Abstract: In its attempt to offer new ways into autonomy for a
large population of disabled people, assistive technology has largely
been inspired by robotics engineering. Recent human-like robots
carry new hopes that it seems to us necessary to analyze by means of
a specific theory of anthropomorphism. We propose to distinguish a
functional anthropomorphism which is the one of actual wheelchairs
from a structural anthropomorphism based on a mimicking of human
physiological systems. If functional anthropomorphism offers the
main advantage of eliminating the physiological systems
interdependence issue, the highly link between the robot for disabled
people and their human-built environment would lead to privilege in
the future the anthropomorphic structural way. In this future
framework, we highlight a general interdependence principle : any
partial or local structural anthropomorphism generates new
anthropomorphic needs due to the physiological systems
interdependency, whose effects can be evaluated by means of
specific anthropomorphic criterions derived from a set theory-based
approach of physiological systems.
Abstract: Recently, X. Ge and J. Qian investigated some relations between higher mathematics scores and calculus scores (resp. linear algebra scores, probability statistics scores) for Chinese university students. Based on rough-set theory, they established an information system S = (U,CuD,V, f). In this information system, higher mathematics score was taken as a decision attribute and calculus score, linear algebra score, probability statistics score were taken as condition attributes. They investigated importance of each condition attribute with respective to decision attribute and strength of each condition attribute supporting decision attribute. In this paper, we give further investigations for this issue. Based on the above information system S = (U, CU D, V, f), we analyze the decision rules between condition and decision granules. For each x E U, we obtain support (resp. strength, certainty factor, coverage factor) of the decision rule C —>x D, where C —>x D is the decision rule induced by x in S = (U, CU D, V, f). Results of this paper gives new analysis of on higher mathematics scores for Chinese university students, which can further lead Chinese university students to raise higher mathematics scores in Chinese graduate student entrance examination.
Abstract: This paper applies fuzzy set theory to evaluate the
service quality of online auction. Service quality is a composition of
various criteria. Among them many intangible attributes are difficult
to measure. This characteristic introduces the obstacles for respondent
in replying to the survey. So as to overcome this problem, we
invite fuzzy set theory into the measurement of performance. By
using AHP in obtaining criteria and TOPSIS in ranking, we found
the most concerned dimension of service quality is Transaction
Safety Mechanism and the least is Charge Item. Regarding to the
most concerned attributes are information security, accuracy and
information.
Abstract: Based on the fuzzy set theory this work develops two
adaptations of iterative methods that solve mathematical programming
problems with uncertainties in the objective function and in
the set of constraints. The first one uses the approach proposed by
Zimmermann to fuzzy linear programming problems as a basis and
the second one obtains cut levels and later maximizes the membership
function of fuzzy decision making using the bound search method.
We outline similarities between the two iterative methods studied.
Selected examples from the literature are presented to validate the
efficiency of the methods addressed.
Abstract: One of the main processes of supply chain
management is supplier selection process which its accurate
implementation can dramatically increase company competitiveness.
In presented article model developed based on the features of
second tiers suppliers and four scenarios are predicted in order to
help the decision maker (DM) in making up his/her mind. In addition
two tiers of suppliers have been considered as a chain of suppliers.
Then the proposed approach is solved by a method combined of
concepts of fuzzy set theory (FST) and linear programming (LP)
which has been nourished by real data extracted from an engineering
design and supplying parts company. At the end results reveal the
high importance of considering second tier suppliers features as
criteria for selecting the best supplier.
Abstract: Fuzzy linear programming is an application of fuzzy set theory in linear decision making problems and most of these problems are related to linear programming with fuzzy variables. A convenient method for solving these problems is based on using of auxiliary problem. In this paper a new method for solving fuzzy variable linear programming problems directly using linear ranking functions is proposed. This method uses simplex tableau which is used for solving linear programming problems in crisp environment before.
Abstract: In conventional reliability assessment, the reliability data of system components are treated as crisp values. The collected data have some uncertainties due to errors by human beings/machines or any other sources. These uncertainty factors will limit the understanding of system component failure due to the reason of incomplete data. In these situations, we need to generalize classical methods to fuzzy environment for studying and analyzing the systems of interest. Fuzzy set theory has been proposed to handle such vagueness by generalizing the notion of membership in a set. Essentially, in a Fuzzy Set (FS) each element is associated with a point-value selected from the unit interval [0, 1], which is termed as the grade of membership in the set. A Vague Set (VS), as well as an Intuitionistic Fuzzy Set (IFS), is a further generalization of an FS. Instead of using point-based membership as in FS, interval-based membership is used in VS. The interval-based membership in VS is more expressive in capturing vagueness of data. In the present paper, vague set theory coupled with conventional Lambda-Tau method is presented for reliability analysis of repairable systems. The methodology uses Petri nets (PN) to model the system instead of fault tree because it allows efficient simultaneous generation of minimal cuts and path sets. The presented method is illustrated with the press unit of the paper mill.
