Search Results - (( java implementation force algorithm ) OR ( using long learning algorithm ))

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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A review of deep learning and machine learning techniques for hydrological inflow forecasting by Latif S.D., Ahmed A.N.

“…In this study, we look at the long short-term memory deep learning method as well as three traditional machine learning algorithms: support vector machine, random forest, and boosted regression tree. …”

Temporal integration based factorization to improve prediction accuracy of collaborative filtering by Al-Qasem, Al-Hadi Ismail Ahmed

“…The existing temporal-based factorization approaches used the long-term preferences and the short-term preferences. …”
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New Approach for E-Commerce Stock Prices Prediction : Combination of Machine Learning and Technical Analysis by Kelvin Lee, Yong Ming, Mohamad, Jais, Pick Soon, Lee

“…Meanwhile, the machine learning algorithms used in this study were Random Forest (RF) and K-Neighbor Nearest (KNN). …”
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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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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat by Fatima, Jannat

“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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Concrete compressive strength prediction modeling utilizing deep learning long short-term memory algorithm for a sustainable environment by Latif S.D.

Advanced machine learning algorithm to predict the implication of climate change on groundwater level for protecting aquifer from depletion by Ahmed Osman A.I., Latif S.D., Wee Boo K.B., Ahmed A.N., Huang Y.F., El-Shafie A.

“…Therefore, the current study aimed to propose an accurate GWL prediction model using advanced machine learning (ML) algorithms in five populated towns, namely Jenderam, Bangi, Beranang, Kajang, and Paya Indah Wetland which are in Selangor, Malaysia. …”