Search Results - (( based optimization system algorithm ) OR ( pattern classification using algorithm ))
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1
Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…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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2
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…The aim of data mining is to search and find undetermined patterns in huge databases. A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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3
Animal voice recognition for identification (ID) detection system
Published 2011“…While the voice pattern classification will be done by using DTW algorithm. …”
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4
Dog voice identification (ID) for detection system
Published 2012“…While the voice pattern classification will be done by using DTW algorithm. …”
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5
Evaluation and optimization of frequent association rule based classification
Published 2014“…Problems such as the discovery of random and coincidental patterns or patterns with no significant values, and the generation of a large volume of rules from a database commonly occur. …”
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6
Predicting building damage grade by earthquake: a Bayesian Optimization-based comparative study of machine learning algorithms
Published 2024“…This study compares Bayesian Optimization-based machine learning systems that anticipate earthquake-damaged buildings and to evaluates building damage classification models. …”
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7
Classification of herbs plant diseases via hierarchical dynamic artificial neural network
Published 2010“…Basically, in this study, image processing and pattern classification are going to be used to implement a machine vision system that could identify and classify the visual symptoms of herb plants diseases. …”
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8
Ant system-based feature set partitioning algorithm for classifier ensemble construction
Published 2016“…All of these approaches attempt to generate diversity in the ensemble.However, classifier ensemble construction still remains a problem because there is no standard guideline in constructing a set of accurate and diverse classifiers. In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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9
Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah
Published 2021“…To solving pattern classification problem, the optimization deep learning architecture and parameter by using four convolution layers is set up to classify the three pathological signs; HEM, MA and exudate. …”
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10
Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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11
Classification of herbs plant diseases via hierachical dynamic artificial neural network after image removal using kernel regression framework
Published 2011“…Basically, in this study, image processing and pattern classification are going to be used to implement a machine vision system that could identify and classify the visual symptoms of herb plants diseases. …”
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12
Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune
Published 2024thesis::master thesis -
13
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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14
Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…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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15
Common spatial pattern with feature scaling (FSc-CSP) for motor imagery classification
Published 2017“…Instead of selecting features, the proposed algorithm employs a feature scaling system to scale the importance of each band by using Genetic Algorithm (GA) altogether with Extreme Learning Machine (ELM) as classifier, with 1 signifying the most important bands, declining until 0 for the unused bands, as opposed to the 1 and 0 selection system used in BPSO-CSP. …”
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16
Electromyography signal processing based on time and time-frequency representations for prosthesis application
Published 2014“…The ECS based on pattern recognition has been improved by using new techniques in the EMG signal processing. …”
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17
Diabetic retinopathy detection using fusion of textural and optimized convolutional neural network features / Uzair Ishtiaq
Published 2024“…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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18
Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin
Published 2011“…The system uses neural network for model estimation and classification of several heart diseases. …”
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19
Apply and optimize machine learning algorithms for estimating battery health
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20
Classification of Agarwood using ANN
Published 2012“…The network developed based on three layers feed forward network and the back propagation learning algorithm was used in executing the network training. …”
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