Search Results - (( java implementation during algorithm ) OR ( pattern gradient tree algorithm ))
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1
Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…The study primarily focuses on tree-based techniques, including Random Forest (RF), Adaptive Boost (ADABoost), Gradient Boosting Tree (GBT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LGBoost), and Categorical Gradient Boosting (CatBoost). …”
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2
An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability
Published 2023“…We preprocess the data to create versions with and without pattern leakage and train and test six ML models: Decision Tree (DT), Gradient Boosting (GB), K-neighbours (KNN), Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR). …”
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3
Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach
Published 2024“…Then the dataset is trained and tested with five Machine Learning (ML) algorithms, including Decision Trees (DT), Adaptive Boosting (AdaBoost), Random Forest (RF), Extra Trees (ET), and Gradient Boosting (GB). …”
Conference Paper -
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Analysis of banana plant health using machine learning techniques
Published 2024“…The first model ANN with SIFT identify the disease by using the activation functions to process the features extracted by the SIFT by distinguishing the complex patterns. The second integrate the combined features of HOG and LBP to identify the disease thus by representing the local pattern and gradients in an image. …”
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Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach
Published 2023“…Then the dataset is trained and tested with five Machine Learning (ML) algorithms, including Decision Trees (DT), Adaptive Boosting (AdaBoost), Random Forest (RF), Extra Trees (ET), and Gradient Boosting (GB). …”
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Proceeding -
6
Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow
Published 2023“…Selected regression models were compared with Random Forest, Gradient Boosting, Decision Tree, and other non-tree algorithms to prove the R2 driven performance superiority of tree-based ensemble models. …”
Article -
7
Pairwise testing tools based on hill climbing algorithm (PTCA)
Published 2014“…The actual implementation of the algorithm which is in Java programming language, the program is implemented on Net Bean 7.0.1. …”
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Undergraduates Project Papers -
8
A Comparative Analysis Using Machine Learning Approach for Thunderstorm Prediction in Southern Region of Peninsular Malaysia
Published 2023“…Then the dataset is trained and tested using five Machine Learning (ML) algorithms, including Decision Trees (DT), Adaptive Boosting (AdaBoost), Random Forest (RF), Extra Trees (ET), and Gradient Boosting (GB). …”
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9
Enhanced faster region-based convolutional neural network for oil palm tree detection
Published 2021“…The proposed model validated the testing dataset of three palm tree regions with mature, young, and mixed mature and young palm trees. …”
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10
Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education
Published 2025journal-article -
11
Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta...
Published 2022“…We also investigated the use of metrics from spectral trajectories of a Landsat time series (LTS) change detection algorithm (LandTrendr) to identify characteristics of disturbance events and their linkage to the recovery of tree community composition, with field validation. …”
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12
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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13
Disparity map algorithm for stereo matching process using local based method
Published 2022“…The aim of Stereo Vision Disparity Map (SVDM) algorithm is to obtain the disparity map from two images. …”
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14
Talkout : Protecting mental health application with a lightweight message encryption
Published 2022“…The investigation of lightweight message encryption algorithms is conducted with systematic quantitative literature and experiment implementation in Java and Android running environment. …”
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Academic Exercise -
15
Design & Development of a Robotic System Using LEGO Mindstorm
Published 2006“…The system is capable in operating an off-line programming method, starting from its programming sequences until robotic implementation of the program. During early stages, the research is emphasis more towards designing a robotic system using RoboLab software and C++ programming language. …”
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Conference or Workshop Item -
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Data Hiding Techniques In Digital Images
Published 2003“…After all these studies, one of the algorithms in the masking technique is developed and implemented using JAVA program to embed message into true color image with a good quality and higher capacity. …”
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17
Multi-floor indoor location estimation system based on wireless local area network
Published 2007“…Before developing the system, study on characteristics of RSS is conducted to help the design, development and implementation of the proposed system. The proposed system is then designed and developed using Java programming language. …”
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18
Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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19
Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam
Published 2023“…This study uses 3,067 responses which are then be coupled with a machine learning methodology (ranging from Naïve Bayesian, Generalised Linear Model, Logistic Regression, Artificial Neural Network, Decision Tree, Random Forest, and Gradient Boosted Trees) via RapidMiner Studio to expand the understanding of how categories of wealth and expenditures can affect retirement behaviour, given the increasingly important role of machine learning algorithms within the context of behavioural economics where it has been demonstrated to describe patterns and relationships in behavioural data better than standard statistical analysis. …”
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20
A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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