A holistic approach to assessment of value of information (VOI) with fuzzy data and decision criteria

Vilela, Martin J.; Oluyemi, Gbenga; Petrovski, Andrei

doi:10.31181/dmame2003097v

Cited by 10 publications

(6 citation statements)

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“…Among them, the values of csQCA and mvQCA are discrete variables while fsQCA allows for the continuous assignment of variables, which is applicable to the continuous variable of the original sample data. FsQCA can complete truth-table transformation based on fuzzy-set data [ 42 ], offering the advantages of both qualitative and quantitative analysis [ 43 ]. By screening the consistency and coverage of the configuration, fsQCA obtains the configuration with theoretical explanatory power.…”

Section: Methodsmentioning

confidence: 99%

Exploring the green development path of the Yangtze River Economic Belt using the entropy weight method and fuzzy-set qualitative comparative analysis

Yan

Hu²,

Wu³

et al. 2021

PLoS ONE

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Green development is an effective way to achieve economic growth and social development in a harmonious, sustainable, and efficient manner. Although the Yangtze River Economic Belt (YREB) plays an important strategic role in China, our understanding of its spatiotemporal characteristics, as well as the multiple factors affecting its green development level (GDL), remains limited. This study used the entropy weight method (EWM) to analyze the temporal evolution and spatial differentiation characteristics of the GDL in the YREB from 2011 to 2019. Further, fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the influence path of GDL. The results showed that the GDL of the YREB increased from 2015 to 2019, but the overall level was still not high, with high GDL mainly concentrated in the lower reaches. The GDL model changed from being environmentally driven and government supported in 2011 to being environmentally and economically driven since 2014. The core conditions for high GDL changed from economic development level (EDL) to scientific technological innovation level (STIL) and environmental regulation (ER). The path for improving GDL is as follows: In regions with high EDL, effective ER, moderate openness level (OL), and high STIL are the basis, supplemented by a reasonable urbanization scale (US). In areas with low EDL, reasonable industrial structure (IS) and STIL are the core conditions for development; further, EDL should be improved and effective ER and OL implemented. Alternatively, without considering changes to EDL, improvement can be achieved through reasonable OL and US or effective ER. This study provides a new method for exploring the path of GDL and a reference for governments to effectively adjust green development policies.

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Section: Methodsmentioning

confidence: 99%

Exploring the green development path of the Yangtze River Economic Belt using the entropy weight method and fuzzy-set qualitative comparative analysis

Yan

Hu²,

Wu³

et al. 2021

PLoS ONE

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“…These methods depend upon many different concepts used for treating uncertainty. Stochastic, fuzzy, rough, and interval models are developed for treating uncertainty through different mathematical programming problems [ 5 – 8 ]. According to the stochastic concept (e.g., [ 9 – 11 ]), the coefficients which have uncertainty are represented as random variables whose probability distributions are supposed to be given in advance as a part of the problem itself.…”

Section: Introductionmentioning

confidence: 99%

Development of an Appropriate Uncertainty Model with an Application to Solid Waste Management Planning

Elazeem

Khalifa

Pamučar

et al. 2022

Computational Intelligence and Neuroscience

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The purpose of this study is to achieve a novel and efficient method for treating the interval coefficient linear programming (ICLP) problems. The problem is used for modeling an uncertain environment that represents most real-life problems. Moreover, the optimal solution of the model represents a decision under uncertainty that has a risk of selecting the correct optimal solution that satisfies the optimality and the feasibility conditions. Therefore, a proposed algorithm is suggested for treating the ICLP problems depending on novel measures such as the optimality ratio, feasibility ratio, and the normalized risk factor. Depending upon these measures and the concept of possible scenarios, a novel and effective analysis of the problem is done. Unlike other algorithms, the proposed algorithm involves an important role for the decision-maker (DM) in defining a satisfied optimal solution by using a utility function and other required parameters. Numerical examples are used for comparing and illustrating the robustness of the proposed algorithm. Finally, applying the algorithm to treat a Solid Waste Management Planning is introduced.

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“…To construct a crowd-sensitive path planner based on smart cost map is a special challenge. In [40] it is presented approach based on learning the cost map that best defines previously observed motion and trajectories of pedestrians. This approach uses a cost map at the beginning of the process that ignores predictions of future pedestrian locations.…”

Section: Related Workmentioning

confidence: 99%

“…Fuzzy logic techniques are efficient in solving complex, ill-defined problems that are characterized by uncertainty of environment and fuzziness of information [36,37]. Taking into account that disturbances and noises are common sources of uncertainties, it can be concluded that from the aspect of fuzzy implementation this system is highly resistant to noise and disturbance [38,39,40]. The fuzzy membership functions for the input linguistic variables, as well as the output linguistic variable are given in Figure 6.…”

Section: Fuzzy Inference Systemmentioning

confidence: 99%

Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning

Zagradjanin

Rodić

Pamučar

et al. 2021

ITC

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This paper considers an autonomous cloud-based multi-robot system designed to execute highly repetitive tasksin a dynamic environment such as a modern megastore. Cloud level is intended for performing the most demandingoperations in order to unload the robots that are users of cloud services in this architecture. For path planningon global level D* Lite algorithm is applied, bearing in mind its high efficiency in dynamic environments. In orderto introduce smart cost map for further improvement of path planning in complex and crowded environment, implementationof fuzzy inference system and learning algorithm is proposed. The results indicate the possibility ofapplying a similar concept in different real-world robotics applications, in order to reduce the total paths length,as well as to minimize the risk in path planning related to the human-robot interactions.

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A holistic approach to assessment of value of information (VOI) with fuzzy data and decision criteria

Cited by 10 publications

References 0 publications

Exploring the green development path of the Yangtze River Economic Belt using the entropy weight method and fuzzy-set qualitative comparative analysis

Exploring the green development path of the Yangtze River Economic Belt using the entropy weight method and fuzzy-set qualitative comparative analysis

Development of an Appropriate Uncertainty Model with an Application to Solid Waste Management Planning

Cloud-Based Multi-Robot Path Planning in Complex and Crowded Environment Using Fuzzy Logic and Online Learning

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