Search Results - ((pattern classification) OR (_ classification)) (problems OR problem)

Multilevel learning in Kohonen SOM network for classification problems by Mohd. Yusof, Norfadzila

“…Classification is the procedure of recognizing classes of patterns that occur in the environment and assigning each pattern to its relevant class. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Fuzzy Min Max Neural Network for pattern classification: An overview of complexity problem by Al Sayaydeh, Osama Nayel, Shamaileh, Abeer

“…Over the last years, the pattern classification is considered one of the most significant domains in artificial intelligence (AI), because it shapes a fundamental in many diverse real live applications where the artificial neural networks (ANNs) and fuzzy logic (FL) are most extensively utilized in pattern classification. …”
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An enhanced generalized adaptive resonance theory neural network and its application to medical pattern classification by Yap K.S., Lim C.P., Mohamad-Saleh J.

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Text classification using modified multi class association rule by Kamaruddin, Siti Sakira, Yusof, Yuhanis, Husni, Husniza, Al Refai, Mohammad Hayel

“…Although previous work proved that Associative Classification produces better classification accuracy compared to typical classifiers, the study on applying Associative Classification to solve text classification problem are limited due to the common problem of high dimensionality of text data and this will consequently results in exponential number of generated classification rules. …”
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A derivative-free optimization method for solving classification problem by Shabanzadeh, Parvaneh, Abu Hassan, Malik, Leong, Wah June

“…Problem statement: The aim of data classification is to establish rules for the classification of some observations assuming that we have a database, which includes of at least two classes. …”
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A survey of fuzzy min max neural networks for pattern classification: variants and applications by Al Sayaydeh, Osama Nayel, Mohammed, Mohammed Falah, Lim, Chee Peng

“…We also summarize the use of FMM and its variants in solving different benchmark and real-world pattern classification problems. In addition, future trends and research directions of FMM-based models are highlighted.…”
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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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Improved two-ways classification for agent patterns by Cheah, Wai Shiang, Masli, Azman Bujang, Mit, Edwin, Abdul Halin, Alfian

“…This paper presents a classification scheme for agent patterns. It is an improvement of the existing pattern classifications. …”
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Flexible enhanced fuzzy min–max neural network model for pattern classification problems by Al-Hroob, Essam Muslem Harb

“…The results demonstrate the efficiency of FEFMM in handling pattern classification problems and providing a superior performance of classification accuracy as compared to the other network structures from the same variants such as EFMM, FMM variants and also non-FMM related models. …”
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An artificial neural network for pattern classification and visualization by Sandra,, Ong Pi Yin.

“…Today, ANN has proven to be able to im itate the human neural network and perform task such as solving real world problems. This study aims to explore in detail an ANN model that is able to perform the task of pattern classification and visualisation , and as well as to evaluate the performance of this model. …”
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Hybrid Computational Intelligence Models With Symbolic Rule Extraction For Pattern Classification by Quteishat, Anas Mohammad Ali

“…This thesis is concerned with the development of hybrid Computational Intelligence (CI) models for tackling pattern classification problems. …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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Grid-Based Classifier as a Replacement for Multiclass Classifier in a Supervised Non-Parametric Approach by Moheb Pour, Majid Reza

“…Pattern recognition/classification has received a considerable attention in engineering fields. …”
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Pattern Recognition for Human Diseases Classification in Spectral Analysis by Nur Hasshima Hasbi, Abdullah Bade, Fuei, Pien Chee, Muhammad Izzuddin Rumaling

“…UV/Vis, IR, and Raman spectroscopy are well-known spectroscopic methods that are used to determine the atomic or molecular structure of a sample in various fields. Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition by Ali Adlan, Hanan Hassan

“…The extraction network extracts detectors that represent pattern’s classes to be supplied to the classification network. …”
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Training a functional link neural network using an artificial bee colony for solving a classification problems by Mohmad Hassim, Yana Mazwin, Ghazali, Rozaida

“…Artificial Neural Networks have emerged as an important tool for classification and have been widely used to classify a non-linear separable pattern. …”
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A modified fuzzy min-max neural network with a genetic-algorithm-based rule extractor for pattern classification by Quteishat, A., Lim, C.P., Tan, K.S.

“…In this paper, a two-stage pattern classification and rule extraction system is proposed. …”
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Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

“…In the recent years, the world has demonstrated an increasing interest in soft computing techniques to deal with complex real world problems. Neural network and fuzzy logic are considered to be one of the most popular soft computing techniques that applied in pattern classification domain. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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