Abstract: The fuzzy set theory has been applied in many fields,
such as operations research, control theory, and management
sciences, etc. In particular, an application of this theory in decision
making problems is linear programming problems with fuzzy
numbers. In this study, we present a new method for solving fuzzy
number linear programming problems, by use of linear ranking
function. In fact, our method is similar to simplex method that was
used for solving linear programming problems in crisp environment
before.
Abstract: This paper is to develop a fuzzy net present value (FNPV) method by taking vague cash flow and imprecise required rate of return into account for evaluating the value of the Build-Operate-Transfer (BOT) sport facilities. In order to clearly manifest a more realistic capital budgeting model based on the classical net present value (NPV) method, some uncertain financial elements in NPV formula will be fuzzified as triangular fuzzy numbers. Through the conscientious manipulation of fuzzy set theory, we will find that the proposed FNPV model is a more explicit extension of classical (crisp) model and could be more practicable for the financial managers to capture the essence of capital budgeting of sport facilities than non-fuzzy model.
Abstract: This paper applies fuzzy AHP to evaluate the service
quality of online auction. Service quality is a composition of various
criteria. Among them many intangible attributes are difficult to
measure. This characteristic introduces the obstacles for respondents
on reply in the survey. So as to overcome this problem, we invite
fuzzy set theory into the measurement of performance and use AHP in
obtaining criteria. We found the most concerned dimension of service
quality is Transaction Safety Mechanism and the least is Charge Item.
Other criteria such as information security, accuracy and information
are too vital.
Abstract: With the enormous growth on the web, users get easily
lost in the rich hyper structure. Thus developing user friendly and
automated tools for providing relevant information without any
redundant links to the users to cater to their needs is the primary task
for the website owners. Most of the existing web mining algorithms
have concentrated on finding frequent patterns while neglecting the
less frequent one that are likely to contain the outlying data such as
noise, irrelevant and redundant data. This paper proposes new
algorithm for mining the web content by detecting the redundant
links from the web documents using set theoretical(classical
mathematics) such as subset, union, intersection etc,. Then the
redundant links is removed from the original web content to get the
required information by the user..
Abstract: Probabilistic techniques in computer programs are becoming
more and more widely used. Therefore, there is a big
interest in the formal specification, verification, and development
of probabilistic programs. In our work-in-progress project, we are
attempting to make a constructive framework for developing probabilistic
programs formally. The main contribution of this paper
is to introduce an intermediate artifact of our work, a Z-based
formalism called PZ, by which one can build set theoretical models of
probabilistic programs. We propose to use a constructive set theory,
called CZ set theory, to interpret the specifications written in PZ.
Since CZ has an interpretation in Martin-L¨of-s theory of types, this
idea enables us to derive probabilistic programs from correctness
proofs of their PZ specifications.
Abstract: Morphological operators transform the original image
into another image through the interaction with the other image of
certain shape and size which is known as the structure element.
Mathematical morphology provides a systematic approach to analyze
the geometric characteristics of signals or images, and has been
applied widely too many applications such as edge detection,
objection segmentation, noise suppression and so on. Fuzzy
Mathematical Morphology aims to extend the binary morphological
operators to grey-level images. In order to define the basic
morphological operations such as fuzzy erosion, dilation, opening
and closing, a general method based upon fuzzy implication and
inclusion grade operators is introduced. The fuzzy morphological
operations extend the ordinary morphological operations by using
fuzzy sets where for fuzzy sets, the union operation is replaced by a
maximum operation, and the intersection operation is replaced by a
minimum operation.
In this work, it consists of two articles. In the first one, fuzzy set
theory, fuzzy Mathematical morphology which is based on fuzzy
logic and fuzzy set theory; fuzzy Mathematical operations and their
properties will be studied in details. As a second part, the application
of fuzziness in Mathematical morphology in practical work such as
image processing will be discussed with the illustration problems.
Abstract: Sensors possess several properties of physical
measures. Whether devices that convert a sensed signal into an
electrical signal, chemical sensors and biosensors, thus all these
sensors can be considered as an interface between the physical and
electrical equipment. The problem is the analysis of the multitudes of
saved settings as input variables. However, they do not all have the
same level of influence on the outputs. In order to identify the most
sensitive parameters, those that can guide users in gathering
information on the ground and in the process of model calibration
and sensitivity analysis for the effect of each change made.
Mathematical models used for processing become very complex.
