Deriving pertinent systems requirements : a methodology

10.32920/ryerson.14652210 ◽

2021 ◽

Author(s):

Swapan Sikdar

Keyword(s):

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Early Stage ◽

Owa Operators ◽

Fuzzy Aggregation ◽

Project Failures ◽

Human Thinking ◽

Systems Requirements ◽

Requirements Development

Poor understanding of needs results in incompletely captured requirements and causes project failures. Analysts and developers by training, practice preoccupation and lacking suitable methodologies are ill equipped to capture various dimensions of requirements. In early stages needs are vaguely expressed. They have to be extracted and reasoned with stakeholders using relevant vocabulary. Business reality limits time at stakeholders' disposal to participate in requirements development. Methodologies that are more workable are required. Working with early stage goal oriented concepts from Goal Oriented Requirements Engineering (GORE) and fuzzy set theory based value aggregation, this thesis proposes a methodology to develop and select pertinent requirements. We use GORE concepts for identifying requirements and fuzzy aggregation to select alternatives. Use of fuzzy set theory and Ordered Weighted Aggregation (OWA) operators allows quantitative structuring of early stage decision problem consistent with human thinking and reasoning. The methodology is illustrated via two case studies.

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Fuzzy set theory based methodology for the analysis of measurement uncertainties in river discharge and stage

Canadian Journal of Civil Engineering ◽

10.1139/l09-151 ◽

2010 ◽

Vol 37 (3) ◽

pp. 429-440 ◽

Cited By ~ 7

Author(s):

Rajesh R. Shrestha ◽

Slobodan P. Simonovic

Keyword(s):

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Velocity Measurement ◽

Discharge Measurement ◽

Sources Of Uncertainty ◽

Fuzzy Aggregation ◽

Combined Uncertainty ◽

Discharge Measurements

The discharge and stage measurements in a river system are characterized by a number of sources of uncertainty, which affects the accuracy of a rating curve established from measurements. This paper presents a fuzzy set theory based methodology for consideration of different sources of uncertainty in the stage and discharge measurements and their aggregation into a combined uncertainty. The uncertainty in individual measurements of stage and discharge is represented using triangular fuzzy numbers, and their spread is determined according to the International Organization for Standardization (ISO) standard 748 guidelines. The extension principle based fuzzy arithmetic is used for the aggregation of various uncertainties into overall stage–discharge measurement uncertainty. In addition, a fuzzified form of ISO 748 formulation is used for the calculation of combined uncertainty and comparison with the fuzzy aggregation method. The methodology developed in this paper is illustrated with a case study of the Thompson River near Spences Bridge in British Columbia, Canada. The results of the case study show that the selection of number of velocity measurement points on a vertical is the largest source of uncertainty in discharge measurement. An increase in the number of velocity measurement points provides the most effective reduction in the overall uncertainty. The next most important source of uncertainty for the case study location is the number of verticals used for velocity measurements. The study also shows that fuzzy set theory provides a suitable methodology for the uncertainty analysis of stage–discharge measurements.

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Fuzzy Modeling Techniques in Human Factors Research

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128402800501 ◽

1984 ◽

Vol 28 (5) ◽

pp. 403-407 ◽

Cited By ~ 2

Author(s):

Waldemar Karwowski ◽

Gerald W. Evans ◽

R. R. Ragade

Keyword(s):

Human Factors ◽

Fuzzy Sets ◽

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Fuzzy Modeling ◽

Modeling Techniques ◽

Potential Applications ◽

Human Thinking ◽

Human Factors Research

Traditional techniques applied in the analysis of human-centered systems fail to recognize the human- and system-based uncertainties due to imprecision and vagueness of human thinking. A new methodology is needed to cope with ill-defined relationships between people, their machines and environments. The purpose of this paper is to introduce the concept of fuzziness, and to identify the potential applications of fuzzy set theory in the area of human factors. Examples of recent and ongoing studies on the relevant application of fuzzy sets in this area are also given.

