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Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…Overall, the VR products developed have proven to be practical and effective in learning programming algorithms. …”
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Design and implemtation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayyawi
Published 2016“…An electronic board, transistor relay driver circuit, is designed for the purpose of establishing communication interface between the computer, adaptive learning algorithm and the actuator mechanism. Design and development an adaptive learning algorithm controller ALAC of position the actuators is presented in real time parallel manipulator based on artificial neural network ANN……”
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Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Machine learning algorithms (ML) are receiving a lot of attention in the development of predictive models for monitoring dengue transmission rates. …”
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Designing algorithm visualization on mobile platform: The proposed guidelines
Published 2017“…This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively.Our previous review indicated that design guidelines of AV on mobile platform are still few.Mostly, previous guidelines of AV are developed for AV on desktop and website platform. …”
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New Approach for E-Commerce Stock Prices Prediction : Combination of Machine Learning and Technical Analysis
Published 2022“…The signals emitted by the technical indicators are used as the features for two machine learning algorithms in predicting the stocks movements. …”
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Classification of Unhealthy Chicken based on Chromaticity of the Comb
Published 2023Conference Paper -
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Automated bilateral negotiation with incomplete information in the e-marketplace.
Published 2011“…Moreover, results indicate that agents equipped by this learning capability can generate Pareto-efficient offers by MGT algorithm. …”
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Waste management using machine learning and deep learning algorithms
Published 2020“…For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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A new machine learning-based hybrid intrusion detection system and intelligent routing algorithm for MPLS network
Published 2023“…This thesis proposes a hybrid ML-based intrusion detection system (ML-IDS) and ML-based intelligent routing algorithm (ML-RA) for MPLS network. The research is divided into three parts, which are (1) dataset development, (2) algorithm development, and (3) algorithm performance evaluation. …”
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Comparison of supervised machine learning algorithms for malware detection / Mohd Faris Mohd Fuzi ... [et al.]
Published 2023“…The results indicated that the Decision Tree and Random Forest algorithms provided the best detection accuracy at 96%, followed by the K-NN algorithm at 95%. …”
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Machine learning approach for automated optical inspection of electronic components
Published 2019“…The factor that affecting the confidence level of the supervised machine learning algorithm is discussed. …”
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Final Year Project / Dissertation / Thesis -
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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The methodology involves data collection, pre-processing, and training the algorithms using k-fold cross-validation. The results indicate that pre-processing steps and dataset characteristics significantly impact algorithm performance. …”
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Implementation of machine learning algorithms for streamflow prediction of Dokan dam
Published 2023“…This study aims at comparing the application of deep learning algorithms and conventional machine learning algorithms for predicting reservoir inflow. …”
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Household overspending model amongst B40, M40 and T20 using classification algorithm
Published 2020“…The attributes are the number of households, area, state, strata, race, highest certificate, marital status, gender, housing, income, total expenditure, and category as attributes class. The model development employs five machine learning algorithms namely decision tree, Naive Bayes, Neural network, Support Vector Machines, Nearest Neighbour. …”
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Classification of diabetic patients with imbalanced class distribution by using a Cost-Sensitive forest algorithm / Ummi Asyiqin Che Muhammad and Muhammad Hasbullah Mohd Razali
Published 2023“…Although many machine learning algorithms have been developed by researchers, the class imbalanced distribution still makes it challenging for classifiers to properly learn and differentiate between the minority and majority classes. …”
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