]>
2014
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4
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Utility Based Credit Scoring for Banks and Financial Institutions Case Study of a Major Iranian Bank
Utility Based Credit Scoring for Banks and Financial Institutions Case Study of a Major Iranian Bank
en
en
Credit scoring mainly distinguishes good customers from the bad ones; therefore it is a classification problem. There are many techniques introduced to solve the problem such as support vector machines, neural networks and rule based classifiers. The main objective of this process is to maximize the profit of bank or financial institute. However these traditional methods of classification seem not to support this objective well. This paper investigates this issue and shows that the best classification model is not necessarily the most profitable model. The applications of the models are shown on an ironing real credit dataset since 2007 to 2012.
281
287
Seyed Mahdi
Sadatrasoul
Mohammad Reza
Gholamian
Zeynab
Hajimohammadi
Mahdi
Hosseini
Credit Scoring
Banking Industry
Classification
Utility based data mining.
Article.1.pdf
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]
Some Results on the Generalized Rough Lie Subalgebras
Some Results on the Generalized Rough Lie Subalgebras
en
en
The main purpose of this paper is to introduce and discuss the concept of
T-roughness in Lie subalgebra and generalized T-rough Lie subalgebras. We
define a set-valued homomorphism on a Lie algebra and study some of their
properties and useful applications.
288
299
S. B.
Hosseini
A.
Kazemi
Lower approximation
Upper approximation
T-rough set
Set-valued homomorphism
Lie algebras.
Article.2.pdf
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]
Levenberg-marquardt Method for Solving the Inverse Heat Transfer Problems
Levenberg-marquardt Method for Solving the Inverse Heat Transfer Problems
en
en
In this paper, The Levenberg-Marquardt method is used in order to solve the inverse heat conduction problem. One-dimensional formulation of heat conduction problem was used. The direct problem was solved with finite-volumes by using an implicit discretization in time. Simulated measurements are obtained from the solution of the direct Problem at the sensor location. Results obtained in this inverse problem will be justified based on the numerical experiments. The results show that the speed of convergence is considerably fast and The Levenberg-Marquardt method is an accurate and stable method to determine the strength of the heat source in the inverse heat conduction problems.
300
310
Nasibeh Asa
Golsorkhi
Hojat Ahsani
Tehrani
Levenberg-Marquardt method
inverse problem
heat conduction .
Article.3.pdf
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]
A Chaotic Blind Digital Image Watermarking Based on Singular Value Decomposition in Spatial Domain
A Chaotic Blind Digital Image Watermarking Based on Singular Value Decomposition in Spatial Domain
en
en
In this letter a new watermarking scheme for Gray scale image is proposed based on a family of the chaotic maps and Singular Value Decomposition. Jacobian elliptic map is used to encrypt the watermark logo to improve the security of watermarked image. Quantum map is also used to determine the location of image's block for the watermark embedding. To test the robustness and effectiveness of our proposed method, several attacks are applied to the watermarked image and the best results have been reported. The purpose of this algorithm is to improve the shortcoming of watermarking such as small key space and low security. The experimental results demonstrate that the key space is large enough to resist the attack and the distribution of grey values of the encrypted image has a random-like behavior, which makes it a potential candidate for encryption of multimedia data such as images, audios and even videos.
311
320
Niaz
Khorrami
Peyman
Ayubi
Sohrab
Behnia
Jila
Ayubi
Blind Digital Image Watermarking
Chaos
Singular Value Decomposition
Chaotic Map.
