A Hybrid Hesitant 2-Tuple IVSF Decision Making Approach to Analyze PERT-Based Critical Paths of New Service Development Process for Renewable Energy Investment Projects

Cheng, Fei-Fei; Lin, Minghua; Yüksel, Serhat; Dınçer, Hasan; Kalkavan, Hakan

doi:10.1109/access.2020.3048016

Cited by 39 publications

(12 citation statements)

References 89 publications

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“…No single work referring to critical path in the context of Z-fuzzy numbers has been identified. On the other hand, papers referring to critical path methods for fuzzy durations modeled not only by well-known types of fuzzy numbers, but also by less common types, like hexagonal, octagonal, type-2, hesitant, intuitionistic fuzzy numbers [5][6][7][8][9][10][11][12][13][14][15] have been identified, which means that our research fits well into the current trends of research in fuzzy project modelling.…”

Section: Related Literaturesupporting

confidence: 67%

Critical Path Method for Z-fuzzy Numbers

Marchwicka

Kuchta

2021

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation

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Project critical path is one of basic notions in project management, known for many years already. Its determination is straightforward and unambiguous in case of crisp activity durations, but the problem becomes more complex when the activity durations are not known precisely and given in the form of fuzzy numbers. Numerous approaches have been proposed for the determination of the critical path in case of fuzzy activity durations. In this paper the case of activity durations given in the form of Z-fuzzy numbers will be considered for the first time. The application of Z-fuzzy numbers allows to model the credibility degree of estimations. This problem (taking into account estimators who are optimistic, pessimistic, volatile or accurate) will be analyzed and a concept and method of determining the critical path based on Z-fuzzy durations proposed. The critical path determined thanks to our approach will take into account not only the lack of "hard" information, but also human features of people involved in the estimation. The result will be thus more realistic and more useful in practical applications.

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Section: Related Literaturesupporting

confidence: 67%

Critical Path Method for Z-fuzzy Numbers

Marchwicka

Kuchta

2021

Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation

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“…In some other models, the causal impacts of the items could not be evaluated (Rahiminezhad Galankashi et al 2020;Bottani et al 2018). In addition, considering the distances to both positive and negative optimal results in the analysis process is the reason for using the TOPSIS in the analysis process (Cheng et al 2020;Haiyun et al 2021). Other models only consider the distance to the positive optimal solutions (Suganthi 2018;Bathaei et al 2019).…”

Section: Discussionmentioning

confidence: 99%

“…( 45) identifies picture fuzzy rough numbers (Jin et al 2021) 46) computes normalized values (Zhan et al 2020a, b), and a weighted normalized DMT is generated with Eq. ( 47) (Cheng et al 2020). Equations ( 48)-( 53) define the distance between the best and worst alternatives.…”

Section: Topsis and Vikor Based On Pfrssmentioning

confidence: 99%

Understanding the financial innovation priorities for renewable energy investors via QFD-based picture fuzzy and rough numbers

Yüksel

Dınçer

2022

Financ Innov

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This study evaluates financial innovation priorities for renewable energy investors by generating a novel hybrid fuzzy decision-making model. First, SERVQUAL-based customer needs for financial innovation are weighted with decision-making trial and evaluation laboratory based on picture fuzzy sets. Second, the financial innovation priorities are ranked by technique for order preference by similarity to ideal solutions based on picture fuzzy rough sets. In this process, Theory of the solution of inventive problems-based technical characteristics for financial services, the process for innovative services, and competencies for financial innovation are considered using quality function deployment phases. In addition, the Vise Kriterijumska Optimizacija I Kompromisno Resenje method is also considered for an alternative ranking. Similarly, sensitivity analysis is also performed by considering five different cases. It is determined that the ranking priorities based on the proposed model are almost identical, demonstrating the proposed model’s validity and reliability. Assurance is the most crucial factor for the customer needs regarding the financial innovation priorities for renewable energy investors. Concerning the financial innovation priorities, the product is the essential priority for financial innovation; hence, it is recommended that companies engage qualified employees to effectively design the financial innovation for renewable energy investors. Additionally, necessary training should be given to the employees who currently work in the company, which can increase the renewable energy investors’ trust in the innovative financial products. Companies should mainly focus on the product to provide better financial innovation to attract renewable energy investors. An effectively designed financial innovation product can help solve the financing problem of renewable energy investors.

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“…PVs, FCs and batteries are always disturbed by nature factors such as variation output load, grid-side faults and changes of irradiation and temperature. The designing of strong control systems to kept output voltage and power in a desired level is one of the challenging problems [1]- [4].…”

Section: Introductionmentioning

confidence: 99%

A New Immersion and Invariance Control and Stable Deep Learning Fuzzy Approach for Power/Voltage Control Problem

et al. 2022

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Background: The use of renewable energies is extended due to their valuable features such as abundant and clarity. The microgrids that include the renewable energies are widely used in various applications such as power supplying of remote areas, increasing the network reliability, reducing the greenhouse gas emission, reducing the consumption demand, eliminating the consumption peaks, and so on. But, energy management in the these systems in an challenging problem. Because, there are some natural perturbations such as variation output load, grid-side faults and changes of irradiation and temperature. Aim and Objective: The problem is to design a controller to regulate the output voltage/energy under aforementioned disturbances. Methods: The paper presents a new approach for energy management in Photovoltaic (PV)/Battery/Fuel Cells (FC) systems. The uncertainties are compensated by the new optimization rules based on Immersion and Invariance (I&I) theorem and proposed deep learning type-2 fuzzy logic compensator (T2FLC). The objective function of T2FLC is to minimize the tracking error in presence of perturbations. The adaptation rules are derived such that the I&I stabilization criterions are satisfied. Both rules and fuzzy sets (FSs) of T2FLCs are optimized by guaranteed stability rules to tackle the effect of perturbations and estimation errors. Results and Discussion: It is shown that a well voltage/energy regulation performance is achieved under variation of temperature, suddenly changes of load and variation of irradiation. A comparison with similar controllers demonstrates the superiority of the suggested approach. Conclusion: The suggested regulator do not depend on the mathematical models, and results in good accuracy under difficult conditions, then it can be used in various applications.INDEX TERMS Energy management, immersion and invariance, deep learning, fuzzy systems, voltage control, stability.• Both rules and FS parameters are optimized.• The superiority of the designed method is examined under various conditions and comparison with other conventional approaches.

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A Hybrid Hesitant 2-Tuple IVSF Decision Making Approach to Analyze PERT-Based Critical Paths of New Service Development Process for Renewable Energy Investment Projects

Cited by 39 publications

References 89 publications

Critical Path Method for Z-fuzzy Numbers

Critical Path Method for Z-fuzzy Numbers

Understanding the financial innovation priorities for renewable energy investors via QFD-based picture fuzzy and rough numbers

A New Immersion and Invariance Control and Stable Deep Learning Fuzzy Approach for Power/Voltage Control Problem

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