fuzzy-rough neural networks
International Journal of Computer Science and Mobile Computing
... like Fuzzy Sets (FSs), Artificial Neural Networks (ANNs), evolutionary computation, Rough Sets (RSs), and Support Vector Machines (SVMs), biologically inspired algorithm like ant colony ...
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Soft-Computing Based Data Mining: A Review
... (involving fuzzy sets, neural networks, genetic algorithms, and rough sets) are most widely applied in the data mining step of the overall KDD ...process. Fuzzy sets provide a natural ...
15
A note on inequalities and critical values of fuzzy rough variables
... the fuzzy set of a fuzzy event can be given, which can be seen as a fuzzy rough ...of fuzzy rough sets by constructing a pair of upper and lower approximation operators of ...
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Effective Intrusion Detection with a Neural Network Ensemble Using Fuzzy Clustering and Stacking Combination Method
... modules: Fuzzy clustering, base classifiers using RBF networks, and stacking ...using fuzzy clustering ...RBF networks using the created ...by fuzzy clustering technique are used as ...
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An Approach of Artificial Neural Networks Modeling Based on Fuzzy Regression for Forecasting Purposes
... Artificial Neural Networks (ANNs) have been extensively used in forecast and prediction ...The fuzzy regression models are suitable models for these ...a fuzzy nonlinear regression model while ...
5
A New Approach to Rough Lattices and Rough Fuzzy Lattices Based on Fuzzy Ideals
... I T is well known that, in the real world, classical methods are not always successful in dealing with the problems in economy, engineering and social science, because of various types of uncertainties presented in these ...
7
HYBRID SOFT COMPUTING: THE PERCEPTION
... recurrent networks. The feed-forward networks include single- and multiple-layer perceptrons, as well as radial basis functions (RBF) networks ...recurrent networks cover competitive ...
18
Implementation of E-Service Intelligence in the Field of Web Mining
... including Neural Networks, Fuzzy Logic, Machine Learning, Genetic Algorithms, Bayesian Network, and Case-Based Reasoning have also been applied into web mining ...
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A Variable Precision Fuzzy Rough Set Approach to a Fuzzy Rough Decision Table
... precision rough set and fuzzy set. For fuzzy rough decision table, we convert fuzzy equivalence relation into equivalence relation through λ-cut set, and we construct variable precision ...
5
Assessment of Severity Level for Diabetic Macular Oedema Using Machine Learning Algorithms
... In view of the above stated reviews, in this proposed work, non-dilated retinal images are fed as input to the pre-processing stage. It corrects the problem of illumination variation that occurred during image ...
8
The Implementation And Automation Of Software Reliability Assessment Model Using Neuro Fuzzy System
... Dependency on computer aided systems is increasing heavily now a days in the modern era with the evolution of latest concepts, technologies and tools in the field of computer science. At the same time the quality of ...
21
Comparison of Robust Nearest Neighbour fuzzy Rough Classifier (RNN-FRC) with KNN and NEC Classifiers
... Neighbourhood rough set model (NEC) as a uniform framework to understand and implement neighbourhood ...learning. Rough set theory [3], especially fuzzy rough set theory [4], which ...
7
Forecasting Fuzzy Delphi and Hybrid intelligent system for ERP Architecture through the Scientific Private Cloud
... artificial neural networks (ANNs) concept is originated from the biological science (neurons in an ...a neural connection is updated by ...BP neural networks consists of an input layer, ...
7
A Comparison and Analysis of Soft Computing Techniques for Content based Image Retrieval System
... classified training data and RBF network is more appropriate to reflect the subsequent feedback of the user [4]. Initially, the RBF network itself contains off-line trained weight matrices to combine heterogeneous ...
6
A Study & Survey on Rainfall Prediction And Production of Crops Using Data Mining Techniques
... they fuzzy. With such remarkable attributes, fuzzy systems have been widely and successfully applied to control, classification and modeling problems (Mamdani, 1974) (Klir and Yuan, 1995) (Pedrycz and ...
6
Stock Market Prediction with Multiple Regression, Fuzzy Type-2 Clustering and Neural Networks
... type-2 Fuzzy Clustering is implemented to create a prediction ...a Fuzzy type-2 Neural Network is used to perform the reasoning for future stock price ...
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3. Rough convergence of a sequence of fuzzy numbers
... of rough limit set of a sequence of fuzzy numbers and obtain the relation between the set of rough limit and the extreme limit points of a sequence of fuzzy ...the rough limit ...
7
A Study on Rough, Fuzzy and Rough Fuzzy Bi-ideals of Ternary Semigroups
... [1] Chinram R. and Malee, S., “L-Fuzzy ternary subsemirings and L- Fuzzy ideals in ternary semirings,” IAENG International Journal of Applied Mathematics, vol. 40, no. 3, pp. 124-129, 2010. Available: ...
5
Artificial Intelligence Applications for Analysis of E mail Communication Activities
... social networks focuses on finding patterns in the way people interact or contact with each ...of networks being studied under the broad field of complex networks ...Complex networks examines ...
5
Managing business processes using soft computing techniques – a literature review
... Development of computer technologies has allowed companies to process large amounts of data and real time decision making (Huang, Huang, Song & You, 2015). Today, companies use numerous techniques which are based on ...
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