In this paper a fuzzy rule-based system is proposed as a solution
for this problem. The system collects the available signals
information from sensors. Moreover, the system allows the study of
the influence of the various factors that take part in the decision
system. Since its inception fuzzy set theory has been regarded as a
formalism suitable to deal with the imprecision intrinsic to many
problems. At the same time, fuzzy sets allow to use symbolic models.
In this study an example was applied for resolving variety of
physiological parameters that define human health state. The
application system was done for medical diagnosis help. The inputs
are the signals expressed the cardiovascular system parameters, blood
pressure, Respiratory system paramsystem was done, it will be able
to predict the state of patient according any input values.
Abstract: Due to the deregulation of the Electric Supply
Industry and the resulting emergence of electricity market, the
volumes of power purchases are on the rise all over the world. In a
bid to meet the customer-s demand in a reliable and yet economic
manner, utilities purchase power from the energy market over and
above its own production. This paper aims at developing an optimal
power purchase model with two objectives viz economy and
environment ,taking various functional operating constraints such as
branch flow limits, load bus voltage magnitudes limits, unit capacity
constraints and security constraints into consideration.The price of
purchased power being an uncertain variable is modeled using fuzzy
logic. DEMO (Differential Evolution For Multi-objective
Optimization) is used to obtain the pareto-optimal solution set of the
multi-objective problem formulated. Fuzzy set theory has been
employed to extract the best compromise non-dominated solution.
The results obtained on IEEE 30 bus system are presented and
compared with that of NSGAII.
Abstract: Clustering in high dimensional space is a difficult
problem which is recurrent in many fields of science and
engineering, e.g., bioinformatics, image processing, pattern
reorganization and data mining. In high dimensional space some of
the dimensions are likely to be irrelevant, thus hiding the possible
clustering. In very high dimensions it is common for all the objects in
a dataset to be nearly equidistant from each other, completely
masking the clusters. Hence, performance of the clustering algorithm
decreases.
In this paper, we propose an algorithmic framework which
combines the (reduct) concept of rough set theory with the k-means
algorithm to remove the irrelevant dimensions in a high dimensional
space and obtain appropriate clusters. Our experiment on test data
shows that this framework increases efficiency of the clustering
process and accuracy of the results.
Abstract: This article outlines conceptualization and
implementation of an intelligent system capable of extracting
knowledge from databases. Use of hybridized features of both the
Rough and Fuzzy Set theory render the developed system flexibility
in dealing with discreet as well as continuous datasets. A raw data set
provided to the system, is initially transformed in a computer legible
format followed by pruning of the data set. The refined data set is
then processed through various Rough Set operators which enable
discovery of parameter relationships and interdependencies. The
discovered knowledge is automatically transformed into a rule base
expressed in Fuzzy terms. Two exemplary cancer repository datasets
(for Breast and Lung Cancer) have been used to test and implement
the proposed framework.
Abstract: Quality control charts indicate out of control
conditions if any nonrandom pattern of the points is observed or any
point is plotted beyond the control limits. Nonrandom patterns of
Shewhart control charts are tested with sensitizing rules. When the
processes are defined with fuzzy set theory, traditional sensitizing
rules are insufficient for defining all out of control conditions. This is
due to the fact that fuzzy numbers increase the number of out of
control conditions. The purpose of the study is to develop a set of
fuzzy sensitizing rules, which increase the flexibility and sensitivity
of fuzzy control charts. Fuzzy sensitizing rules simplify the
identification of out of control situations that results in a decrease in
the calculation time and number of evaluations in fuzzy control chart
approach.
Abstract: Knowledge Discovery in Databases (KDD) has
evolved into an important and active area of research because of
theoretical challenges and practical applications associated with the
problem of discovering (or extracting) interesting and previously
unknown knowledge from very large real-world databases. Rough
Set Theory (RST) is a mathematical formalism for representing
uncertainty that can be considered an extension of the classical set
theory. It has been used in many different research areas, including
those related to inductive machine learning and reduction of
knowledge in knowledge-based systems. One important concept
related to RST is that of a rough relation. In this paper we presented
the current status of research on applying rough set theory to KDD,
which will be helpful for handle the characteristics of real-world
databases. The main aim is to show how rough set and rough set
analysis can be effectively used to extract knowledge from large
databases.
Abstract: In this article, by using fuzzy AHP and TOPSIS
technique we propose a new method for project selection problem.
After reviewing four common methods of comparing alternatives
investment (net present value, rate of return, benefit cost analysis
and payback period) we use them as criteria in AHP tree. In this
methodology by utilizing improved Analytical Hierarchy Process
by Fuzzy set theory, first we try to calculate weight of each
criterion. Then by implementing TOPSIS algorithm, assessment of
projects has been done. Obtained results have been tested in a
numerical example.