Data modeling and querying with fuzzy sets: A systematic survey

Ma, Zongmin; Li, Yan

doi:10.1016/j.fss.2022.01.006

Cited by 11 publications

(3 citation statements)

References 216 publications

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“…A concept representing fuzziness as a quantitative number is denoted as a fuzzy set. 55,56 Thus, a fuzzy set is usually denoted by a membership function that can have any value of membership between complete membership (1) and non-membership. 57 A fuzzy set's mathematical interpretation can be illustrated as follows:…”

Section: Fuzzy Set Conceptmentioning

confidence: 99%

Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

Kumar,

Nadeem,

Shameem

2023

J Software Evolu Process

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Increasingly, software organizations are implementing DevOps culture to benefit from it in terms of continuous testing, delivery, improvement, and so forth. Implementing DevOps is difficult due to a lack of understanding about the practices and their effective application for its effective implementation. This paper aims to explore different DevOps practices that can be implemented in software organizations. The study involves conducting a systematic literature review (SLR) to identify DevOps implementation practices, followed by the utilization of the fuzzy best–worst method (FBWM) to establish a taxonomy or classification of software practices. We have used an SLR to investigate the practices, and subsequently, the survey method was followed to validate the identified practices. Moreover, the best–worst method (BWM) was considered to evaluate the significance and develop the taxonomy of the practices. The results of this study extracted 19 practices that have been identified in the SLR process. The identified factors are further classified into six core DevOps lifecycle phases. The results of the BWM approach are shown. The outcomes of the study conclude that the proposed taxonomy of the practices could help DevOps practitioners and researchers effectively implement them in software development organizations.

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Section: Fuzzy Set Conceptmentioning

confidence: 99%

Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

Kumar,

Nadeem,

Shameem

2023

J Software Evolu Process

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“…Epistemic uncertainty is related to the inability to obtain systematic accurate probability information owing to a lack of information. To efectively describe epistemic uncertainty, many epistemic uncertainty models have been developed in recent years, primarily including the convex model [9,10], fuzzy model [11], interval model [12,13], and evidence theory model [14,15]. Among these epistemic uncertainty models, the evidence theory model can reasonably describe and process various inaccurate probabilistic information, unreliable information, and even conficting information, possessing more powerful processing capabilities than other models [16].…”

Section: Introductionmentioning

confidence: 99%

Reduced Space Optimization‐Based Evidence Theory Method for Response Analysis of Space‐Coiled Acoustic Metamaterials with Epistemic Uncertainty

Yin

Chen

Qin

2023

Mathematical Problems in Engineering

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Acoustic metamaterials have been widely concerned by researchers because of their excellent sound absorption properties. Traditional uncertainty analysis methods for response analysis of acoustic metamaterials with evidence variables have limitations. The excessive time spent on repetitive extreme analysis of focal elements severely impedes the practical application of evidence theory. To reduce the computational costs of uncertainty quantification for acoustic metamaterials under the evidence theory, a reduced space optimization-based evidence theory method (RSO-ETM) is proposed. In RSO-ETM, a simplified surrogate model is first constructed by a modified adaptive arbitrary orthogonal polynomial (MAAOP) expansion method, and then, the monotonicity of the response surface is examined to reduce the space. Subsequently, the Newton iteration technique and a transformation boundary method are used to obtain the extreme points in the reduced space, through which the boundary of the response over each focal element can be readily obtained. By using RSO-ETM, the optimization for each focal element can be avoided, and correspondingly the computational costs are reduced. Two mathematical examples and acoustic problems are employed to demonstrate the practicality of the methods.

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“…The "fuzzy set theory (FST)" invented by Zadeh [25] has successfully been employed in varied areas and has demonstrated its powerful ability to deal with vague and uncertain information. In the literature, several doctrines and principles have been studied on FST [26][27][28]. Furthermore, Atanassov [29] extended the FST to an "intuitionistic fuzzy set (IFS)", which deals with uncertain and ambiguous information more accurately.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Intuitionistic Fuzzy-MEREC-RS-DNMA Method for Assessing the Alternative Fuel Vehicles with Sustainability Perspectives

Hezam

Mishra²,

Rani³

et al. 2022

Sustainability

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Alternative fuel vehicles (AFVs) offer opportunities to lower fuel costs as well as to reduce greenhouse gas emissions, and, therefore, they are a feasible option for customers in the market. Due to technological advancements, decisions about suitable alternative fuel vehicles are a challenging problem for fleet operators. This paper aims to introduce a multi-attribute decision-analysis framework to rank and select the “alternative fuel vehicles (AFVs)” for a private home healthcare service provider in Chandigarh, India. The selection of AFVs can be treated as a decision-making problem, because of the presence of various qualitative and quantitative attributes. Thus, the current work introduces an integrated decision-making framework based on intuitionistic fuzzy-“method based on the removal effects of criteria (MEREC)”, “ranking sum (RS)”, and the “double normalization-based multi-aggregation (DNMA)” framework for assessing the AFVs. The combination of MEREC and RS is applied to assess the objective and subjective weighting values of various parameters for AFV assessment. The DNMA approach is utilized to prioritize the different AFVs over various significant parameters. According to the outcomes, the most significant parameters for AFV assessment are social benefits, fueling/charging infrastructure, and financial incentives, respectively. In this context, globally existing AFVs for the sustainable transportation sector are identified, and then prioritized against fifteen different criteria relevant to the environmental, economic, technological, social, and political aspects of sustainability. It is distinguished that electric vehicles (G2), hybrid electric vehicles (G1), and hydrogen vehicles (G3) achieve higher overall performance compared to the other technologies available in India. The assessment outcomes prove that electric vehicles can serve as a valuable alternative for decreasing carbon emissions and negative effects on the environment. This technology contributes to transportation sector development and job creation in less developed areas of the country. Moreover, a comparison with existing studies and a sensitivity investigation are conferred to reveal the robustness and stability of the developed framework.

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Data modeling and querying with fuzzy sets: A systematic survey

Cited by 11 publications

References 216 publications

Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

Multicriteria decision‐making–based framework for implementing DevOps practices: A fuzzy best–worst approach

Reduced Space Optimization‐Based Evidence Theory Method for Response Analysis of Space‐Coiled Acoustic Metamaterials with Epistemic Uncertainty

A Hybrid Intuitionistic Fuzzy-MEREC-RS-DNMA Method for Assessing the Alternative Fuel Vehicles with Sustainability Perspectives

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