Search Results - (( java application scheduling algorithm ) OR ( using learning tree algorithm ))

Performance evaluation of real-time multiprocessor scheduling algorithms by Alhussian, H., Zakaria, N., Abdulkadir, S.J., Fageeri, S.O.

“…The CPU profiler of JavaTM VisualVM measures the number of invocations of scheduling event handlers (procedures) in each algorithm as well as the total time spent in all invocations of this handler. …”
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A Toolkit for Simulation of Desktop Grid Environment by FOROUSHAN, PAYAM CHINI

“…In this type of environment it is nearly impossible to prove the effectiveness of a scheduling algorithm. Hence the main objective of this study is to develop a desktop grid simulator toolkit for measuring and modeling scheduler algorithm performance. …”
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Computer Lab Timetabling Using Genetic Algorithm Case Study - Unit ICT by Abdullah, Amran

“…Genetic Algorithm is one of the most popular optimization solutions used in various applications such as scheduling. …”
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Improving Class Timetabling using Genetic Algorithm by Qutishat, Ahmed Mohammed Ali

“…This paper reports the power fill techniques using GA in scheduling. Class timetabling problem is one of the applications in scheduling. …”
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Examination timetabling using genetic algorithm case study: KUiTTHO by Mohd Salikon, Mohd Zaki

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Examination Timetabling Using Genetic Algorithm Case Study : KUiTTHO by Mohd. Zaki, Mohd. Salikon

“…This paper reports the powerful techniques using GA in scheduling. Examination timetabling problem is one of the applications in scheduling. …”
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Phylogenetic tree classification system using machine learning algorithm by Tan, Jia Kae

“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Reinforcement Learning Algorithm for Optimising Durian Irrigation Systems: Maximising Growth and Water Efficiency by Ramli, Muhammad Shahrul Azwan, Zainal Abidin, Mohamad Shukri, Hasan, Nor Shahida, Md Reba, Mohd Nadzri, Kolawole, Keshinro Kazeem, Ardiansyah, Rizqi Andry, Mpuhus, Sikudhan Lucas

“…This study presents a Reinforcement Learning-based algorithm designed to optimise irrigation for Durio Zibethinus (i.e., durian) trees, aiming to maximise tree growth and reduce water usage. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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An Intelligent Data-Driven Approach for Electrical Energy Load Management Using Machine Learning Algorithms by Akhtar, Shamim, Muhamad Zahim, Sujod, Rizvi, Syed Sajjad Hussain

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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms by Haw, Jia Yong, Mohd Yousof, Mohd Fairouz, Abd Rahman, Rahisham, Talib, Mohd Aizam, Azis, Norhafiz

“…The algorithms that will be used include boosted trees, RUS boosted trees and subspace KNN, which belongs to the same ensemble group. …”
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Tree-based machine learning in classifying reverse migration/ Azreen Anuar, Nur Huzeima Mohd Hussain and Hugh Byrd by Anuar, Azreen, Mohd Hussain, Nur Huzeima, Byrd, Hugh

“…The findings revealed that tree-based machine learning algorithms performed slightly better than linear-based algorithms in terms of accuracy of prediction, with an improvement of approximately 1%. …”
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Batch mode heuristic approaches for efficient task scheduling in grid computing system by Maipan-Uku, Jamilu Yahaya

“…Many algorithms have been implemented to solve the grid scheduling problem. …”
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Comparison of malware detection model using supervised machine learning algorithms / Syamir Mohd Shahirudin by Mohd Shahirudin, Syamir

“…The objective of this project is to develop the Windows malware detection model using supervised machine learning in Decision Tree, K-NN and Naïve Bayes, to evaluate the performance of malware detection in term of testing and training of the features selection and to compare the accuracy detection model in all three machine learning algorithms. …”
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Prediction of earnings manipulation on Malaysian listed firms: A comparison between linear and tree-based machine learning by Rahman, R.A., Masrom, S., Zakaria, N.B., Nurdin, E., Abd Rahman, A.S.

“…Thus, the aim of the paper is to compare the earnings manipulation prediction models developed by using two types of machine learning algorithms; linear and tree categories. …”
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram by Faris Francis Singaram, Fareena

“…The supervised machine learning algorithm, SVM and Decision Tree are used for the estimation of the mangrove age into young and mature. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
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Detection and classification of conflict flows in SDN using machine learning algorithms by Mutaz Hamed Hussien Khairi, Sharifah Hafizah Syed Ariffin, Nurul Mu'azzah Abdul Latiff, Kamaludin Mohamad Yusof, Mohamed Khalafalla Hassan, Fahad Taha Al-Dhief, Mosab Hamda, Suleman Khan, Muzaffar Hamzah

“…As a result, this paper presents several machine learning algorithms that include Decision Tree (DT), Support Vector Machine (SVM), Extremely Fast Decision Tree (EFDT) and Hybrid (DT-SVM) for detecting and classifying conflicting flows in SDNs. …”
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Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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