Search Results - (( java implementation modified algorithm ) OR ( pattern gradient tree algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

“…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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An empirical study of pattern leakage impact during data preprocessing on machine learning-based intrusion detection models reliability by Bouke, Mohamed Aly, Abdullah, Azizol

“…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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Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach by Rufus S.A., Ahmad N.A., Abdul-Malek Z., Abdullah N.

“…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). …”

Analysis of banana plant health using machine learning techniques by Thiagarajan, Joshva Devadas, Kulkarni, Siddharaj Vitthal, Jadhav, Shreyas Anil, Waghe, Ayush Ashish, Raja, S.P., Rajagopal, Sivakumar, Poddar, Harshit, Subramaniam, Shamala

“…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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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. The objectives of this work are: i) to provide a comprehensive review of the cloud and scheduling process; ii) to classify the scheduling strategies and scientific workflows; iii) to implement our proposed algorithm with various scheduling algorithms (i.e., Min-Min, Round-Robin, Max-Min, and Modified Max-Min) for performance comparison, within different cloudlet sizes (i.e., small, medium, large, and heavy) in three scientific workflows (i.e., Montage, Epigenomics, and SIPHT); and iv) to investigate the performance of the implemented algorithms by using CloudSim. …”

Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach by Shirley, Rufus, Noor Azlinda, Ahmad, Zulkurnain, Abdul-Malek, Noradlina, Abdullah

“…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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Prediction of Oil Palm Yield Using Machine Learning in the Perspective of Fluctuating Weather and Soil Moisture Conditions: Evaluation of a Generic Workflow by Khan N., Kamaruddin M.A., Ullah Sheikh U., Zawawi M.H., Yusup Y., Bakht M.P., Mohamed Noor N.

“…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. …”

Prevention And Detection Mechanism For Security In Passive Rfid System by Khor, Jing Huey

“…The proposed protocol is designed with lightweight cryptographic algorithm, including XOR, Hamming distance, rotation and a modified linear congruential generator (MLCG). …”
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A Comparative Analysis Using Machine Learning Approach for Thunderstorm Prediction in Southern Region of Peninsular Malaysia by Shirley, Rufus, Noor Azlinda, Ahmad, Zulkurnain, Abdul Malek, Noradlina, Abdullah

“…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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Automatic generation of content security policy to mitigate cross site scripting by Mhana, Samer Attallah, Din, Jamilah, Atan, Rodziah

“…It can be extended to support generating CSP for contents that are modified by JavaScript after loading. Current approach inspects the static contents of URLs.…”
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Enhanced faster region-based convolutional neural network for oil palm tree detection by Liu, Xinni

“…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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Beyond Grades - Predicting Programme Learning Outcomes with Multi-Output Regression in Malaysian Higher Education by Muhammad Noorazizi Abd Ghani, Istas Fahrurrazi Nusyirwan

Recovery of tree community composition across different types of anthropogenic disturbances and characterization of their effect using Landsat time series in Bornean tropical monta... by Keiko Ioki, Daniel James, Phua, Mui How, Satoshi Tsuyuki, Nobuo Imai

“…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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Disparity map algorithm for stereo matching process using local based method by Gan, Melvin Yeou Wei

“…The aim of Stereo Vision Disparity Map (SVDM) algorithm is to obtain the disparity map from two images. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system by Beg, Abul Hashem

“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Factors with retirement behaviour among retirees and pre-retirees identified with a machine learning method / Muhammad Aizat Zainal Alam by Muhammad Aizat , Zainal Alam

“…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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Challenges of hidden data in the unused area two within executable files by Naji, Ahmed Wathik, Zaidan, A.A., Zaidan, B.B.

“…Results: The programs were coded in Java computer language and implemented on Pentium PC. …”
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Fuzzy-based multi-agent approach for reliability assessment and improvement of power system protection by Nadheer Abdulridha, Shalash

“…Meanwhile, the second MAS model has been designed using two agents as follows: the first agent is a fault current agent that is to determine the fault current at all points before and after grounding; the second agent is the time operating of the agent which is used to determine the relay operating time before and after modifying fault current. The simulation results for the first and second models are done using the data obtained from Malaysia distribution network (DISCO-Net) and 69 bus test system that were implemented using Java Agent Development Framework package software. …”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

“…There is also a need to consider implementing this strategy for dynamic object-oriented languages such as Python, Lisp, and Smalltalk.…”
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