Search Results - (( based applications out algorithm ) OR ( wave application learning algorithm ))*

An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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An algorithm for Elliott Waves pattern detection by Vantuch, T., Zelinka, I., Vasant, P.

“…The Random Decision Forest and the Support Vector Machine are the machine learning algorithms employed for this task. The accuracy of trend prediction above 70 proves the relevancy of EW patterns on stock market data as well as the validity of the algorithm as a tool for detection of such patterns. …”
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Deep Learning-Driven Mobility And Utility-Based Resource Management In Mm-Wave Enable Ultradense Heterogeneous Networks by Ukasyah bin Mahamod

Market prices trend forecasting supported by Elliott Wave's theory by Vantuch, T., Zelinka, I., Vasant, P.

“…The trend prediction is supported by application of recognized Elliot waves which was performed by custom developed algorithm based on available knowledge about the patterns. …”
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Machine learning approach for stress detection based on alpha-beta and theta-beta ratios of EEG signals by Altaf, Hunain, Ibrahim, Siti Noorjannah, Mohd Azmin, Nor Fadhillah, Asnawi, Ani Liza, Walid, Balqis Hanisah, Harun, Noor Hasmiza

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Water wave optimization with deep learning driven smart grid stability prediction by Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, Alamgeer, Mohammad, K. Nour, Mohamed, Abdelrahman, Anas, Motwakel, Abdelwahed

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A review of wave-net identical learning & filling-in in a decomposition space of (JPG-JPEG) sampled images by Al-Azzawi, Alaa Khamees, Saripan, M. Iqbal, Jantan, Adznan, O. K. Rahmat, Rahmita Wirza

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Machine learning in botda fibre sensor for distributed temperature measurement by Nur Dalilla binti Nordin

Development of an automated detector and counter for bagworm census by Ahmad, Mohd Najib

“…The classification of the larval and pupal stages was carried out by grouping the larval and pupal stages based on their real size; Group 1: larvae stage 1-3, Group 2: larvae stage 4-7 and Group 3: pupal stage. …”
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Neural network approach of harmonics detection by Zin, A.A.M, Rokonuzzaman, M., Shaibon, H., Lo, K.I.

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Optimal power flow using the Jaya algorithm by Warid, Warid, Hizam, Hashim, Mariun, Norman, Abdul Wahab, Noor Izzri

“…Unlike other population-based optimization methods, no algorithm-particular controlling parameters are required for this algorithm. …”
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A web-based implementation of k-means algorithms by Lee, Quan

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Adaptive beamforming algorithm based on Simulated Kalman Filter by Kelvin Lazarus, Lazarus

“…Some of the metaheuristic algorithms have been modified from the original algorithms to improve the algorithms performance in adaptive beamforming application. …”
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An Improved of Channel Allocation for WLAN Using Vertex Merge Algorithm by Mr, Handrizal, Mr, Muhammad Zarlis, Noraziah, Ahmad, Abdalla, Ahmed N.

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A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem by Alharbi, Saad, Venkat, Ibrahim

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A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem by Alharbi, Saad, Venkat, Ibrahim

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Toxic Gas Dispersion Model Based On Neural Pattern Recognition Networks by Roslan, Nurfarah Arina

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Selective opposition based constrained barnacle mating optimization: Theory and applications by Ahmed, Marzia, Mohd Herwan, Sulaiman, Hassan, Md. Maruf, Rahaman, Md. Atikur, Abdullah, Masuk

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On density-based data streams clustering algorithms: A survey by Teh, Y.W.

“…Due to data streams characteristics, the traditional density-based clustering is not applicable. Recently, a lot of density-based clustering algorithms are extended for data streams. …”
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Ramp-rate control smoothing methods to control output power fluctuations from solar photovoltaic (PV) sources�A review by Sukumar S., Marsadek M., Agileswari K.R., Mokhlis H.