On General Framework of Type-1 Membership Function Construction: Case Study in QoS Planning

Miliauskaitė, Jolanta; Kalibatiene, Diana

doi:10.1007/s40815-019-00753-4

Cited by 10 publications

(2 citation statements)

References 46 publications

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“…Since quality is a vague and subjective concept, it is recommended to model and assess it by applying a fuzzy inference [36], [45]. Fuzzy controllers, such as Mamdani, Sugeno, etc., are the most widely used in practice since they provide satisfactory results with quantitative numerical data input [48].…”

Section: Introductionmentioning

confidence: 99%

An Effect of User Experience on A Data-Driven Fuzzy Inference of Web Service Quality

Miliauskaitė

Kalibatiene

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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Today, various stakeholders provide a large number of functionally similarWeb Services (WS) to meet increasingly complex business needs. Therefore, to distinguish similar WS, some researchers have proposed using the non-functional characteristics, named Quality of Service (QoS), and user’s needs, expressed through Quality of Experience (QoE). Thus, all those QoS and QoE attributes should be taken into account in predicting WS quality jointly, called WS QoSE (Quality of Service and Experience). However, these attributes are different in nature, i.e., QoS is data-driven and numerical, while QoE is expert-based and linguistic. Consequently, to predict WS QoSE, in this paper, we propose a hybrid fuzzy inference approach, composing both quantitative and qualitative data inputs into WS QoSE output by applying the adaptive neuro-fuzzy inference system (ANFIS). The developed prototype allows us to implement the proposed approach, investigate its performance, and study the effect of QoE attributes on WS QoSE. The results of the two experiments show good performance and suitability of the proposed hybrid fuzzy inference approach for predicting WS QoSE based on combining QoS and QoE attributes. We expect that those results inspire researchers and practitioners to understand the WS QoSE better and develop user needs matching WS.

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Section: Introductionmentioning

confidence: 99%

An Effect of User Experience on A Data-Driven Fuzzy Inference of Web Service Quality

Miliauskaitė

Kalibatiene

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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“…In a data-driven FIS, the underlying MFs and fuzzy rules are generated automatically from synthetic or real data streams but not defined by an expert manually (Miliauskaitė and Kalibatienė, 2020b) (Fig. 1).…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development

Kalibatiene¹,

Miliauskaitė²

2021

Informatica

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The data-driven approach is popular to automate learning of fuzzy rules and tuning membership function parameters in fuzzy inference systems (FIS) development. However, researchers highlight different challenges and issues of this FIS development because of its complexity. This paper evaluates the current state of the art of FIS development complexity issues in Computer Science, Software Engineering and Information Systems, specifically: 1) What complexity issues exist in the context of developing FIS? 2) Is it possible to systematize existing solutions of identified complexity issues? We have conducted a hybrid systematic literature review combined with a systematic mapping study that includes keyword map to address these questions. This review has identified the main FIS development complexity issues that practitioners should consider when developing FIS. The paper also proposes a framework of complexity issues and their possible solutions in FIS development.

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A dynamic fuzzification approach for interval type-2 membership function development: case study for QoS planning

Kalibatiene

Miliauskaitė

2021

Soft Comput

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On General Framework of Type-1 Membership Function Construction: Case Study in QoS Planning

Cited by 10 publications

References 46 publications

An Effect of User Experience on A Data-Driven Fuzzy Inference of Web Service Quality

An Effect of User Experience on A Data-Driven Fuzzy Inference of Web Service Quality

A Hybrid Systematic Review Approach on Complexity Issues in Data-Driven Fuzzy Inference Systems Development

A dynamic fuzzification approach for interval type-2 membership function development: case study for QoS planning

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