Search Results - (( using simulation based algorithm ) OR ( using classification technique algorithm ))
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The forms of urban growth can be simulated using satellite remote sensing data and suitable classification technique. …”
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Thesis -
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A Novel Wrapper-Based Optimization Algorithm for the Feature Selection and Classification
Published 2023“…The performance of the proposed SCSO algorithm was compared with six state-of-the-art and recent wrapper-based optimization algorithms using the validation metrics of classification accuracy, optimum feature size, and computational cost in seconds. …”
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Selection and optimization of peak features for event-related eeg signals classification / Asrul bin Adam
Published 2017“…At first, a peak classification algorithm is developed based on the general following processes including peak candidate identification, feature extraction, and classification. …”
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Thesis -
4
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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5
A new ant based rule extraction algorithm for web classification
Published 2011“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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Monograph -
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…Specifically, 6 benchmark classification datasets are used for training the hybrid Artificial Neural Network algorithms. …”
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Thesis -
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An Adaptive Fuzzy Contrast Enhancement Algorithm with Details Preserving
Published 2014“…The classification of an image in the ACEDP technique is done based solely on the intensity range of the maximum number of pixels, which may be inaccurate. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…This is achieved by using a new design algorithm by separating marker TCP and UDP protocols and extended the marking probability for injecting more green and yellow traffic into the network. …”
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Thesis -
10
Oil spill detection and characterization from satellite image using artificial neural network algorithm
Published 2014“…The objective of the algorithm is to classify every pixel of the image whether it is sea water or oil based on its intensity. …”
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Conference or Workshop Item -
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Cyber Terrorist Detection by using Integration of Krill Herd and Simulated Annealing Algorithms
Published 2024“…Two thousand datasets had been used for training and testing with 10-fold cross validation for this research and the simulations were performed using Matlab (R). …”
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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Conference or Workshop Item -
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Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction
Published 2024“…Most computer applications use machine learning and data mining techniques to aid classification and prediction of a disease. …”
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Deep learning-based item classification for retail automation
Published 2025“…Real-time processing was achieved through the integration of object detection algorithms like YOLO and image segmentation techniques. …”
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Final Year Project / Dissertation / Thesis -
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data
Published 2014“…This paper presents a classification technique using Fuzzy Logic Inference System to identify and predict the partial seizure from the epileptic EEG data. …”
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Book Section -
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…For the ANN, Multilayer feed-forward networks are trained using Back Propagation (BP) learning algorithm and for the KNN, is used the most common distance which is Euclidean. …”
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Student Project -
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Electrical impedance tomography with fuzzy logic classification in lung image reconstruction
Published 2021“…Performance of the enhanced image reconstruction is analyzed through simulation on the thorax Finite Element Model (FEM) based on a thorax CT image generated using NETGEN Mesher. …”
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Proceedings -
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Electroencephalography Simulation Hardware for Realistic Seizure, Preseizure and Normal Mode Signal Generation
Published 2015“…The proposed hardware simulator will enhance researchers and hardware validators to simulate, validate and test their detection algorithms forehand, as well as for clinicians to use this system for training as well as for academic exercises. …”
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