Abstract: There are many situations where input feature vectors are incomplete and methods to tackle the problem have been studied for a long time. A commonly used procedure is to replace each missing value with an imputation. This paper presents a method to perform categorical missing data imputation from numerical and categorical variables. The imputations are based on Simpson-s fuzzy min-max neural networks where the input variables for learning and classification are just numerical. The proposed method extends the input to categorical variables by introducing new fuzzy sets, a new operation and a new architecture. The procedure is tested and compared with others using opinion poll data.
Abstract: The design of Automatic Generation Control (AGC) system plays a vital role in automation of power system. This paper proposes Hybrid Neuro Fuzzy (HNF) approach for AGC of two-area interconnected reheat thermal power system with the consideration of Generation Rate Constraint (GRC). The advantage of proposed controller is that it can handle the system non-linearities and at the same time the proposed approach is faster than conventional controllers. The performance of HNF controller has been compared with that of both conventional Proportional Integral (PI) controller as well as Fuzzy Logic Controller (FLC) both in the absence and presence of Generation Rate Constraint (GRC). System performance is examined considering disturbance in each area of interconnected power system.
Abstract: Decision fusion is one of hot research topics in
classification area, which aims to achieve the best possible
performance for the task at hand. In this paper, we
investigate the usefulness of this concept to improve change
detection accuracy in remote sensing. Thereby, outputs of
two fuzzy change detectors based respectively on
simultaneous and comparative analysis of multitemporal
data are fused by using fuzzy integral operators. This
method fuses the objective evidences produced by the
change detectors with respect to fuzzy measures that express
the difference of performance between them. The proposed
fusion framework is evaluated in comparison with some
ordinary fuzzy aggregation operators. Experiments carried
out on two SPOT images showed that the fuzzy integral was
the best performing. It improves the change detection
accuracy while attempting to equalize the accuracy rate in
both change and no change classes.
Abstract: In this paper I have developed a system for evaluating
the degree of fear emotion that the intelligent agent-based system
may feel when it encounters to a persecuting event. In this paper I
want to describe behaviors of emotional agents using human
behavior in terms of the way their emotional states evolve over time.
I have implemented a fuzzy inference system using Java
environment. As the inputs of this system, I have considered three
parameters related on human fear emotion. The system outputs can
be used in agent decision making process or choosing a person for
team working systems by combination the intensity of fear to other
emotion intensities.
Abstract: This paper presents a new method for the
implementation of a direct rotor flux control (DRFOC) of induction
motor (IM) drives. It is based on the rotor flux components
regulation. The d and q axis rotor flux components feed proportional
integral (PI) controllers. The outputs of which are the target stator
voltages (vdsref and vqsref). While, the synchronous speed is depicted at
the output of rotor speed controller. In order to accomplish variable
speed operation, conventional PI like controller is commonly used.
These controllers provide limited good performances over a wide
range of operations even under ideal field oriented conditions. An
alternate approach is to use the so called fuzzy logic controller. The
overall investigated system is implemented using dSpace system
based on digital signal processor (DSP). Simulation and experimental
results have been presented for a one kw IM drives to confirm the
validity of the proposed algorithms.
Abstract: This paper focuses on testing database of existing
information system. At the beginning we describe the basic problems
of implemented databases, such as data redundancy, poor design of
database logical structure or inappropriate data types in columns of
database tables. These problems are often the result of incorrect
understanding of the primary requirements for a database of an
information system. Then we propose an algorithm to compare the
conceptual model created from vague requirements for a database
with a conceptual model reconstructed from implemented database.
An algorithm also suggests steps leading to optimization of
implemented database. The proposed algorithm is verified by an
implemented prototype. The paper also describes a fuzzy system
which works with the vague requirements for a database of an
information system, procedure for creating conceptual from vague
requirements and an algorithm for reconstructing a conceptual model
from implemented database.
Abstract: In the present paper, active control system is used in
different heights of the building and the most effective part was
studied where the active control system is applied. The mathematical
model of the building is established in MATLAB and in order to
active control the system FLC method was used. Three different
locations of the building are chosen to apply active control system,
namely at the lowest story, the middle height of the building, and at
the highest point of the building with TMD system. The equation of
motion was written for high rise building and it was solved by statespace
method. Also passive control was used with Tuned Mass
Damper (TMD) at the top floor of the building to show the robustness
of FLC method when compared with passive control system.
