Search Results - (( java implementation mining algorithm ) OR ( using long learning 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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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…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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A comparative study of deep learning algorithms in univariate and multivariate forecasting of the Malaysian stock market by Mohd. Ridzuan Ab. Khalil, Azuraliza Abu Bakar

“…Three deep learning algorithms, Multilayer Perceptron (MLP), Convolutional Neural Network (CNN), and Long Short-Term Memory (LSTM), are used to develop the prediction model. …”
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Streamflow Prediction Utilizing Deep Learning and Machine Learning Algorithms for Sustainable Water Supply Management by Latif S.D., Ahmed A.N.

Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

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Rabies Outbreak Prediction Using Deep Learning with Long Short-Term Memory by Abdulrazak Yahya, Saleh, Shahrulnizam, Medang, Ashraf, Osman Ibrahim

“…The results from this research prove that a deep learning LSTM network can predict the disease prevalence, using the rabies datasets, with a good accuracy. …”
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A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

A Systematic Literature Review of Electricity Load Forecasting using Long Short-Term Memory by Salleh N.S.M., Suliman A., J�rgensen B.N.

Machine failure prediction technique using recurrent neural network long short-term memory-particle swarm optimization algorithm by Rashid, N.A., Abdul Aziz, I., Hasan, M.H.B.

“…This paper proposes a hybrid prediction technique based on Recurrent Neural Network Long-Short-Term Memory (RNN-LSTM) with the integration of Particle Swarm Optimization (PSO) algorithm to estimate the Remaining Useful Life (RUL) of machines. …”
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Evaluation of rehearsal effects of multimedia content based on EEG using machine learning algorithms by Mazher, M., Aziz, A.A., Malik, A.S.

“…Three frequency based features are used to discriminate the three learning states mentioned as L1, L2 and L3 using machine learning algorithms. …”
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CLASSIFICATION OF BEARING FAULTS USING EXTREME LEARNING MACHINE ALGORITHMS by TEH, CHOON KEONG

“…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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A Case Study of Using Long Short-Term Memory (LSTM) Algorithm in Solar Photovoltaic Power Forecasting by Lee Chin, Kho, Sze Song, Ngu, Annie, Joseph, Siti Kudnie, Sahari, Kuryati, Kipli, R., Rulaningtyas

“…The results show that the deep learning algorithm provides reliable forecasting results.…”
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Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan by Alwee, Razana, Sallehuddin, Roselina, Shamsuddin, Siti Mariyam

“…The results show that by using a small value of learning rate, Krzyzak algorithm is better than standard back propagation algorithm for medium and long term forecasting.…”
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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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