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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Software Classification Using Structure-Based Descriptors
Published 2009“…A total of 2800 programs have been used during the training process while two different datasets of size (28) were used for testing. …”
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3
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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4
Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…The design network is trained by presenting several target machining data that the network must learn according to a learning rule (algorithm). …”
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5
Academic Achievement Prediction Model Using Neural Networks
Published 2002“…The system can predict the result of Programming I subject based on the student's background during the Sijil Pelajaran Malaysia (SPM) examination. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…This knowledge is then converted into computer program or by utilizing exhaustively trained and tested Artificial Intelligence (AI) algorithm. …”
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7
An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…DL models often use gradient descent optimization, i.e., the Back-Propagation (BP) algorithm; therefore, their training and optimization procedures suffer from local sub-optimal solutions. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms
Published 2024“…We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%.…”
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11
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The simulation results from the selected ANFIS and ANN models during training, validation and testing revealed the superiority of the ANN model. …”
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Synthetic pterygium images using Style Generative Adversarial Networks (SGANs)
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Human activity recognition via accelerometer and gyro sensors
Published 2023“…To prevent overfitting, early stopping is used to monitor validation loss during training and dropout rate of 0.3 are applied. …”
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Predicting Post-Internship Employability Using Ensemble Machine Learning Approach
Published 2024“…These findings underscore the importance of robust internship programs in enhancing graduate outcomes. Future research could explore the competencies developed during internships and their correlation with job success.…”
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AI chatbot system for educational institutions
Published 2023“…Users can seamlessly apply for programs, check application statuses, and schedule campus visits, all while enjoying a user-friendly experience. …”
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Enhanced dynamic security assessment for power system under normal and fake tripping contingencies.
Published 2019“…The training dataset is built by applying all possible contingencies during normal and fake tripping scenarios to the test system models. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…In particular. nonverbal HRI plays an important role in social interactions, which highlights the need to accurately detect the subject's attention by evaluating the programmed cues. In this paper, a conceptual attentiveness model algorithm called attentive Recognition Model (ARM) is proposed to recognize a person's aii:ontiveness, which improves the of detection and subjective experience during nonverbal ARI using three combined detection models: face tracking, iris tracking and eye blinking. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…In particular. nonverbal HRI plays an important role in social interactions, which highlights the need to accurately detect the subject's attention by evaluating the programmed cues. In this paper, a conceptual attentiveness model algorithm called attentive Recognition Model (ARM) is proposed to recognize a person's aii:ontiveness, which improves the of detection and subjective experience during nonverbal ARI using three combined detection models: face tracking, iris tracking and eye blinking. …”
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NON-VERBAL HUMAN-ROBOT INTERACTION USING NEURAL NETWORK FOR THE APPLICATION OF SERVICE ROBOT
Published 2023“…In particular. nonverbal HRI plays an important role in social interactions, which highlights the need to accurately detect the subject's attention by evaluating the programmed cues. In this paper, a conceptual attentiveness model algorithm called attentive Recognition Model (ARM) is proposed to recognize a person's aii:ontiveness, which improves the of detection and subjective experience during nonverbal ARI using three combined detection models: face tracking, iris tracking and eye blinking. …”
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