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Decision Making Methods Based on Fuzzy Aggregation Operators: Three Decades Review from 1986 to 2017

International Journal of Information Technology & Decision Making ◽

10.1142/s021962201830001x ◽

2018 ◽

Vol 17 (02) ◽

pp. 391-466 ◽

Cited By ~ 45

Author(s):

Abbas Mardani ◽

Mehrbakhsh Nilashi ◽

Edmundas Kazimieras Zavadskas ◽

Siti Rahmah Awang ◽

Habib Zare ◽

...

Keyword(s):

Decision Making ◽

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Operator Theory ◽

Real Life ◽

Aggregation Operator ◽

Aggregation Operators ◽

Weighted Averaging ◽

Fuzzy Aggregation

In many real-life decision making (DM) situations, the available information is vague or imprecise. To adequately solve decision problems with vague or imprecise information, fuzzy set theory and aggregation operator theory have become powerful tools. In last three decades, DM theories and methods under fuzzy aggregation operator have been proposed and developed for effectively solving the DM problems and numerous applications have been reported in the literature. While various aggregation operators have been suggested and developed, there is a lack of research regarding systematic literature review and classification of study in this field. Regarding this, Web of Science database has been nominated and systematic and meta-analysis method called “PRISMA” has been proposed. Accordingly, a review of 312 published articles appearing in 33 popular journals related to fuzzy set theory, aggregation operator theory and DM approaches between July 1986 and June 2017 have been attained to reach a comprehensive review of DM methods and aggregation operator environment. Consequently, the selected published articles have been categorized by name of author(s), the publication year, technique, application area, country, research contribution and journals in which they appeared. The findings of this study found that, ordered weighted averaging (OWA) has been the highest frequently accessed more than other areas. This systematic review shows that the DM theories under fuzzy aggregation operator environment have received a great deal of interest from researchers and practitioners in many disciplines.

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Multi-Attribute Multi-Perception Decision-Making Based on Generalized T-Spherical Fuzzy Weighted Aggregation Operators on Neutrosophic Sets

Mathematics ◽

10.3390/math7090780 ◽

2019 ◽

Vol 7 (9) ◽

pp. 780 ◽

Cited By ~ 11

Author(s):

Quek ◽

Selvachandran ◽

Munir ◽

Mahmood ◽

Ullah ◽

...

Keyword(s):

Decision Making ◽

Set Theory ◽

Fuzzy Set ◽

Fuzzy Set Theory ◽

Aggregation Operators ◽

Neutrosophic Sets ◽

Operational Laws ◽

Fuzzy Aggregation ◽

Multi Attribute Decision Making ◽

Do So

The framework of the T-spherical fuzzy set is a recent development in fuzzy set theory that can describe imprecise events using four types of membership grades with no restrictions. The purpose of this manuscript is to point out the limitations of the existing intuitionistic fuzzy Einstein averaging and geometric operators and to develop some improved Einstein aggregation operators. To do so, first some new operational laws were developed for T-spherical fuzzy sets and their properties were investigated. Based on these new operations, two types of Einstein aggregation operators are proposed namely the Einstein interactive averaging aggregation operators and the Einstein interactive geometric aggregation operators. The properties of the newly developed aggregation operators were then investigated and verified. The T-spherical fuzzy aggregation operators were then applied to a multi-attribute decision making (MADM) problem related to the degree of pollution of five major cities in China. Actual datasets sourced from the UCI Machine Learning Repository were used for this purpose. A detailed study was done to determine the most and least polluted city for different perceptions for different situations. Several compliance tests were then outlined to test and verify the accuracy of the results obtained via our proposed decision-making algorithm. It was proved that the results obtained via our proposed decision-making algorithm was fully compliant with all the tests that were outlined, thereby confirming the accuracy of the results obtained via our proposed method.

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