Search Results - (( java implementation phase algorithm ) OR ( using time learning algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…All the algorithm for the engine has been developed by using Java script language. …”
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Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar
Published 2006“…Although from human logical thinking, the route can be generated easily but the calculation of checking the route whether it is optimal route or not is difficult and will take long time to be implemented. This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Improved rsync algorithm to minimize communication cost using multi-agent systems for synchronization in multi-learning management systems
Published 2017“…The experimental results show that the improved rsync (irsync) algorithm yields a better performance against two previous algorithms, rsync algorithm and hierarchical folder synchronization algorithm (HFSA) in terms of reducing computation time and improve synchronization response time. …”
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Comparative study on job scheduling using priority rule and machine learning
Published 2021“…VM is allocated in space-sharing mode all the time. We’ve achieved better for SJF and a decent machine learning algorithm outcome as well.…”
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Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm
Published 2020“…The average accuracy training is 0.9909 and average processing time improved of dynamic algorithm is 430 times faster than the BBP algorithm. …”
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Accelerating learning performance of back propagation algorithm by using adaptive gain together with adaptive momentum and adaptive learning rate on classification problems
Published 2011“…The back propagation (BP) algorithm is a very popular learning approach in feedforward multilayer perceptron networks. …”
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An improved artificial bee colony algorithm for training multilayer perceptron in time series prediction
Published 2014“…Backpropagation (BP) learning algorithm is the well-known learning technique that trained ANN. …”
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9
CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS
Published 2017“…Therefore, this project introduces three learning algorithms which are Extreme Learning Machine (ELM), Finite Impulse Response Extreme Learning Machine (FIR-ELM) and Discrete Fourier Transform Extreme Learning Machine (DFT-ELM) to improve the bearing fault diagnosis accuracy and shorten the time used to train and test the neural network.…”
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Machine Learning Regression Approach for Estimating Energy Consumption of Appliances in Smart Home
Published 2024“…This paper attempts to use machine learning algorithms to estimate the energy consumption of appliances in a smart home environment. …”
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Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage
Published 2010“…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithms. …”
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Ensemble dual recursive learning algorithms for identifying flow with leakage
Published 2010“…The objective of this paper is to introduce a combination of advantages of different algorithm scheme into one learning algorithm. For this purpose, three models is developed, first using recursive least square algorithm (RLS), second using recursive instrument variable (RIV) algorithm and lastly using combination of this two algorithm. …”
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An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM)
Published 2024“…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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15
Financial time series predicting using machine learning algorithms
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Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying
Published 2019“…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
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Classification of fault and stray gassing in transformer by using duval pentagon and machine learning algorithms
Published 2022“…Machine learning algorithms are used to classify the DGA data into normal condition and corresponding faults based on IEEE limits and Duval pentagon method. …”
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Waste management using machine learning and deep learning algorithms
Published 2020“…The model that we have used are the classification models. For our research we did the comparisons between three Machine Learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Decision Tree, and one Deep Learning algorithm called Convolutional Neural Network (CNN), to find the optimal algorithm that best fits for the waste classification solution. …”
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Machine learning algorithms for early predicting dropout student online learning
Published 2023“…This study uses access log data recorded in the LMS and student statistical information and calculated data and aims to present a suitable predictive algorithm for dropout early prediction systems for online learning students using machine learning. …”
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