https://doi.org/
10.1038/s41560-024-01518-6

[7] B. Ayasi, I. X. V´azquez, M. Saleh, et al., Application of spiking neural networks and traditional artificial neural
networks for solar radiation forecasting in photovoltaic systems in Arab countries, Neural Computing and Applic,
(2025). https://doi.org/10.1007/s00521-025-11066-z

[8] S. Aziz, S. A. Chowdhury, M. Alauddin, Investment risks and policy solutions for renewable electricity in Bangladesh,
Energy for Sustainable Development, 85 (2025), 101605. https://doi.org/10.1016/j.esd.2024.101605

[9] P. Bonomo, F. Frontini, Building integrated photovoltaics (BIPV): Analysis of the technological transfer process
and innovation dynamics in the Swiss building sector, Buildings, 14(6) (2024), 1510. https://doi.org/10.3390/
buildings14061510

[10] P. Bonomo, F. Frontini, R. Loonen, A. H. M. E. Reinders, Comprehensive review and state of play in the use
of photovoltaics in buildings, Energy and Buildings, 323 (2024), 114737. https://doi.org/10.1016/j.enbuild.
2024.114737

[11] A. Borja Block, J. Escarre Palou, M. Courtant, A. Virtuani, G. Cattaneo, M. Roten, H. Y. Li, M. Despeisse, A.
Hessler-Wyser, U. Desai, et al., Colouring solutions for building integrated photovoltaic modules: A review, Energy
and Building, 314 (2024), 114253. https://doi.org/10.1016/j.enbuild.2024.114253

[12] S. Budhiraja, S. Agrawal, N. Sharma, Infrared and visible image fusion based on sparse representation and weighted
least square optimization, IETE Journal of Research, (2025), 1-13. https://doi.org/10.1080/03772063.2025.
2469642

[13] L. Chen, J. Wang, Z. Wu, Y. Yu, M. Zhou, G. Li, 5G and energy internet planning for power and communication
network expansion, Iscience, 27(3) (2024). https://doi.org/10.1016/j.isci.2024.109290

[14] H. Din¸cer, S. Y¨uksel, G. O. Olaru, S. Eti, Integrated information system based on Q-learning algorithm and
multi-objective particle swarm optimization with molecular fuzzy-based decision-making for corporate environmental
investments, Information Sciences, 698 (2025), 121757. https://doi.org/10.1016/j.ins.2024.121757

[15] N. Fahoum, M. Sitbon, Effects of building color, material, and angle on bifacial and transparent solar panels,
Processes, 13(2) (2025), 480. https://doi.org/10.3390/pr13020480

[16] S. Forhad, M. S. Hossen, S. Noman, I. A. Diba, F. Mahmud, M. O. Ullah, M. R. K. Shuvo, Influence of a
dual axis IoT-based off-grid solar tracking system and Wheatstone bridge on efficient energy harvesting and management, Journal of Engineering Research and Reports, 26(3) (2024), 125-136. https://doi.org/10.9734/jerr/
2024/v26i31099

[17] K. Fragkos, G. Charalampous, I. Fountoulakis, K. Papachristopoulou, D. Hadjimitsis, S. Kazadzis, Next-day solar
irradiance forecasting: A preliminary study in Limassol, 2024 3rd International Conference on Energy Transition
in the Mediterranean Area (SyNERGY MED), Limassol, Cyprus, 2024, 1-5, 10.1109/SyNERGYMED62435.2024.
10799286

[18] H. Gholami, A holistic multi-criteria assessment of solar energy utilization on urban surfaces, Energies, 17(21)
(2024), 5328. https://doi.org/10.3390/en17215328

[19] M. Gholami, A. Arefi, A. Hasan, et al., Enhancing energy autonomy of greenhouses with semi-transparent photovoltaic
systems through a comparative study of battery storage systems, Scientific Reports, 15 (2024), 2213.
https://doi.org/10.1038/s41598-025-85418-z

[20] A. Habchi, B. Hartiti, H. Labrim, P. Thevenin, E. Ntsoenzok, Amplification of green hydrogen production using an
innovative new hybrid semi-transparent photovoltaic solar panel integrated with tubular thermoelectric generators,
Applied Energy, 384 (2025), 125464. https://doi.org/10.1016/j.apenergy.2025.125464

