Assessment of safety management system on energy investment risk using house of quality based on hybrid stochastic interval-valued intuitionistic fuzzy decision-making approach

Su, Fang; Zhou, Pengfei; Dınçer, Hasan; Yüksel, Serhat

doi:10.1016/j.ssci.2021.105333

Cited by 78 publications

(11 citation statements)

References 83 publications

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“…For instance, in some models, only the positive ideal solution is considered [24,25]. However, the TOPSIS method also uses negative ideal solutions, contributing to more accurate results [26].…”

Section: The Purpose and Novelty Of This Studymentioning

confidence: 99%

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Application of M-SWARA and TOPSIS Methods in the Evaluation of Investment Alternatives of Microgeneration Energy Technologies

et al. 2022

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Investments in microgeneration technologies help to boost the usage of clean energy while reducing pollution. However, selecting the appropriate investment remains the most critical phase in developing these technologies. This study aims to design a multi-criteria decision-making method (MCDM) to evaluate investment alternatives for microgeneration energy technologies. The proposed MCDM is based on a Multi Stepwise Weight Assessment Ratio Analysis (M-SWARA), to define the relative importance of the factors. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and q-Rung Orthopair Fuzzy Soft Sets (q-ROFSs) are used to rank investment alternatives. Calculations were also made with Intuitionistic Fuzzy Sets (IFSs) and Pythagorean Fuzzy Sets (PFSs). For analysis, five evaluation criteria were selected based on the literature: frequency of maintenance, ease of installation, environmental adaptation, transmission technologies, and efficiency of cost. Similarly, six alternatives for microgeneration technology investments were selected: ground source heat pumps, micro hydroelectric power, micro combined heat and power, micro bioelectrochemical fuel cell systems, small-scale wind turbines, and photovoltaic systems. The results showed that cost efficiency was the most significant factor in the effectiveness of microgeneration energy investments, and the photovoltaic system was the best alternative to increase microgeneration energy technology investment performance. Furthermore, the results were the same for the analyses made with IFSs and PFSs, demonstrating the reliability of the proposed method. Therefore, investors in microgeneration technologies should prioritize photovoltaic systems. This conclusion is supported by the fact that photovoltaic is a renewable energy source that has witnessed the most technological improvements and cost reductions over the last decade.

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Section: The Purpose and Novelty Of This Studymentioning

confidence: 99%

“…In this study, this technique is extended with q-ROFSs. After providing the evaluations, a decision matrix is constructed as in Equation ( 21) [26].…”

Section: Topsis With Q-rofssmentioning

confidence: 99%

Application of M-SWARA and TOPSIS Methods in the Evaluation of Investment Alternatives of Microgeneration Energy Technologies

et al. 2022

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“…Due to the corruption of the host country's government, the assets of multinational enterprises may be handed over to the local government of the host country in a plundering manner or at a very low price. The risk caused by this phenomenon is called nationalization risk [ 12 , 13 ].…”

Section: Investment Risk and DL Model Analysis Of Multinational Enter...mentioning

confidence: 99%

Application of Deep Learning Model in the Avoidance of Investment Risk of Multinational Enterprises

Yan

Feng

2022

Computational Intelligence and Neuroscience

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With the continuous improvement and development of the socialist market economic system, China's economic development has full momentum, but the domestic market is no longer sufficient to meet the needs of enterprise development. China has always focused on peaceful diplomacy, and the world market has a strong demand for Chinese products. This work aims to improve the accuracy of exchange rate forecasting. The risk factors that may be encountered in the investment process of multinational enterprises can be effectively avoided. Combining the advantages of Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN), the LSTM-CNN (Long Short-Term Memory-Convolutional Neural Network) model is proposed to predict the volatility trend of stocks. Firstly, the investment risk of multinational enterprises is analyzed, and, secondly, the principles of the used CNN and LSTM are expounded. Finally, the performance of the proposed model is verified by setting experiments. The experimental results demonstrate that when predicting the 10 selected stocks, the proposed LSTM-CNN model has the highest accuracy in predicting the volatility of stocks, with an average accuracy of 60.1%, while the average accuracy of the rest of the models is all below 60%. It can be found that the stock category does not have a great impact on the prediction accuracy of the model. The average prediction accuracy of the CNN model is 0.578, which is lower than that of the Convolutional Neural Network-Relevance model, and the prediction accuracy of the LSTM model is 0.592, which is better than that of the Long Short-Term Memory-Relevance model. The designed model can be used to predict the stock market to guide investors to make effective investments and reduce investment risks based on relevant cases. The research makes a certain contribution to improving the company's income and stabilizing the national economic development.

