Search Results - (( using optimization methods algorithm ) OR ( pattern classification problem algorithm ))

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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Mussels wandering optimization algorithmn based training of artificial neural networks for pattern classification by Abusnaina, Ahmed A., Abdullah, Rosni

“…Traditional training algorithms have some drawbacks such as local minima and its slowness.Therefore, evolutionary algorithms are utilized to train neural networks to overcome these issues.This research tackles the ANN training by adapting Mussels Wandering Optimization (MWO) algorithm.The proposed method tested and verified by training an ANN with well-known benchmarking problems.Two criteria used to evaluate the proposed method were overall training time and classification accuracy.The obtained results indicate that MWO algorithm is on par or better in terms of classification accuracy and convergence training time.…”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…The focus of this thesis is on solvingclustering and classification problems. Specifically, we will focus on new optimization methods for solving clustering and classification problems. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Feature subset selection and classifier ensemble learning are familiar techniques with high ability to optimize above problems. Recently, various techniques based on different algorithms have been developed. …”
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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

“…ACO classification accuracy is compared to Genetic Algorithm classifier which also a wrapper method. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem by Mohd Pozi, Muhammad Syafiq

“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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Probabilistic ensemble fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms by Loo, C.K., Liew, W.S., Seera, M., Lim, Einly

“…To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection by Too, Jing Wei, Abdullah, Abdul Rahim

“…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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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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A new model for iris data set classification based on linear support vector machine parameter's optimization by Faiz Hussain, Zahraa, Ibraheem, Hind Raad, Alsajri, Mohammad, Ali, Ahmed Hussein, Mohd Arfian, Ismail, Shahreen, Kasim, Sutikno, Tole

“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

“…Neural networks are useful tools for solving many type of problems. These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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Integrated Features by Administering the Support Vector Machine of Translational Initiations Sites in Alternative Polymorphic Context by Nanna Suryana, Herman, Burairah, Hussin

“…Many algorithms and methods have been proposed for classification problems in bioinformatics. …”
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A survey on improvement of Mahalanobis Taguchi system and its application by Tan L.M., Wan Muhamad W.Z.A., Yahya Z.R., Junoh A.K., Azziz N.H.A., Ramlie F., Harudin N., Abu M.Y., Tan X.J.

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Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…Ensemble method is considered as a new direction in pattern classification. …”
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Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

“…It is very important to identify new integration of classification or clustering algorithm especially in neuro fuzzy domain as compared to conventional or traditional method. …”
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Face emotion recognition using artificial intelligence techniques by Kartigayan Muthukaruppan

“…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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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…Besides using solely a single leaf organ to recognize plant species, numerous studies have employed DL methods to solve multi-organ plant classification problem. …”
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Improved Genetic Algorithm Multilayer Perceptron Network For Data Classification by Ahmad, Fadzil

“…The improved GA is then applied for optimization and automatic design of multilayer perceptron (MLP) neural network in solving pattern classification problem. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…Pattern classification and recognition in low-rank distance metric dealing with nonparametric changes is an underlying problem in dynamic environment applications. …”
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