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Monitoring the photovoltaic industry financing challenge by a neural network algorithm
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Batoul Zargar   , Hosein Jahangirnia * , Ali Emami meibodi , Mozhgan Safa |
| , Islamic Azad University, Qom, Iran. |
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Abstract: (2465 Views) |
Sounding the alarm of the energy crisis around the world has increasingly highlighted the need to move from finite fossil fuels to renewable fuels such as solar energy. The present study aims to study one of the most fundamental challenges that the solar photovoltaic industry is facing in the development path. To fulfill this aim, the opinions of industry experts were collected through interviews in the period from January 2021 to August 2021 and were analyzed by using text mining and self-organized maps for clustering. Based on the results of the research, issues related to the financing challenge of the photovoltaic industry can be examined in 8 clusters, which are; challenging factors, mediating conditions, consequences, government financing strategies, government incentives for the private sector, personal financing strategies, public financing strategies, guarantees and insurance. A comprehensive review of the issue of photovoltaic financing through this clustering showed that at this point of the industry life cycle, the public sector plays a prominent role in overcoming the challenge of financing. According to go over previous industry schedules, the government's planning policies must be reviewed.
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Article number: 3 |
| Keywords: Photovoltaic, Financing, Neural Networks, Self-Organizing Maps |
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Full-Text [PDF 1414 kb]
(266 Downloads)
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Type of Study: Research |
Subject:
Special
Received: 2022/03/25 | Accepted: 2022/06/18 | Published: 2022/06/18
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