Article.4.pdf
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[1]
IJ. Cox, LM. Matthew, AB. Jeffrey, et al, Digital Watermarking and Steganography, Second edition, MA: Morgan Kaufmann Publishers (Elsevier), Burlington (2007)
##[2]
S. Amirgholipour, A. Naghsh-Nilchi, et al, Application of Unsharp Mask in Augmenting the Quality of Extracted Watermark in Spatial Domain Watermarking, The journal of Mathematics and Computer Science, 11 (2014), 137-146
##[3]
C. H. Huang, J. L. Wua, Fidelity-guaranteed robustness enhancement of blind-detection watermarking schemes, Information Sciences , 179 (2009), 791-808
##[4]
Y. Liu, J. Zhao, A new video watermarking algorithm based on 1-D DFT and Radon transform, Signal Processing, 90 (2010), 626-639
##[5]
H. Wei, M. Yuan, J. Zhao, Z. Kou, Research and Realization of Digital Watermark for Picture Protecting, First International Workshop on Education Technology and Computer Science, IEEE, 1 (2009), 968-970
##[6]
X. Li, A New Measure of Image Scrambling Degree Based on Grey Level Difference and Information Entropy, International Conference on Computational Intelligence and Security, 1 (2008), 350-354
##[7]
Z. W. Shen, W. W. Liao, Y. N. Shen, Blind watermarking algorithm based on henon chaos system and lifting scheme wavelet, Proceedings of the 2009 International Conference on Wavelet Analysis and Pattern Recognition, Baoding, (2009), 308-313
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]
The Use of the Corner Sorting Method in the Nsga-ii in Comparison with Spea-ii in the Simultaneous Optimization, the Size, Shape and Topology of Two-dimensional Trusses
The Use of the Corner Sorting Method in the Nsga-ii in Comparison with Spea-ii in the Simultaneous Optimization, the Size, Shape and Topology of Two-dimensional Trusses
en
en
In this study, we are trying to do Non-dominated Sorting in simultaneous optimization at three levels the size, deformation and topology in two-dimensional trusses by using a new technique for Corner Sorting in genetic algorithms. Also, using this method and comparison with strong SPEA-II evolutionary algorithms in parameter, accuracy and extent of the Pareto curve occurs. Therefore, first we examine the algorithm in terms of numerical in the mathematics problems. And then, in ten-bars and three -bars trusses, we examine three levels of size, deformation and topology. The results show that the algorithm has very high accuracy to find solutions closer to the true Pareto optimal. Also, the algorithm has high capacity to find different topology at Pareto optimal level.
321
335
Hamid Reza
Loghmani
Ali
Ghoddosian
multi-objective optimization
topology
Pareto curve
dominate
Non-dominated Sorting
Corner Sorting
Article.5.pdf
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]
A Best Proximity Point Theorem in Metric Spaces with Generalized Distance
A Best Proximity Point Theorem in Metric Spaces with Generalized Distance
en
en
In this paper at first, we define the weak P-property with respect to a \(\tau\)-distance such as p. Then we state a best proximity point theorem in a complete metric space with generalized distance such that it is an extension of previous research.
336
342
Mehdi
Omidvari
S. Mansour
Vaezpour
weak P-property
best proximity point
\(\tau\)-distance
weakly contractive mapping
altering distance functions.
Article.6.pdf
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M. Akram, W. Shamaila , Fixed point results in partial metric spaces using generalized weak contractive conditions, The Journal of Mathematics and Computer Science, 12 (2014), 85-98
]
Application of Ant Colony Algorithm and Principal Components Analysis in the Diagnosis of Lung Cancer
Application of Ant Colony Algorithm and Principal Components Analysis in the Diagnosis of Lung Cancer
en
en
This paper presents a new method for diagnosing lung cancer by combination of ant colony algorithm, fuzzy logic and principal component analysis (PCA). In this method, PCA method is used to reduce the size of data sets, the fuzzy logic is used to create fuzzy rules that make it possible to be interpreted by experts. Finally, these fuzzy rules are optimized by ant colony algorithm (ACO). Evaluation and comparing the proposed method with other methods have been proposed to implement this approach, leading to lung cancer dataset with criteria such as speed, reliability, and the ability to interpret the show.
343
352
Saeed
Ayat
Mohsen
Rahi
lung cancer
data mining
ACO
fuzzy logic
PCA.
Article.7.pdf
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Proposing a Neural-genetic System for Optimized Feature Selection Applied in Medical Datasets
Proposing a Neural-genetic System for Optimized Feature Selection Applied in Medical Datasets
en
en
This paper, presents a new system for selecting the best optimized features among a collection of features by combination of neural network and genetic algorithm. Feature selection is an important issue because it has a direct impact on the performance (Specificity, sensitivity) and system efficiency.
The proposed system uses neural network for selecting the best features based on Signal to Noise Ratio (SNR), and genetic algorithm for training the neural network by determining the optimum values of weighs and other parameters. This system is a combination of a Multi-Layer Perceptron (MLP) with 3 layers and decimal genetic algorithm.
We evaluated our proposed system on 10 medical data sets and compared it with binary genetic algorithm that is used widely for feature selection. The results confirmed the superiority of the proposed system in Specificity, sensitivity and the number of selected optimized features.
353
358
Saeed
Ayat
Mohammad Reza Mohammadi
Khoroushani
feature selection
optimized feature selection
neural network
genetic algorithm.
Article.8.pdf
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]