Search Results - (( developing interactive classification algorithm ) OR ( java optimization swarm algorithm ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Thesis -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…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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Development of interactive application for classification of Artocarpus Species
Published 2020“…The aim of this research is to identify the classification of Artocarpus species by using interactive application and the effectiveness of the interactive application for classification of Artocarpus species. …”
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Undergraduate Final Project Report -
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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Identify texture of MRI human brain using Adaptive Fuzzy C-Means (AFCM) Algorithm / Faridatul Akma Mohd Noor
Published 2010“…The result of this research can be uses for segmentation and classification process. To access its viability, a prototype with interactive graphical user interface (GUI) was developed and tested for its reliability. …”
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Scan Matching and KNN Classification for Mobile Robot Localisation Algorithm
Published 2017“…The mobile robot and the developed algorithm are tested in static environment. …”
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Classification of hand gestures from EMG signals / Diaa Albitar
Published 2022“…This study is to develop classification model to classify six hand gestures using Artificial Intelligent algorithm. …”
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VHDL modeling of EMG signal classification using artificial neural network
Published 2012“…The acquired and processed EMG signal requires classification before utilizing it in the development of interfacing which is the most difficult part of the development process. …”
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Improved building roof type classification using correlation-based feature selection and gain ratio algorithms
Published 2017“…Accurate feature selection is a necessary step to improve the accuracy of classification. This process depends on the number of feature attributes available for interactive synthesis of common characteristics that discriminate different features. …”
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Conference or Workshop Item -
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EMG signal classification for human computer interaction: a review
Published 2009“…This review paper is to discuss the various methodologies and algorithms used for EMG signal classification for the purpose of interpreting the EMG signal into computer command.…”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…This is taking advantage on the discriminative feature provided by both methods, statistical and CSP filter, which is expected to increase the accuracy of the eye state classification algorithm. The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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Intent-IQ: customer’s reviews intent recognition using random forest algorithm
Published 2025“…In order to overcome this problem, a classification model for intent recognition is developed. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…Enhancements in cognitive neuroscience and brain imaging technologies such as Human-Computer Interaction (HCI) have started to provide human with the ability to interact directly with the brain. …”
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Thesis -
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EEG EYE STATE IDENTIFICATION BASED ON STATISTICAL FEATURES AND COMMON SPATIAL PATTERN
Published 2019“…Besides, common spatial pattern (CSP) is the well-known method for classification algorithm in the BCI field. However, application of CSP in EEG eye state classification considered uncommon as compared to motor imagery classification. …”
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Final Year Project -
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Compact Convolutional neural network (CNN) based on SincNet for end-to-end motor imagery decoding and analysis
Published 2021“…In the field of human-computer interaction, the detection, extraction and classification of the electroencephalogram (EEG) spectral and spatial features are crucial towards developing a practical and robust non-invasive EEG-based brain-computer interface. …”
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