scholarly journals Fuzzy linguistic in geometric modeling

2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohd Sallehuddin Husain ◽  
Abd Fatah Wahab ◽  
R.U. Gobithasaan
Keyword(s):  
Set Theory ◽  
Fuzzy Set Theory ◽  
Geometric Modeling ◽  
Control Point ◽  
Control Points ◽  
Linguistic Variables ◽  
Numerical Examples ◽  
Basic Functions ◽  
Linguistic Control ◽  
Fuzzy Linguistic

Fuzzy Linguistic is an extension of fuzzy set theory was introduced by Zadeh. Normally fuzzy linguistic is often associated with linguistic variables generated by a function modifier is also known as a hedges. This paper discusses the theorems and definitions of fuzzy linguistic perspective geometric modeling to produce Fuzzy Linguistic Control Point (FLCP). Fuzzy Linguistic Control Points have been blended in with the spline basic functions of the model to produce a few splines’s model are characterized by fuzzy linguistics. At the end of this article will discuss some numerical examples of Fuzzy Linguistic Bezier Model. 

scholarly journals Application of Fuzzy DEMATEL in Risks Evaluation of Knowledge-Based Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
M. Abbasi ◽  
R. Hosnavi ◽  
B. Tabrizi
Keyword(s):  
Risk Factors ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
New Products ◽  
Linguistic Variables ◽  
Fuzzy Dematel ◽  
Knowledge Based ◽  
Wide Range ◽  
Do So

Developing new products has received much attention within the last decades. This issue can be highlighted for strategic innovations, in particular. Recently, knowledge-based networks have been introduced in order to facilitate the affair of transforming knowledge into commercial products which can be regarded as a set of research centers, universities, knowledge intermediaries, customers, and so forth. However, there is a wide range of risk factors that are liable to affect the chain performance. Hence, this paper aims to consider the most influencing criteria that can play a more significant role in achievements of such networks. To do so, DEMATEL has been applied to take the relationships between the risk factors into account. Moreover, fuzzy set theory has been utilized in order to deal with the linguistic variables. Finally, the most important factors are identified and their relations are determined.

Stability Failure Analysis in the Operations of Floating Dry Docks

2017 ◽  
Vol Vol 159 (A1) ◽  
Author(s):  
D A Njumo
Keyword(s):  
Failure Analysis ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Evidential Reasoning ◽  
Linguistic Variables ◽  
Main Area ◽  
Failure Data ◽  
Dry Dock

The main area of this work reflects a topic for which there is little or limited reference available and is carried out to meet the needs of professional and practical floating dry dock operators. The risk of hazards in floating dry docks is evaluated using a discrete fuzzy set theory (FST) and an evidential reasoning (ER) approach in a situation where historical failure data is not available. Fuzzy set modelling is used to estimate the safety levels of the causes of basic failure events in floating dry docks due to stability concerns using the concept of linguistic variables, and provides a framework for dealing with such variables in a systematic way. The ER approach is used to synthesise the estimated safety levels of the causes of hazards/basic hazard events. The results of this work will be valuable to dry dock masters and sister maritime engineering professionals.

scholarly journals A FUZZY MODEL FOR AN INCREASE IN LOCOMOTIVE TRACTION FORCE

Transport ◽  
2010 ◽  
Vol 25 (1) ◽  
pp. 36-45 ◽  
Author(s):  
Marko Djukić ◽  
Srdjan Rusov ◽  
Zoran Mitrović
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Optimization Model ◽  
Mechanical Model ◽  
Fuzzy Controller ◽  
Fuzzy Model ◽  
Traction Force ◽  
Numerical Examples

This paper deals with the process of traction force realization described by a suitable mechanical model and is pointed to the adhesion phenomenon as a physical one, i.e. is a suitable factor that the value of traction force depends on. The model for the process of optimizing locomotive traction force based on using the fuzzy set theory is explained. The projecting process of a fuzzy controller regulating the value of skidding and the value of traction torque by increasing the value of traction force that can be realized according to adhesion conditions is described. Finally, testing the optimization model in several numerical examples under specific conditions of wheel-rail adhesion is done.