Abstract: This paper proposes the application of a hierarchical fuzzy system (HFS) based on multi-input power system stabilizer (MPSS) and also Static Var Compensator (SVC) in multi-machine environment.The number of rules grows exponentially with the number of variables in a conventional fuzzy logic system. The proposed HFS method is developed to solve this problem. To reduce the number of rules the HFS consists of a number of low-dimensional fuzzy systems in a hierarchical structure. In fact, by using HFS the total number of involved rules increases only linearly with the number of input variables. In the MPSS, to have better efficiency an auxiliary signal of reactive power deviation (ΔQ) is added with ΔP+ Δω input type Power system stabilizer (PSS). Phasor model of SVC is described and used in this paper. The performances of MPSS, Conventional power system stabilizer (CPSS), hierarchical Fuzzy Multi-input Power System Stabilizer (HFMPSS) and the proposed method in damping inter-area mode of oscillation are examined in response to disturbances. By using digital simulations the comparative study is illustrated. It can be seen that the proposed PSS is performing satisfactorily within the whole range of disturbances.
Abstract: Much research into handwritten Thai character
recognition have been proposed, such as comparing heads of
characters, Fuzzy logic and structure trees, etc. This paper presents a
system of handwritten Thai character recognition, which is based on
the Ant-minor algorithm (data mining based on Ant colony
optimization). Zoning is initially used to determine each character.
Then three distinct features (also called attributes) of each character
in each zone are extracted. The attributes are Head zone, End point,
and Feature code. All attributes are used for construct the
classification rules by an Ant-miner algorithm in order to classify
112 Thai characters. For this experiment, the Ant-miner algorithm is
adapted, with a small change to increase the recognition rate. The
result of this experiment is a 97% recognition rate of the training set
(11200 characters) and 82.7% recognition rate of unseen data test
(22400 characters).
Abstract: The aim of this paper is to adopt a compromise ratio (CR) methodology for fuzzy multi-attribute single-expert decision making proble. In this paper, the rating of each alternative has been described by linguistic terms, which can be expressed as triangular fuzzy numbers. The compromise ratio method for fuzzy multi-attribute single expert decision making has been considered here by taking the ranking index based on the concept that the chosen alternative should be as close as possible to the ideal solution and as far away as possible from the negative-ideal solution simultaneously. From logical point of view, the distance between two triangular fuzzy numbers also is a fuzzy number, not a crisp value. Therefore a fuzzy distance measure, which is itself a fuzzy number, has been used here to calculate the difference between two triangular fuzzy numbers. Now in this paper, with the help of this fuzzy distance measure, it has been shown that the compromise ratio is a fuzzy number and this eases the problem of the decision maker to take the decision. The computation principle and the procedure of the compromise ratio method have been described in detail in this paper. A comparative analysis of the compromise ratio method previously proposed [1] and the newly adopted method have been illustrated with two numerical examples.
Abstract: The highly nonlinear characteristics of drying
processes have prompted researchers to seek new nonlinear control
solutions. However, the relation between the implementation
complexity, on-line processing complexity, reliability control
structure and controller-s performance is not well established. The
present paper proposes high performance nonlinear fuzzy controllers
for a real-time operation of a drying machine, being developed under
a consistent match between those issues. A PCI-6025E data
acquisition device from National Instruments® was used, and the
control system was fully designed with MATLAB® / SIMULINK
language. Drying parameters, namely relative humidity and
temperature, were controlled through MIMOs Hybrid Bang-bang+PI
(BPI) and Four-dimensional Fuzzy Logic (FLC) real-time-based
controllers to perform drying tests on biological materials. The
performance of the drying strategies was compared through several
criteria, which are reported without controllers- retuning. Controllers-
performance analysis has showed much better performance of FLC
than BPI controller. The absolute errors were lower than 8,85 % for
Fuzzy Logic Controller, about three times lower than the
experimental results with BPI control.
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: In quality control of freeze-dried durian, crispiness is
a key quality index of the product. Generally, crispy testing has to be
done by a destructive method. A nondestructive testing of the
crispiness is required because the samples can be reused for other
kinds of testing. This paper proposed a crispiness classification
method of freeze-dried durians using fuzzy logic for decision
making. The physical changes of a freeze-dried durian include the
pores appearing in the images. Three physical features including (1)
the diameters of pores, (2) the ratio of the pore area and the
remaining area, and (3) the distribution of the pores are considered to
contribute to the crispiness. The fuzzy logic is applied for making the
decision. The experimental results comparing with food expert
opinion showed that the accuracy of the proposed classification
method is 83.33 percent.
