Search Results - (( software visualization learning algorithm ) OR ( evolution classification _ algorithm ))
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Algorithm-program visualization model : An intergrated software visualzation to support novices' programming comprehension
Published 2015“…Mostly, conventional programming courses have been delivered based on the programming textbooks with professional developer tools which focus on the syntax or semantic through the coding task. The role of Software Visualization (SV) has been involved to overcome the complexity and problems in the learning programming. …”
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Parse tree visualization for Malay sentence (BMTutor)
Published 2015“…In terms of technology, to date, there is no computer software or a prototype that is available that can help students in learning the BM sentence structure.Thus, BMTutor is introduced as a solution to this problem. …”
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Smart object detection using deep learning algorithm and jetson nano for blind people
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Postsurgery classification of best-corrected visual acuity changes based on Pterygium Characteristics using the Machine Learning Technique
Published 2021“…Conclusion. Machine learning algorithms can produce a highly accurate postsurgery classification model of BCVA changes using pterygium characteristics.…”
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Visual codebook analysis in image understanding / Hoo Wai Lam
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Effectiveness of algorithm visualisation in studying complex algorithms: a case study using TRAKLA Ravie / Chandren Muniyandi, Ali Maroosi
Published 2015“…TRAKLA2 is a visualisation tool used to enhance the process of learning algorithm construction and optimization. To assess the effectiveness of TRAKLA2, students were given an algorithm test prior to being introduced to the software. …”
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Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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Differential evolution for neural networks learning enhancement
Published 2008“…Evolutionary computation is the name given to a collection of algorithms based on the evolution of a population toward a solution of a certain problem. …”
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Hybrid sampling and random forest machine learning approach for software detect prediction
Published 2019“…Cross validation is used to remove overriding problem. Scikit-learn library is used for machine learning algorithms. …”
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…In this regard, this thesis proposes five FS methods for efficient EMG signals classification. The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
Published 2019“…The spectral features were performed by employing the relative spectral powers of delta (δRP), theta (θRP), alpha (αRP), beta (βRP), and gamma (γRP). The differential evolution-based channel selection algorithm (DEFS_Ch) was computed to find the most suitable EEG channels that have the greatest efficacy for identifying the various emotional states of the brain regions. …”
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A New Quadratic Binary Harris Hawk Optimization For Feature Selection
Published 2019“…In this study, twenty-two datasets collected from the UCI machine learning repository are used to validate the performance of proposed algorithms. A comparative study is conducted to compare the effectiveness of QBHHO with other feature selection algorithms such as binary differential evolution (BDE), genetic algorithm (GA), binary multi-verse optimizer (BMVO), binary flower pollination algorithm (BFPA), and binary salp swarm algorithm (BSSA). …”
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Intersection Features For Android Botnet Classification
Published 2019“…This paper proposed an enhancement approach for Android botnet classification based on features selection and classification algorithms. …”
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Malware visualizer: A web apps malware family classification with machine learning
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Enhancing understanding of programming concepts through physical games
Published 2017“…The motivation behind this approach is firstly based on learning style theories that many students are of the kinaesthetic typed compared to the visual and auditory and this is also true in the context of computer science students. …”
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Feature selection optimization using hybrid relief-f with self-adaptive differential evolution
Published 2017“…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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