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Paper Title Authors Conference Abstract
A New Approach in Feature Subset Selection Based on Fuzzy Entropy Concept Hossein Ghaffarian
Hamid Parvin
Behrouz Minaei
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
Improving the Classification of Unknown Documents by Concept Graph Morteza Mohaqeqi
Reza Soltanpoor
Azadeh Shakery
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
Evolution of Neural Network Architecture and Weights Using Mutation Based Genetic Algorithm A. Nadi
S. S. Tayarani-Bathaie
R. Safabakhsh
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
Random Indexing and the episodic memory metaphor. Application to text categorization Yann Vigile Hoareau
Adil El Ghali
Denis Legros
Kaoutar El Ghali
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
Feature Selection and Dimension Reduction for Automatic Gender Identification Mohammad Ali Keyvanrad
Mohammad Mehdi Homayounpour
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
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
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
Improving Source Localization in LOS and NLOS Multipath Environments for UWB Signals Arash Abbasi
Mohammad Hossein Kahaei
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
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
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
Multi Agent Based Web Service QoS Management Architecture Jaleh Shoshtarian Malak
Mehran Mohsenzadeh
Mir Ali Seyyedi
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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