Abstract: One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.
Abstract: Groundlessness of application probability-statistic methods are especially shown at an early stage of the aviation GTE technical condition diagnosing, when the volume of the information has property of the fuzzy, limitations, uncertainty and efficiency of application of new technology Soft computing at these diagnosing stages by using the fuzzy logic and neural networks methods. It is made training with high accuracy of multiple linear and nonlinear models (the regression equations) received on the statistical fuzzy data basis. At the information sufficiency it is offered to use recurrent algorithm of aviation GTE technical condition identification on measurements of input and output parameters of the multiple linear and nonlinear generalized models at presence of noise measured (the new recursive least squares method (LSM)). As application of the given technique the estimation of the new operating aviation engine D30KU-154 technical condition at height H=10600 m was made.
Abstract: The innovative fuzzy estimator is used to estimate the
ground motion acceleration of the retaining structure in this study. The
Kalman filter without the input term and the fuzzy weighting recursive
least square estimator are two main portions of this method. The
innovation vector can be produced by the Kalman filter, and be
applied to the fuzzy weighting recursive least square estimator to
estimate the acceleration input over time. The excellent performance
of this estimator is demonstrated by comparing it with the use of
difference weighting function, the distinct levels of the measurement
noise covariance and the initial process noise covariance. The
availability and the precision of the proposed method proposed in this
study can be verified by comparing the actual value and the one
obtained by numerical simulation.
Abstract: The design of weight is one of the important parts in
fuzzy decision making, as it would have a deep effect on the evaluation
results. Entropy is one of the weight measure based on objective
evaluation. Non--probabilistic-type entropy measures for fuzzy set
and interval type-2 fuzzy sets (IT2FS) have been developed and applied
to weight measure. Since the entropy for (IT2FS) for decision
making yet to be explored, this paper proposes a new objective
weight method by using entropy weight method for multiple attribute
decision making (MADM). This paper utilizes the nature of IT2FS
concept in the evaluation process to assess the attribute weight based
on the credibility of data. An example was presented to demonstrate
the feasibility of the new method in decision making. The entropy
measure of interval type-2 fuzzy sets yield flexible judgment and
could be applied in decision making environment.
Abstract: A new fuzzy filter is presented for noise reduction of
images corrupted with additive noise. The filter consists of two
stages. In the first stage, all the pixels of image are processed for
determining noisy pixels. For this, a fuzzy rule based system
associates a degree to each pixel. The degree of a pixel is a real
number in the range [0,1], which denotes a probability that the pixel
is not considered as a noisy pixel. In the second stage, another fuzzy
rule based system is employed. It uses the output of the previous
fuzzy system to perform fuzzy smoothing by weighting the
contributions of neighboring pixel values. Experimental results are
obtained to show the feasibility of the proposed filter. These results
are also compared to other filters by numerical measure and visual
inspection.
Abstract: Static Var Compensator (SVC) is a shunt type FACTS
device which is used in power system primarily for the purpose of
voltage and reactive power control. In this paper, a fuzzy logic based
supplementary controller for Static Var Compensator (SVC) is
developed which is used for damping the rotor angle oscillations and
to improve the transient stability of the power system. Generator
speed and the electrical power are chosen as input signals for the
Fuzzy Logic Controller (FLC). The effectiveness and feasibility of
the proposed control is demonstrated with Single Machine Infinite
Bus (SMIB) system and multimachine system (WSCC System)
which show improvement over the use of a fixed parameter
controller.
Abstract: An additive fuzzy system comprising m rules with
n inputs and p outputs in each rule has at least t m(2n + 2 p + 1)
parameters needing to be tuned. The system consists of a large
number of if-then fuzzy rules and takes a long time to tune its
parameters especially in the case of a large amount of training data
samples. In this paper, a new learning strategy is investigated to cope
with this obstacle. Parameters that tend toward constant values at the
learning process are initially fixed and they are not tuned till the end
of the learning time. Experiments based on applications of the
additive fuzzy system in function approximation demonstrate that the
proposed approach reduces the learning time and hence improves
convergence speed considerably.