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Paper Title |
Authors |
Conference |
Abstract |
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A New Approach in Feature Subset Selection Based on Fuzzy Entropy Concept |
Hossein Ghaffarian
Hamid Parvin
Behrouz Minaei
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we proposed a new feature subset
selection approach. In proposed approach first, the
entire dataset are classified and the best number of
clusters over it are found according to silhouette ... more
In this paper, we proposed a new feature subset
selection approach. In proposed approach first, the
entire dataset are classified and the best number of
clusters over it are found according to silhouette value.
Then according to this value, each feature is alone
classified with the same cluster number and
accordingly the proposed entropy fuzzy measure is
found for them. We examine our method on some
traditional datasets. The results show a good
performance of proposed method. less
In this paper, we proposed a new feature subset
selection approach. In proposed approach first, the
entire dataset are classified and the best number of
clusters over it are found according to silhouette ... more |
خرید مقاله
|
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Improving the Classification of Unknown Documents by Concept Graph |
Morteza Mohaqeqi
Reza Soltanpoor
Azadeh Shakery
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Concept graph is a graph that represents the
relationships between language concepts. In this
structure the relationship between any two words is
demonstrated by a weighted edge such that the value of
this weight ... more
Concept graph is a graph that represents the
relationships between language concepts. In this
structure the relationship between any two words is
demonstrated by a weighted edge such that the value of
this weight is interpreted as the degree of the relevance
of two words. Having this graph, we can obtain most
relevant words to a special term. In this paper, we
propose a method for improving the classification of
documents from unknown sources by means of concept
graph. In our method, initially some features are
selected from a training set by a well-known feature
selection algorithm. Then, by extracting most relevant
words for each class from the concept graph, a more
effective feature set is produced. Our experimental
results identify an improvement of 1% and 8% in
precision and recall measures, respectively. less
Concept graph is a graph that represents the
relationships between language concepts. In this
structure the relationship between any two words is
demonstrated by a weighted edge such that the value of
this weight ... more |
خرید مقاله
|
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Evolution of Neural Network Architecture and Weights Using Mutation Based Genetic Algorithm |
A. Nadi
S. S. Tayarani-Bathaie
R. Safabakhsh
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper we present a new approach for
evolving an optimized neural network architecture for a
three layer feedforward neural network with a mutation
based genetic algorithm. In this study we will ... more
In this paper we present a new approach for
evolving an optimized neural network architecture for a
three layer feedforward neural network with a mutation
based genetic algorithm. In this study we will optimize the
weights and the network architecture simultaneously
through a new presentation for the three layer feedforward
neural network. The goal of the method is to find the
optimal number of neurons and their appropriate weights.
This optimization problem so far has been solved by looking
at the general architecture of the network but we optimize
the individual neurons of the hidden layer. This change
results in a search space with much higher resolution and an
increased speed of convergence. Evaluation of algorithm by
3 data sets reveals that this method shows a very good
performance in comparison to current methods. less
In this paper we present a new approach for
evolving an optimized neural network architecture for a
three layer feedforward neural network with a mutation
based genetic algorithm. In this study we will ... more |
خرید مقاله
|
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Random Indexing and the episodic memory metaphor. Application to text categorization |
Yann Vigile Hoareau
Adil El Ghali
Denis Legros
Kaoutar El Ghali
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
A model of episodic memory is derived to propose
algorithms of text categorization with semantic space models.
Performances of two algorithms are contrasted using textual
material of the text-mining context ‘DEFT09’. Results confirm
that ... more
A model of episodic memory is derived to propose
algorithms of text categorization with semantic space models.
Performances of two algorithms are contrasted using textual
material of the text-mining context ‘DEFT09’. Results confirm
that the episodic memory metaphor provides a convenient
framework to propose efficient algorithm for text
categorization. One algorithm has already been tested with
LSA. The present paper extends these algorithms to another
model of Word Vector named Random Indexing. less
A model of episodic memory is derived to propose
algorithms of text categorization with semantic space models.
Performances of two algorithms are contrasted using textual
material of the text-mining context ‘DEFT09’. Results confirm
that ... more |
خرید مقاله
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Feature Selection and Dimension Reduction for Automatic Gender Identification |
Mohammad Ali Keyvanrad
Mohammad Mehdi Homayounpour
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Gender identification based on speech signal has
become gradually a matter of concern in recent years.
In this context 6 feature types including MFCC, LPC,
RC, LAR, pitch values and formants are compared ... more
Gender identification based on speech signal has
become gradually a matter of concern in recent years.
In this context 6 feature types including MFCC, LPC,
RC, LAR, pitch values and formants are compared for
automatic gender identification and three best feature
types are selected using four feature selection
techniques. These techniques are GMM, Decision
Tree, Fisher’s Discriminant Ratio, and Volume of
Overlap Region. A dimension reduction is done on the
best three feature types and the best coefficients are
then selected from each feature vector. Selected
coefficients are evaluated for gender classification
using three types of classifiers including GMM, SVM
and MLP neural network. 96.09% gender
identification performance was obtained as the best
performance using the selected coefficients and MLP
classifier. less
Gender identification based on speech signal has
become gradually a matter of concern in recent years.
