Search Results - (( using function method algorithm ) OR ( pattern classification problem algorithm ))
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1
Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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Thesis -
2
Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The architecture provides a novel method to pattern recognition and is expected to be robust to any pattern recognition problem. …”
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3
Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023“…The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering. � 2006 IEEE.…”
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4
Modern fuzzy min max neural networks for pattern classification
Published 2019“…To build an efficient classifier model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Thesis -
5
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The components of the AIRS2 algorithm that pose problems will be modified. This thesis proposes three new hybrid algorithms: The FRA-AIRS2 algorithm uses fuzzy logic to improve data reduction capability of AIRS2 and to solve the linearity problem associated with resource allocation of AIRS. …”
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6
Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context
Published 2012“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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7
A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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8
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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9
Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal
Published 2021“…The simulation results showed that the proposed method outperformed conventional CSP by 6.9% in 2-class and 2.23% in multi-class problem in term of mean classification accuracy.…”
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10
Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Four state-of-the-art algorithms include particle swarm optimization, flower pollination algorithm, butterfly optimization algorithm, and CBGWO are used to examine the effectiveness of proposed methods in feature selection. …”
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11
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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Thesis -
12
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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13
Face emotion recognition using artificial intelligence techniques
Published 2008“…In order to circumvent this problem in recognizing the emotions, two Artificial Intelligence (AI) classification techniques such as neural network and fuzzy clustering are employed. …”
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14
Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification
Published 2017“…Based on the occurrences of the best result obtained by an algorithm across different test functions; it is proven that the proposed method outperforms standard GA. …”
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15
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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16
Integrated framework with association analysis for gene selection in microarray data classification
Published 2011“…The main challenge in building this classification system is the curse of dimensionality problem. …”
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17
FEATURES EXTRACTION OF HEP-2 IMMUNOFLUORESCENCE PATTERNS BASED ON TEXTURE AND REGION OF INTEREST TECHNIQUES
Published 2013“…Next, to design an algorithm that can automatically identify the 2 patterns of the HEp-2 cell tested using ANA. …”
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Final Year Project -
18
Tracking and recognizing the activity of multi resident in smart home environments
Published 2017“…Also enable to foresee the patterns of everyday activities that commonly occur or not in an individual’s routine by considering the simplification and efficient method using the multi label classification framework. …”
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19
Extrema Points Application In Determining Iris Region Of Interest
Published 2019“…Iris recognitionis an automated method of biometric identification that uses mathematical pattern-recognition techniques on the images of one or both irises of an individual' seyes, where the complex patterns are unique, stable, and can be seen from a distance. …”
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20
Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…The use of UV/Vis, IR, and Raman spectroscopy for disease classification is also highlighted. To conclude, many pattern recognition algorithms have the potential to overcome each of their distinct limits, and there is also the option of combining all of these algorithms to create an ensemble of methods.…”
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