[21] A. Hussain, M. Umair, S. Khan, W. B. Alonazi, S. S. Almutairi, A. Malik, Exploring sustainable healthcare:
Innovations in health economics, social policy, and management, Heliyon, 10(13) (2024), e33186. https://doi.
org/10.1016/j.heliyon.2024.e33186

[22] H. A. Kazem, M. T. Chaichan, A. H. Al-Waeli, K. Sopian, Recent advancements in solar photovoltaic tracking
systems: An in-depth review of technologies, performance metrics, and future trends, Solar Energy, 282 (2024),
112946. https://doi.org/10.1016/j.solener.2024.112946

[23] K. Kumba, P. Upender, P. Buduma, M. Sarkar, S. P. Simon, V. Gundu, Solar tracking systems: Advancements,
challenges, and future directions: A review, Energy Reports, 12 (2024), 3566-3583. https://doi.org/10.1016/j.
egyr.2024.09.038

[24] Z. Li, J. Ma, Q. Wang, M. Wang, F. Jiang, Enhancing urban solar irradiation prediction with shadow-attention
graph neural networks: Implications for net-zero energy buildings in New York City, Sustainable Cities and Society,
120 (2025), 106133. https://doi.org/10.1016/j.scs.2025.106133

[25] T. Liu, M. M. Almutairi, J. Ma, A. Stewart, Z. Xing, M. Liu, Y. Cho, Solution-processed thin film transparent
photovoltaics: Present challenges and future development, Nano-Micro Letters, 17(1) (2025), 49. https://doi.org/
10.1007/s40820-024-01547-6

[26] H. Luo, M. Vasiliev, T. He, P. Wang, J. Lyford, V. Rosenberg, C. Li, Transparent solar photovoltaic windows
provide a strong potential for self-sustainable food production in forward-looking greenhouse farming architectures,
Cleaner Engineering and Technology, (2025), 100895. https://doi.org/10.1016/j.clet.2025.100895

[27] X. Luo, Y. Zhang, J. Lu, J. Ge, Multi-objective optimization of the office park building envelope with the goal of
nearly zero energy consumption, Journal of Building Engineering, 84 (2024), 108552. https://doi.org/10.1016/
j.jobe.2024.108552

[28] S. Minazhova, M. Kurrat, B. Ongar, A. Georgiev, Deploying a rooftop PV panels in the southern regions of
Kazakhstan, Energy, (2025), 135205. https://doi.org/10.1016/j.energy.2025.135205

[29] R. Miranda-Jim´enez, O. Vigil-Gal´an, J. R. Gonz´alez-Castillo, A. R. Ter´an-Cuevas, M. E. Guti´errez-Castillo, L.
R. Tovar-G´alvez, Solar PV technologies selection for the design of photovoltaic installations in Mexico based on the
analysis of meteorological satellite data from the region, Atm´osfera, 38 (2024). https://doi.org/10.20937/atm.
53282

[30] Z. Ozturk, M. Terkes, A. Demirci, Optimal planning of hybrid power systems under economic variables and different
climatic regions: A case study of T¨urkiye, Renewable Energy, 232 (2024), 121029. https://doi.org/10.1016/j.
renene.2024.121029

[31] J. A. Pinto, G. L. Tiago Filho, A. L. C. de Jesus, M. D. G. Barbedo, I. F. S. dos Santos, R. M. Barros, F. D.
G. B. da Silva, A comparative analysis of thermosolar and photovoltaic systems for meeting residential hot water
demands, Renewable Energy, (2025), 122652. https://doi.org/10.1016/j.renene.2025.122652

[32] A. Qamili, S. Kapia, Evaluation and integration of photovoltaic (PV) systems in Albanian energy landscape, Solar
Compass, 10 (2024), 100070. https://doi.org/10.1016/j.solcom.2024.100070

[33] S. A. Sadat, K. Mittal, J. M. Pearce, Using investments in solar photovoltaics as inflation hedges, Energies, 18(4)
(2025), 890. https://doi.org/10.3390/en18040890

[34] S. A. Sadat, J. M. Pearce, Techno-economic evaluation of electricity pricing structures on photovoltaic and
photovoltaic-battery hybrid systems in Canada, Renewable Energy, 242 (2025), 22456. https://doi.org/10.1016/
j.renene.2025.122456

[35] J. Shand, E. Glakpe, C. Ivey, Policy implications of implementing residential PV solar energy systems in developing
regions, Energy Policy, 196 (2025), 114414. https://doi.org/10.1016/j.enpol.2024.114414

