Search Results - (( data classification system algorithm ) OR ( pattern optimization method algorithm ))

Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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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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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm by Yap K.S., Abidin I.Z., Ahmad A.R., Hussien Z.F., Pok H.L., Ismail F.I., Mohamad A.M.

“…It provides an increased convergence and globally optimized solutions. The algorithm has been tested using actual customer consumption data from SESB. 10 fold cross validation method is used to confirm the consistency of the detection accuracy. …”

Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…The aim of this article attempts to study the potential of this method in text classification for sentiment analysis.This study consists of three phases; data preparation; classification model development using three selected Immune System based algorithms i.e. …”
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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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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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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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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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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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A genetic algorithm based fuzzy inference system for pattern classification and rule extraction by Wong S.Y., Yap K.S., Li X.

“…This paper presents a genetic-algorithm-based fuzzy inference system for extracting highly comprehensible fuzzy rules to be implemented in human practices without detailed computation (hereafter denoted as GA-FIS). …”

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.

Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

“…These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq by Uzair , Ishtiaq

“…Combining Local Binary Patterns (LBP) based texture features and deep learning features resulted in the creation of the fused features vector which was then optimized using Binary Dragonfly Algorithm (BDA) and Sine Cosine Algorithm (SCA). …”
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Classification of Agarwood using ANN by M. S., Najib, N. A., Mohd Ali, M. N., Mat Arip, M., Abd Jalil, M. N., Taib

“…Five input neurons, two hidden layer sizes and one output neurons were found to be the optimized combination for the network. The experimental results reveal that the proposed method is effective and significant to the classification of Agarwood region.…”
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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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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

“…The LVQ network was observed to have poor classification for the VOCs data with classification accuracy percentage below 80%. …”
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Classification of agarwood using ANN / Muhammad Sharfi Najib ...[et al.] by Najib, Muhammad Sharfi, Md Ali, Nor Azah (Dr.), Mat Arip, Mohd Nasir, Jalil, Abd Majid, Taib, Mohd Nasir

“…Five input neurons, two hidden layer sizes and one output neurons were found to be the optimized combination for the network. The experimental results reveal that the proposed method is effective and significant to the classification of Agarwood region.…”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…Hitherto, the majority of computer vision approaches have been focused on designing sophisticated algorithms to achieve a robust feature representation for plant data. …”
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Liver segmentation on CT images using random walkers and fuzzy c-means for treatment planning and monitoring of tumors in liver cancer patients by Moghbel, Mehrdad

“…The proposed segmentation is evaluated on real-world clinical data using publicly accessible benchmark clinical liver datasets containing one of the highest numbers of tumors and pathological livers utilized for liver tumor and vasculature segmentation. The proposed method is based on a hybrid method integrating random walkers algorithm with integrated priors and particle swarm optimized spatial fuzzy c-means (FCM) algorithm with level set method and AdaBoost classifier. …”
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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…This new algorithm was developed to overcome the subjectivity of the manual categorization of scale data of landslide conditioning factors, and to predict rainfall-induced susceptibility map in Kuala Lumpur city and surrounding areas using geographic information system (GIS). …”
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