In this context 6 feature types including MFCC, LPC,
RC, LAR, pitch values and formants are compared ... more |
خرید مقاله
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Performance Improvement of AOA Positioning using A Two-Step Plan Based on Factor Graphs and the Gauss-Newton Method |
Behzad Omidali
S. Ali-Asghar Beheshti Shirazi
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper a two step method based on Gauss-
Newton and factor graphs algorithm is proposed for
localization to enhance accuracy of localization. The
Gauss-Newton algorithm is accurate method for
positioning. The most ... more
In this paper a two step method based on Gauss-
Newton and factor graphs algorithm is proposed for
localization to enhance accuracy of localization. The
Gauss-Newton algorithm is accurate method for
positioning. The most important challenge of this
method is senility to initial point; this problem is
solved in positioning based on factor graphs. So, in
this paper, first positioning equations using angle of
arrival is considered based on factor graphs
algorithm. Second, final location estimation is
performed using Gauss Newton algorithm with error
near to Cramer-Rao bound. Simulation results shows
that positioning error using two step method has
maximum 6% gap to Cramer-Rao Bound. less
In this paper a two step method based on Gauss-
Newton and factor graphs algorithm is proposed for
localization to enhance accuracy of localization. The
Gauss-Newton algorithm is accurate method for
positioning. The most ... more |
خرید مقاله
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Improving Source Localization in LOS and NLOS Multipath Environments for UWB Signals |
Arash Abbasi
Mohammad Hossein Kahaei
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
The presence of undetected direct path conditions in
the TOA (Time of Arrival)-based indoor geolocation
introduces major errors into distance measurements.
In the proposed location estimation, an improved
procedure is introduced in Ultra-wideband (UWB)
systems ... more
The presence of undetected direct path conditions in
the TOA (Time of Arrival)-based indoor geolocation
introduces major errors into distance measurements.
In the proposed location estimation, an improved
procedure is introduced in Ultra-wideband (UWB)
systems in Line of Sight (LOS) and Non-Line of Sight
(NLOS) multipath environments by incorporating the
skewness as new statistic information of multipath
channel. Weighted least square error (WLS) algorithm
is used to estimate source position in this paper.
Simulation results show effectiveness of the proposed
algorithm, by reducing source localization error.
Uncertainty region between NLOS and LOS
identification is reduced in the proposed method
compared to previous methods.. less
The presence of undetected direct path conditions in
the TOA (Time of Arrival)-based indoor geolocation
introduces major errors into distance measurements.
In the proposed location estimation, an improved
procedure is introduced in Ultra-wideband (UWB)
systems ... more |
خرید مقاله
|
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A Predictive Reinforcement Learning Framework for Modeling Human Decision Making Behavior |
Rezvan Kianifar
Farzad Towhidkhah
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Human can determine optimal behaviors which
depend on the ability to make planned and adaptive
decisions. In this paper, we have proposed a predictive
structure based on neuropsychological evidences to
model human decision making ... more
Human can determine optimal behaviors which
depend on the ability to make planned and adaptive
decisions. In this paper, we have proposed a predictive
structure based on neuropsychological evidences to
model human decision making process by
concentrating on the role of frontal brain regions
which are responsible for predictive control of human
behavior. We have considered a model-based
reinforcement learning framework to implement the
relations between these brain areas. Finally, we have
designed an experimental test to compare the function
of model with human behavior in a maze task. Our
results reveal that there is more than reward and
punishment in human behavior, and considering
higher cognitive functions such as prediction will help
to have more reliable models which could better
describe human behavior. less
Human can determine optimal behaviors which
depend on the ability to make planned and adaptive
decisions. In this paper, we have proposed a predictive
structure based on neuropsychological evidences to
model human decision making ... more |
خرید مقاله
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A Refinement Approach for Developing Probabilistic Programs |
Hassan Haghighi
Seyyed Hassan Mirian-Hosseinabadi
|
چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
In this paper, we introduce a refinement approach
to develop probabilistic programs formally. To
achieve this goal, we first present a way to specify
probabilistic programs in a Z-based notation. We then
use an ... more
In this paper, we introduce a refinement approach
to develop probabilistic programs formally. To
achieve this goal, we first present a way to specify
probabilistic programs in a Z-based notation. We then
use an existing method of translating Z into a
refinement calculus to transform our Z-style
specifications of probabilistic programs into
specification statements of the refinement calculus.
We finally add new laws to the refinement calculus
helping us to refine the resulting specification
statements into probabilistic choice constructs of a
probabilistic imperative language. In this way, we will
provide a completely formal way for developing
probabilistic programs. less
In this paper, we introduce a refinement approach
to develop probabilistic programs formally. To
achieve this goal, we first present a way to specify
probabilistic programs in a Z-based notation. We then
use an ... more |
خرید مقاله
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Multi Agent Based Web Service QoS Management Architecture |
Jaleh Shoshtarian Malak
Mehran Mohsenzadeh
Mir Ali Seyyedi
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چهاردهمین کنفرانس بین‌المللی سالانه انجمن کامپیوتر ایران |
Due to the changing and dynamic environment of
web services, Quality of Service (QoS) becomes a key
factor to differentiate service providers. Since current
web service standards and technologies suffer from
the lack of ... more
Due to the changing and dynamic environment of
web services, Quality of Service (QoS) becomes a key
factor to differentiate service providers. Since current
web service standards and technologies suffer from
the lack of QoS Management, having architectures
capable of supporting QoS verification, selection,
negotiation and monitoring is inevitable. Software
agents have been recognized as a promising
technology for managing web services. Using FIPA
compliant Multi Agents we were able to propose a
Multi Agents based web service QoS Management
Architecture. We also introduced a QoS based web
service clustering method which helps us to select the
best service that suits user quality preferences. less
Due to the changing and dynamic environment of
web services, Quality of Service (QoS) becomes a key
factor to differentiate service providers. Since current
web service standards and technologies suffer from
the lack of ... more |
خرید مقاله
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