Search Results - (( simulation computing based algorithm ) OR ( evolution classification system algorithm ))
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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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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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Analysis on target detection and classification in LTE based passive forward scattering radar
Published 2016“…The experimental results confirm the passive FSR system’s capability for ground target detection and classification. …”
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An improved method using fuzzy system based on hybrid boahs for phishing attack detection
Published 2022“…The algorithms involved were Genetic Algorithm, Differential Evolution Algorithm, Particle Swarm Optimization, Butterfly Optimization Algorithm, Teaching-Learning-Based Optimization Algorithm, Harmony Search Algorithm and Gravitational Search Algorithm. …”
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Improving Ant Swarm Optimization With Embedded Vaccination For Optimum Reducts Generation
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…Hence, the numerical simulations take unacceptably more execution time on sequential computers to run the simulation packages. …”
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Incorporating the range-based method into GridSim for modeling task and resource heterogeneity
Published 2017“…As heterogeneity is one of the unique characteristics of Grid computing, which induces additional challenges in designing heuristic-based scheduling algorithms, the main concern when performing simulation experiments for evaluating the performance of scheduling algorithms is how to model and simulate different Grid scheduling scenarios or cases that capture the inherent nature of heterogeneity of Grid computing environment. …”
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Image Template Matching Based on Simulated Kalman Filter (SKF) Algorithm
Published 2018“…A novel approach to the image matching based on Simulated Kalman Filter (SKF) algorithm has been proposed in this paper. …”
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Fault tolerance structures in Wireless Sensor Networks (WSNs): survey, classification, and future directions
Published 2022“…Thus, the respective underlying Fault Tolerance (FT) structure is a critical requirement that needs to be considered when designing any algorithm in WSNs. Moreover, with the exponential evolution of IoT systems, substantial enhancements of current FT mechanisms will ensure that the system constantly provides high network reliability and integrity. …”
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PSAT : a pairwise test data generation tool based on simulated annealing algorithm
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Undergraduates Project Papers -
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Batch mode heuristic approaches for efficient task scheduling in grid computing system
Published 2016“…We simulate our proposed algorithms using a Java based simulator that is purposedly built for Grid computing simulations. …”
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Deep learning detector for pests and plant disease recognition
Published 2020“…And developing a quick and accurate model could help in detecting pests and diseases in plants. Meanwhile, evolution in deep convolutional neural networks for image classification has rapidly improved the accuracy of object detection, classification and system recognition. …”
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Final Year Project / Dissertation / Thesis -
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Hybrid test redundancy reduction strategy based on global neighborhood algorithm and simulated annealing
Published 2018“…Given such prospects, this research explores a hybrid test redundancy reduction strategy based on Global Neighborhood Algorithm and Simulated Annealing, called GNA_SA. …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Benchmark simulator with dynamic environment for job scheduling in grid computing
Published 2014“…Job scheduling algorithm has a significant influence on grid computing performance. …”
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