Search Results - (( java optimization model algorithm ) OR ( sequence classification system algorithm ))
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Optimization of blood vessel detection in retina images using multithreading and native code for portable devices
Published 2013“…The performance of Java programming model and native programming model are compared with respect to the execution time for blood vessel detection. …”
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A new LoRa based positioning algorithm utilizing sequence based deep learning technique
Published 2023“…Then, a new positioning algorithm is developed which incorporates distance estimation, Kalman Filter and trilateration technique according to the classification with different sequence length data and the positioning error is being analysed. …”
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Protein Sequences Classification Using Modular RBF Neural Networks
Published 2002“…Therefore, there is a need to build an improved classification system for effectively identifying protein sequences. …”
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Book Chapter -
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Development Of Vehicle Tracking And Counting System From Traffic Surveillance Video
Published 2015“…The existing Vehicle Detection and Classification System does not have tracking and counting module implemented. …”
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Fuzzy modeling using Bat Algorithm optimization for classification
Published 2018“…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
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Undergraduates Project Papers -
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The proposed system utilizes Biased ARTMAP for pattern learning and classification. …”
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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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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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Development of Phasor Measurement Unit Based Fault Detection and Faulty Line Classification in Electrical Power System
Published 2019“…Secondly, the study proposes an index for faulty node classification (FNC) based on the positive sequence voltage (PSV) measurements of the pre-fault and post-fault conditions. …”
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An accurate algorithm of PMU-based wide area measurements for fault detection using positive-sequence voltage and unwrapped dynamic angles
Published 2022“…The algorithm includes an index for faulty bus classification based on the positive-sequence voltage measurements of the pre-fault and post-fault conditions, where the bus with a maximum differential percentage is identified as a faulted bus. …”
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Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…The system consists of two main processes, which are classification and detection. …”
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Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023“…To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering. � 2006 IEEE.…”
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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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Evaluation and optimization of frequent association rule based classification
Published 2014“…In this paper, a systematic way to evaluate the association rules discovered from frequent itemset mining algorithms, combining common data mining and statistical interestingness measures, and outline an appropriated sequence of usage is presented. …”
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