Search Results - (( variables learning tree algorithm ) OR ( java simulation optimization algorithm ))
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1
Application of Decision Trees in Athlete Selection: A Cart Algorithm Approach
Published 2023“…The focus of this study is on the use of DTs, employing the Classification and Regression Trees (CART) algorithm, in the initial screening of athletes. …”
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2
Ensemble-based machine learning algorithms for classifying breast tissue based on electrical impedance spectroscopy
Published 2020“…Therefore, we aimed to classify six classes of freshly excised tissues from a set of electrical impedance measurement variables using five ensemble-based machine learning (ML) algorithms, namely, the random forest (RF), extremely randomized trees (ERT), decision tree (DT), gradient boosting tree (GBT) and AdaBoost (Adaptive Boosting) (ADB) algorithms, which can be subcategorized as bagging and boosting methods. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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4
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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5
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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6
Prediction of Machine Failure by Using Machine Learning Algorithm
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear reg...
Published 2022“…These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. …”
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9
OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
Review -
10
Predicting dengue transmission rates by comparing different machine learning models with vector indices and meteorological data
Published 2023“…Previous work has focused only on specific weather variables and algorithms, and there is still a need for a model that uses more variables and algorithms that have higher performance. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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13
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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14
Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit
Published 2025“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”
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Decision tree as knowledge management tool in image classification
Published 2008“…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…Several machine learning algorithms which are decision tree, linear discriminant, naïve Bayes, support vector machines, k-nearest neighbor, AdaBoost, and random forest were used for the classification. …”
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Decision tree and rule-based classification for predicting online purchase behavior in Malaysia / Maslina Abdul Aziz, Nurul Ain Mustakim and Shuzlina Abdul Rahman
Published 2024“…The performance of six machine learning models comprising J48, Random Tree, REPTree representing decision trees and JRip, PART, and OneR as rule-based algorithms was assessed. …”
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Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri
Published 2022“…In contrast, machine learning is used to calculate the accuracy assessment of dependent between independent variables. …”
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Random forest algorithm for co2 water alternating gas incremental recovery factor prediction
Published 2020“…RF develops multiple decision trees based on the random selection of the input data and random selection of the variables. …”
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Tree species and aboveground biomass estimation using machine learning, hyperspectral and LiDAR data / Nik Ahmad Faris Nik Effendi
Published 2022“…Besides, Artificial Neural Network (ANN) and Random Forest (RF) algorithm was used to predicted the AGB using different combination of variables. …”
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