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“…Bunun ardından, söz konusu matris normalize edilmektedir [33,34]. Daha sonraki aşamada ise toplam ilişki matrisi hesaplanmaktadır [35,36]. Son olarak da toplam matrisindeki rakamlar dikkate alınarak kriter ağırlıkları hesaplanmaktadır [37,38].…”

Section: Dematel Yöntemiunclassified

Yeşil Hastanelerin Gelişimi İçin Stratejik Unsurların Belirlenmesi: Enerji Bazlı Faktörlere Yönelik DEMATEL Yöntemi ile Bir Analiz

Yüksel

Dınçer

Çelebi

2022

İstatistik Ve Uygulamalı Bilimler Dergisi

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Bu çalışmanın amacı yeşil hastanelerin gelişimi için önem arz eden stratejik unsurların belirlenmesidir. Bu kapsamda, ilk olarak detaylı bir literatür taraması gerçekleştirilmiştir. Yapılan bu incelemeler sayesinde, enerji bazlı dört farklı faktör tespit edilmiştir. Bu kriterler karbon emisyonunun azaltılması, temiz enerji kullanımı, enerji verimliliğinin sağlanması ve düşük enerji tüketen ekipmanların seçilmesi şeklindedir. Bu kriterler arasından en önemlilerinin tespit edilebilmesi için DEMATEL yöntemiyle bir analiz gerçekleştirilmiştir. Sonuç olarak, yeşil hastanelerin gelişebilmesi için en fazla önem arz eden kriter temiz enerji kullanımıdır. Ayrıca, karbon emisyonunun azaltılması da önem arz eden diğer önemli bir faktördür. Elde edilen bu sonuçlardan anlaşılabileceği üzere, hastanelerin temiz enerji kullanımına acilen geçmeleri gerekmektedir. Bu süreçte, küçük ölçekli güneş panelleri dikkate alınabilmektedir. Bu paneller sayesinde, hastaneler hem kendi enerjilerini üretebilmekte hem de kullanılan enerji çevre dostu olabilmektedir. Bu bağlamda, yapılacak kapsamlı araştırma ve geliştirme çalışmaları sayesinde, bu enerji türlerinin maliyetlerinin düşürülebilmesi mümkün olabilecektir. Belirtilen bu hususa ek olarak, vergi indirimi ve düşük faizli kredi kullanımı gibi devlet teşvikleri sayesinde, küçük ölçekli güneş panellerinin maliyet avantajı elde edebilmesi mümkün olabilecektir.

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Assessment of safety management system on energy investment risk using house of quality based on hybrid stochastic interval-valued intuitionistic fuzzy decision-making approach

Cited by 78 publications

References 83 publications

Application of M-SWARA and TOPSIS Methods in the Evaluation of Investment Alternatives of Microgeneration Energy Technologies

Application of M-SWARA and TOPSIS Methods in the Evaluation of Investment Alternatives of Microgeneration Energy Technologies

Application of Deep Learning Model in the Avoidance of Investment Risk of Multinational Enterprises

Yeşil Hastanelerin Gelişimi İçin Stratejik Unsurların Belirlenmesi: Enerji Bazlı Faktörlere Yönelik DEMATEL Yöntemi ile Bir Analiz

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