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The influence of sentiments in digital currency prediction using hybrid sentiment-based Support Vector Machine with Whale Optimization Algorithm (SVMWOA)
Published 2021“…Support Vector Machine (SVM) technique is used with the Whale Optimization Algorithm (WOA) which is inspired by the swarm optimization algorithms. …”
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Proceeding Paper -
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Improved whale optimization algorithm for feature selection in Arabic sentiment analysis
Published 2019“…In SA, feature selection phase is an important phase for machine learning classifiers specifically when the datasets used in training is huge. Whale Optimization Algorithm (WOA) is one of the recent metaheuristic optimization algorithm that mimics the whale hunting mechanism. …”
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Hybrid feature selection of microarray prostate cancer diagnostic system
Published 2024“…The performance of GA, particle swarm optimization (PSO), and whale optimization algorithm (WOA) is compared in terms of accuracy, computation time, and the number of selected features. …”
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Information fusion and data augmentation with deep features for a deep learning-based baby cry recognition / Zhang Ke
Published 2024“…To validate the effectiveness of the proposed method, examples are analyzed, and applied in baby cry recognition. The Whale optimization algorithm-Variational mode decomposition is used to optimally decompose the baby cry signals. …”
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Thesis -
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Subjects:Conference paper -
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Modeling total quality management in higher education with case-based reasoning
Published 2023Subjects: “…Case-based reasoning (CBR)…”
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Density based subspace clustering: a case study on perception of the required skill
Published 2014“…This thesis proposed subspace clustering based on density connection, named DAta MIning subspace clusteRing Approach (DAMIRA), an improve of subspace clustering algorithm based on density connection. …”
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Density subspace clustering: a case study on perception of the required skill
Published 2014“…This thesis proposed subspace clustering based on density connection, named DAta MIning subspace clusteRing Approach (DAMIRA), an improve of subspace clustering algorithm based on density connection. …”
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Thesis -
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Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat
Published 2020“…Based on the initial study conducted, there are 6 factors that have the potential to influence the number of DHF cases in an area, namely temperature (X1), rainfall (X2), population density (X3), altitude (X4), distribution of males (X5), and distribution of education level (X6). …”
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Algoritma pendaraban nombor perpuluhan dari perspektif pelajar Tingkatan Satu
Published 2001“…Identification of students' algorithms has implications towards the teaching and learning activities and forms a basis in planning teaching strategies of multiplication involving decimals for mathematics educators.…”
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A study on course timetabling for FCSIT
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Final Year Project Report / IMRAD -
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Development of an open-source and low-cost robotic arm based on STM32 microcontroller for promoting STEM education
Published 2023“…The forward kinematic has also been constructed and validated in a simulation-based environment in MATLAB and SolidWorks. The developed kinematics algorithm showed precise Denavit-Hartenberg (DH) characteristics with high accuracy with the worst-case scenario for the kinematic computation error contributes to only 0.26% or 0.0702mm of the end-effector position.…”
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Conference or Workshop Item -
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Students’ attitude towards video-based learning: machine learning analysis with rapid software / Abdullah Sani Abd Rahman ... [et al.]
Published 2022“…The results show that all the three machine learning algorithms produced high accuracy (above 95%) prediction results based on the hold-out testing dataset. …”
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Learning analytic framework for students’ academic performance and critical learning pathways
Published 2024“…The resulting reduced dataset is then subjected to various clustering algorithms, including partition-based clustering (K-means), hierarchical clustering, and density-based clustering (DBSCAN). …”
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