Search Results - (( code classification methods algorithm ) OR ( wave optimization based algorithm ))
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Android Malware classification using static code analysis and Apriori algorithm improved with particle swarm optimization
Published 2014“…In this method, features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Proceeding Paper -
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Static code analysis of permission-based features for android malware classification using apriori algorithm with particle swarm optimization
Published 2015“…In this method, permission-based features were extracted from Android applications byte-code through static code analysis, selected and were used to train supervised classifiers. …”
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Optimizing the efficiency of Oscillating Water Column (OWC) wave energy converter using genetic algorithm
Published 2015“…This paper, describes a method to maximize the pneumatic system efficiency using optimization technique based on Genetic algorithm. This method involves an extraction of maximum incident wave energy corresponding to the wave height, determining of the best deep water length and maximizing the applied damping ratio which can lead to an increase in the pneumatic system efficiency. …”
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Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model
Published 2021“…In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. …”
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Chain coding and pre processing stages of handwritten character image file
Published 2010“…Each of the pre-processing stages and the chain coding process will be described in detail giving improvised algorithms, and examples of the processes on existing samples from the database shown. …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction
Published 2021“…Therefore, the wind plays an essential role in the oceanic atmosphere and contributes to the formation of waves. This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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Optimized controllers for stabilizing the frequency changes in hybrid wind-photovoltaic-wave energy-based maritime microgrid systems
Published 2024“…Furthermore, an Archimedes optimization algorithm (AOA) is used to optimize the 2DOF-TIDN controller. …”
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Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
Published 2023“…With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. …”
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Conference or Workshop Item -
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks
Published 2025thesis::doctoral thesis -
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Whale Optimisation Freeman Chain Code (WO-FCC) extraction algorithm for handwritten character recognition
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Conference or Workshop Item -
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…The hybrid method was exemplified in a binary classification between digits ‘4’ and ‘9’ from a multiple features dataset. …”
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Final Year Project / Dissertation / Thesis -
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Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning
Published 2016“…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
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Thesis