STABILITY FAILURE ANALYSIS IN THE OPERATIONS OF FLOATING DRY DOCKS

2021 ◽  
Vol 159 (A1) ◽  
Author(s):  
D A Njumo
Keyword(s):  
Failure Analysis ◽  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Evidential Reasoning ◽  
Linguistic Variables ◽  
Main Area ◽  
Failure Data ◽  
Dry Dock

The main area of this work reflects a topic for which there is little or limited reference available and is carried out to meet the needs of professional and practical floating dry dock operators. The risk of hazards in floating dry docks is evaluated using a discrete fuzzy set theory (FST) and an evidential reasoning (ER) approach in a situation where historical failure data is not available. Fuzzy set modelling is used to estimate the safety levels of the causes of basic failure events in floating dry docks due to stability concerns using the concept of linguistic variables, and provides a framework for dealing with such variables in a systematic way. The ER approach is used to synthesise the estimated safety levels of the causes of hazards/basic hazard events. The results of this work will be valuable to dry dock masters and sister maritime engineering professionals.

scholarly journals Generalized dice similarity measures for complex q-Rung Orthopair fuzzy sets and its application

2020 ◽  
Author(s):  
Harish Garg ◽  
Zeeshan Ali ◽  
Tahir Mahmood
Keyword(s):  
Set Theory ◽  
Fuzzy Set ◽  
Fuzzy Set Theory ◽  
Intuitionistic Fuzzy Set ◽  
Similarity Measures ◽  
Membership Degree ◽  
Pythagorean Fuzzy Set ◽  
Numerical Examples ◽  
Medical Diagnoses ◽  
Special Cases

AbstractComplex q-rung orthopair fuzzy set (Cq-ROFS) is an extension of Complex fuzzy set, intuitionistic fuzzy set, Pythagorean fuzzy set, to cope with complicated and inconsistence information in the environment of fuzzy set theory with a wider domain. In Cq-ROFS, each attribute is characterized by the degree of membership and non-membership degree over the unit-disc of the complex plan. Keeping the advantages of Cq-ROFSs, in this manuscript, we present a concept of the dice similarity and generalized dice similarity measures between the pairs of the sets. The basic axioms and properties are also stated. Further, we extend the proposed measures to weighted dice similarity measures and investigated their properties. The certain properties and the special cases of the proposed work are also derived. The applicability of the proposed measures is demonstrated with some numerical examples related to medical diagnoses and pattern recognition. The superiority and advantages of the measures over the existing ones are also illustrated with certain numerical examples.

scholarly journals AN INITIATIVE FOR CONSTRUCTION OF NEW-GENERATION LUNAR GLOBAL CONTROL NETWORK USING MULTI-MISSION DATA

2017 ◽  
Vol XLII-3/W1 ◽  
pp. 29-34 ◽  
Author(s):  
K. Di ◽  
B. Liu ◽  
M. Peng ◽  
X. Xin ◽  
M. Jia ◽  
...  
Keyword(s):  
Geometric Modeling ◽  
Large Scale ◽  
Control Point ◽  
Remote Sensing Data ◽  
Control Network ◽  
Control Points ◽  
Lunar Laser Ranging ◽  
Global Control ◽  
New Generation ◽  
Absolute Control

A lunar global control network provides geodetic datum and control points for mapping of the lunar surface. The widely used Unified Lunar Control Network 2005 (ULCN2005) was built based on a combined photogrammetric solution of Clementine images acquired in 1994 and earlier photographic data. In this research, we propose an initiative for construction of a new-generation lunar global control network using multi-mission data newly acquired in the 21<sup>st</sup> century, which have much better resolution and precision than the old data acquired in the last century. The new control network will be based on a combined photogrammetric solution of an extended global image and laser altimetry network. The five lunar laser ranging retro-reflectors, which can be identified in LROC NAC images and have cm level 3D position accuracy, will be used as absolute control points in the least squares photogrammetric adjustment. Recently, a new radio total phase ranging method has been developed and used for high-precision positioning of Chang’e-3 lander; this shall offer a new absolute control point. Systematic methods and key techniques will be developed or enhanced, including rigorous and generic geometric modeling of orbital images, multi-scale feature extraction and matching among heterogeneous multi-mission remote sensing data, optimal selection of images at areas of multiple image coverages, and large-scale adjustment computation, etc. Based on the high-resolution new datasets and developed new techniques, the new generation of global control network is expected to have much higher accuracy and point density than the ULCN2005.