[36] Y. Shen, W. Liu, H. Din¸cer, S. Y¨uksel, Hybrid molecular fuzzy recommender systems for impact of climate change
on renewable energy performance, Renewable Energy, 245 (2025), 122799. https://doi.org/10.1016/j.renene.
2025.122799

[37] F. Sierro, Y. Blumer, Collective action without community? Perspectives from project developers and participants
in citizen-financed photovoltaic projects, Energy Research and Social Science, 119 (2025), 103856. https://doi.
org/10.1016/j.erss.2024.103856

[38] P. N. Tham, T. D. Thuy, P. K. Nam, E. Papyrakis, Policy uncertainty, public perception, and the preferences for
rooftop solar power systems: A choice experiment study in Vietnam, Renewable and Sustainable Energy Reviews,
208 (2025), 115067. https://doi.org/10.1016/j.rser.2024.115067

[39] A. Tro-Cabrera, R. Lago-Aurrekoetxea, I. Mart´ınez-de-Alegr´ıa, E. Villamor, A. Campos-Celador, A methodology
for assessing rooftop solar photovoltaic potential using GIS open-source software and the EROI constraint, Energy
and Buildings, (2025), 115401. https://doi.org/10.1016/j.enbuild.2025.115401

[40] M. Umair, W. Ahmad, B. Hussain, C. Fortea, M. L. Zlati, V. M. Antohi, Empowering Pakistan’s economy: The
role of health and education in shaping labor force participation and economic growth, Economies, 12(5) (2024), 113.
https://doi.org/10.3390/economies12050113

[41] Y. Wang, S. Lee, C. Li, et al., Techno-economic evaluation of solar photovoltaic power production in China
for sustainable development and the environment, Environ Dev Sustain, (2024). https://doi.org/10.1007/
s10668-024-05837-2

[42] H. Wang, X. Wang, Y. Yin, X. Deng, M. Umair, Evaluation of urban transportation carbon footprint—Artificial
intelligence based solution, Transportation Research Part d: Transport and Environment, 136 (2024), 104406.
https://doi.org/10.1016/j.trd.2024.104406

[43] Z. Wu, Z. Chen, C. Wang, M. Zhou, J. Wang, L. Chen, Unlocking the potential of rooftop solar panels: An incentive
rate structure design, Energy Policy, 190 (2024), 114159. https://doi.org/10.1016/j.enpol.2024.114159

[44] Q. Xuan, N. Yang, M. Kai, C. Wang, B. Jiang, X. Liu, B. Zhao, Combined daytime radiative cooling and solar
photovoltaic/thermal hybrid system for year-round energy saving in buildings, Energy, 304 (2024), 132178. https:
//doi.org/10.1016/j.energy.2024.132178

[45] Y. Zhang, Enhancing solar irradiance prediction for sustainable energy solutions employing a hybrid machine
learning model; improving hydrogen production through Photoelectrochemical device, Applied Energy, 382 (2025),
125280. https://doi.org/10.1016/j.apenergy.2025.125280

[46] H. Zhang, X. Chen, W. Li, R. Peng, J. Ji, X. Su, C. Luo, Energy, economic, emissions analysis of semi-flexible
crystalline silicon photovoltaic system integrated with factory building roofs based on actual electricity load and cost
conditions, Energy and Buildings, 330 (2025), 115358. https://doi.org/10.1016/j.enbuild.2025.115358

[47] T. Zhang, J. Zhai, Z. Shi, Q. Li, J. Cai, Comparison of PV and PV/T systems in different regions of China:
Energy gain, energy cost, energy payback and energy return, Energy and Built Environment, (2024). https://doi.
org/10.1016/j.enbenv.2024.12.001

[48] N. Zhao, J. Zhang, C. Ding, Integrated 3E impacts of photovoltaic systems: A comparative study of panels and
windows, Case Studies in Thermal Engineering, 66 (2025), 105736. https://doi.org/10.1016/j.csite.2024.
105736

Iranian Journal of Fuzzy Systems

Molecular fuzzy least squares optimization-based decision making with entropy expert weighting for transparent solar panel installation investments

References

References

Volume 22, Issue 3
May and June 2025
Pages 55-86

Molecular fuzzy least squares optimization-based decision making with entropy expert weighting for transparent solar panel installation investments

References

References

Volume 22, Issue 3May and June 2025Pages 55-86

Volume 22, Issue 3
May and June 2025
Pages 55-86