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2013
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A New and Quick Method to Detect Dos Attacks by Neural Networks
A New and Quick Method to Detect Dos Attacks by Neural Networks
en
en
Since it is technically impossible to create computer systems (Hardware and Software) without any defect or security failure, intrusion detection in computer systems’ researches is specifically regarded as important.IDS is a protective system that can detect disorders occurring on the network. The procedure goes as intrusion detection can report and control occurred disorders through steps including collecting data, seeking ports, controlling computers, and finally hacking. So, intrusion detection can report control intrusion sabotage that composed of phases collecting data, probing port, gaining computer’s control and finally hacking. In this paper, we consider some different agents, each of which can detect one or two DOS attacks. These agents interact in a way not to interfere each other. Parallelization Technology is used to increase system speed. Since the designed agents act separately and the result of each agent has no impact on the others, you can run each system on discrete CPUs (depending on how many CPUs are used in IDS computers) to speed up the performance.
85
96
Mohammad Masoud
Javidi
M. Hassan
Mohammad Hassan
Multi-Layer Protection (MLP)
Neural Network
Intrusion Detection System
Misuse-based IDS.
Article.1.pdf
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]
A New Method for Clustering in Credit Scoring Problems
A New Method for Clustering in Credit Scoring Problems
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en
Due to the recent financial crisis and regulatory concerns of Basel II, credit risk assessment has become one of the most important topics in the financial risk management. Quantitative credit scoring models are widely used to assess credit risk in financial institutions. In this paper we introduce Time Adaptive self organizing Map Neural Network to cluster creditworthy customers against non credit worthy ones. We test this Neural Network on Australian credit data set and compare the results with other clustering Algorithm’s include K-means, PAM, SOM against different internal and external measures. TASOM has the best performance in clusters customers.
97
106
Mohammad Reza
Gholamian
Saber
Jahanpour
Seyed Mahdi
Sadatrasoul
Credit Scoring
Banking Industry
Clustering
Time adaptive neural network
Article.2.pdf
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]
Choosing an Appropriate Factorial System Through the Modern and Outmoded System by Two Approaches Anp Ahp-fuzzy
Choosing an Appropriate Factorial System Through the Modern and Outmoded System by Two Approaches Anp Ahp-fuzzy
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en
Today, by introducing the factorial modern systems to the construction industry of the country, it is not easy to make a decision in order to use these modern systems together with the outmoded and conventional systems .Regarding the unique traits in each of these systems, and the special conditions of each project, it is possible that each of these systems to have a priority over the factorial systems prevailing in the country. Thus, it was made an effort to choose the most appropriate factorial system through the modern and outmoded systems in the country using the multi criteria making decision methods, ANP and AHP-FUZZY, and regarding some of the important criteria in choosing the type of the factorial system such as dead load, saving energy, performance facility, etc .finally, light steel frame (LSF) system has been chosen as the most appropriate selection through the ones under study.
107
117
Gholamreza
Abdollahzadeh
Mohammad Javad Taheri
Amiri
Ehsan Akbari
Kaffash
Media
Hemmatian
Soroush
Keihanfard
Structural systems
Industrialization
Management and structure engineering
ANP
AHP-FUZZY
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]
Fixed Point Theorems for Weakly Compatible Maps under E.a. Property in Fuzzy 2-metric Spaces
Fixed Point Theorems for Weakly Compatible Maps under E.a. Property in Fuzzy 2-metric Spaces
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en
In this paper, we introduce E.A. property on fuzzy 2-metric spaces and prove common fixed point
theorem for a pair of weakly compatible maps under E.A. property on fuzzy 2-metric spaces.
118
128
H.
Shojaei
K.
Banaei
N.
Shojaei
Weakly compatible maps
E.A. property
fuzzy 2-metric space.
Article.4.pdf
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A New Mechanism for Traffic Reduction the Serviceresource Discovery Protocol in Ad-hoc Grid Network
A New Mechanism for Traffic Reduction the Serviceresource Discovery Protocol in Ad-hoc Grid Network
en
en
129
138
A. S.
Izadi
A. R.
Sahab
J.
Vahidi
Article.5.pdf
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, , , (), -
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Use of Computer Facilities for Study of Geodesics Schwarzschild Robertsonwalker Space-time
Use of Computer Facilities for Study of Geodesics Schwarzschild Robertsonwalker Space-time
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en
We describe the graphical study of geodesic motion on Schwarzshild Robertson-Walker space-time
using the symbols and graphical computation facilities of maple platform.
139
145
Jamal Saffar
Ardabili
Mahnaz
Ebrahimi
General relativity
Computer algebra.
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Optimization of Orthogonal Polyphase Coding Waveform for Mimo Radar Based on Evolutionary Algorithms
Optimization of Orthogonal Polyphase Coding Waveform for Mimo Radar Based on Evolutionary Algorithms
en
en
Using multiple antennas at both transmitter and receiver to improve communication
performance is referred to as multi-input multi-output (MIMO) system. In order to keep away
interference and increase the independency between the information received from or reflected by
various targets, the transmitted signals are required to be mutually orthogonal. In this paper a new
approach using evolutionary algorithms including particle swarm optimization (PSO), bee
algorithm (BA) and artificial bee colony (ABC) to design orthogonal discrete frequency coding
waveforms (DFCWs) is proposed. These methods have desirable autocorrelation and cross
correlation characteristics for orthogonal MIMO radars. The simulation results and comparisons
demonstrate that each evolutionary algorithm has its own advantages and disadvantages and
therefore can be applied to meet particular requirements.
146
153
Hamed
Azami
Milad
Malekzadeh
Saeid
Sanei
Alireza
Khosravi
Poly phase
MIMO radars
evolutionary algorithms.
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]
A Graph Based Approach for Clustering Ensemble of Fuzzy Partitions
A Graph Based Approach for Clustering Ensemble of Fuzzy Partitions
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en
Fuzzy clustering and Cluster Ensemble are important subjects in data mining. In recent years, fuzzy
clustering algorithms have been growing rapidly, but fuzzy Clustering ensemble techniques have not
grown much and most of them have been created by converting them to a fuzzy version of Consensus
Function. In this paper, a fuzzy cluster ensemble method based on graph is introduced. Proposed approach
uses membership matrixes obtained from multiple fuzzy partitions resulted by various fuzzy methods, and
then creates fuzzy co-association matrixes for each partition which their entries present degree of
correlation between related data points. Finally all of these matrixes summarize in another matrix called
strength matrix and the final result is specified by an iterative decreasing process until one gets the
desired number of clusters. Also a few data sets and some UCI datasets data set are used for evaluation of
proposed methods. The proposed approach shows this could be more effective than base clustering
algorithms same of FCM, K-means and spectral method and in comparison with various cluster ensemble
methods, the proposed methods consist of results that are more reliable and less error rates than other
methods.
154
165
Mohammad
Ahmadzadeh
Zahra Azartash
Golestan
Javad
Vahidi
Babak
Shirazi
Fuzzy Clustering Ensemble
Fuzzy Co-association Matrix
Dissimilarity Matrix.
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