scholarly journals Intuitionistic fuzzy in spline curve/surface

2015 ◽  
Vol 11 (1) ◽  
Author(s):  
Abd Fatah Wahab ◽  
Mohammad Izat Emir Zulkifly
Keyword(s):  
Geometric Modeling ◽  
Boundary Value ◽  
Curve Surface ◽  
Fuzzy Data ◽  
Control Points ◽  
New Model ◽  
Spline Curve ◽  
Intuitionistic Fuzzy ◽  
Data Problem ◽  
Basic Functions

The uncertainty data problem with intuitionistic information is difficult to deal with through the methodology or approach available. This is because the existing fuzzy geometric modeling can only solve the fuzzy data problem that is  intuitionistic and fuzzy complex in nature as the data have information that is incomplete boundary value (less clear and ambiguous), have meaning and truth value of the range, a lot of value logic values as well as having vague distribution and indistinct. Furthermore, the operation is characteristically minimum or maximum and image together with the range are obscure and complex. To solve this problem, a new model with a redefinition of the control points which   characterized by three important components of intuitionistic fuzzy is developed. These control points will be blended with the basic functions of spline to generate several models in the form of intuitionistic fuzzy spline curve / surface and can be easily understood. With the intuitionistic concept and its relations, then the relevant data can be translated through the production of these models.

On Objective-Based Roughc-Regression

2015 ◽  
Vol 19 (1) ◽  
pp. 36-42
Author(s):  
Akira Sugawara ◽  
◽  
Yasunori Endo ◽  
Naohiko Kinoshita ◽  
Keyword(s):  
Pattern Recognition ◽  
Set Theory ◽  
Rough Set ◽  
Fuzzy Set Theory ◽  
Clustering Algorithm ◽  
Rough Set Theory ◽  
Pattern Recognition Method ◽  
Clustering Methods ◽  
Recognition Method ◽  
Numerical Examples

The pattern recognition method of clustering is a technique automatically classifying data into clusters. Among clustering methods,c-regression based on fuzzy set theory, called Fuzzyc-Regression (FCR), is proposed to get a linear dataset structure. The most recent clustering is based on rough set theory called rough clustering, which is less descriptive than fuzzy clustering. A typical rough clustering algorithm is Roughk-Regression (RKR). However, RKR has problems because it depends on initial values and has no optimum index, so we do not know whether a clustering result will be optimal. This paper proposes Roughc-Regression (RCR) based on the optimization of an objective function and demonstrates its effectiveness through numerical examples.

scholarly journals Cubic q-rung orthopair fuzzy linguistic set and their application to multi-attribute decision making with Muirhead mean operator

2020 ◽  
Author(s):  
Harish Garg ◽  
Tahir Mahmood ◽  
Jabbar Ahmmad ◽  
Qaisar Khan ◽  
Zeeshan Ali
Keyword(s):  
Decision Making ◽  
Fuzzy Set ◽  
The Other ◽  
Linguistic Variables ◽  
Qualitative Information ◽  
Numerical Examples ◽  
Other Hand ◽  
Multi Attribute Decision Making ◽  
Fuzzy Linguistic

The objective of the paper is to present a new concept named as Cubic q-rung orthopair fuzzy linguistic set (Cq-ROFLS) to quantify the uncertainty in the information. The proposed Cq-ROFLS is qualitative form of cubic q-rung orthopair fuzzy set (Cq-ROFS), where membership degrees (MDs) and non-membership degrees (NMDs) are represented in terms of linguistic variables. The basic notions of Cq-ROFLS have been introduced and study their basic operations and properties. Further, to aggregate the different pairs of the preferences, we introduce the Cq-ROFL Muirhead mean, weighted Muirhead mean, dual Muirhead mean based operators. The major advantages of considering the Muirhead mean is that it considers the interrelationship between more than two arguments at a time. On the other hand, the Cq-ROFLS has the ability to describe the qualitative information in terms of linguistic variables. Several properties and relation of the derived operators are argued. Besides, we also investigate multi attribute decision making (MADM) problems under the Cq-ROFLS environment and illustrate with a numerical examples. Finally, the effectiveness and advantages of the work are established by comparing with other methods.

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