Search Results - (( pre evaluation case algorithm ) OR ( java implication based algorithm ))
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Case Slicing Technique for Feature Selection
Published 2004“…Case Slicing Technique (CST) helps in identifying the subset of features used in computing the similarity measures needed by classification algorithms. …”
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Modified word representation vector based scalar weight for contextual text classification
Published 2024“…To validate this algorithm, the modified word vectors are compared with original LLM-generated word vectors to evaluate their reflection of the intended context. …”
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Integrating of web 2.0 technologies for interactive courseware : data structure and algorithm as case study
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Final Year Project Report / IMRAD -
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Development of an effective clustering algorithm for older fallers
Published 2022“…The proposed fall risk clustering algorithm grouped the subjects according to features. …”
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Block based low complexity iterative QR precoder structure for Massive MIMO
Published 2021“…We also study one of the suboptimal pre-coding solutions known as Block-diagonalization (BD) applicable in the case where a receiver has multiple antennas and compare their performance. …”
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Collaboration of integrative processes intermediaries supporting supply chain management
Published 2012“…The ongoing interactions are also important after the execution of the pre-planned activities to monitor and restructure the processes in case of deviation occurred in the middle of execution. …”
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Book Chapter -
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Design of QFT-based self-tuning deadbeat controller
Published 2013“…Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. …”
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Design of QFT-based self-tuning deadbeat controller
Published 2013“…Using a grain dryer plant model as a pilot case-study, the performance of the proposed method has been evaluated and analyzed. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment
Published 2021“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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Forecast innovative development level in green supply chains using a comprehensive fuzzy algorithm
Published 2022“…The suggested support vector machine model was also evaluated in 30 case studies, demonstrating that the model is capable of accurately forecasting technological advancement in green supply chains (score: 0.81). …”
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Object detection in aerial images using Convolutional Neural Network (CNN) / Wan Nur Alya Athirah Wan Roshdee
Published 2024“…To solve this aim, several steps will be used including analysis, design, development, evaluation, and documentation phases. It also has been explained about the use of Convolutional Neural Network (CNN) in the project, the advantages and disadvantages, the implementation of the algorithm in various problem and similar works with the project title. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…After evaluating the results of these algorithms, a hybrid Artificial Neural Network-based Imperial Competitive Algorithm (ANN-ICA) was presented in the deployment step of the proposed methodology to identify the structural damage of illustrative structures. …”
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The impact of executive function and aerobic exercise recognition in obese children under deep learning
Published 2025“…The performance of the model before and after optimizations was evaluated to obtain the optimal parameters. Simultaneously, 200 cases of children with simple obesity were recruited as the research subjects and randomly rolled into a control group (CG, conventional aerobic exercise) and an experimental group (EG, aerobic exercise assisted by the optimized OpenPose motion recognition model based on STN and Lucas–Kanade optical flow algorithm). …”
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Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…Conclusion The fndings in this study fll the existing gap of game-induced emotion recognition feld by providing an in-depth evaluation on the ruleset algorithm’s performance and feasibility of applying the generated rules on the game-induced EEG data for justifying the emotional state prediction result.…”
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