Search Results - (centered OR centre) ((learning algorithm) OR (learning algorithms))

A Mininet emulation study for SDN fat tree data center sleep mode routing algorithms by Fawzi S., Din N.M.

“…Employing sleep mode aligns with sustainability goals and can reduce the environmental impact of data centers by lowering carbon emissions. In this work meta heuristic algorithm is incorporated at the SDN central controller in a fat tree-based data centre for bandwidth usage monitoring, sleep decisions and path selection using Mininet emulation. …”

A harmony search-based learning algorithm for epileptic seizure prediction by Kee, Huong Lai, Zainuddin, Zarita, Ong, Pauline

“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Artificial intelligent integrated into sun-tracking system to enhance the accuracy, reliability and long-term performance in solar energy harnessing by Tan, Jun You

“…The proposed AI algorithm integrates two deep learning models which are object detection algorithm and reinforcement learning. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…In future work, the accuracy of proposed model can be strengthened by comparative study with other heuristic based searching algorithms such as genetic algorithm, ant colony optimization, swam algorithms and etc.…”
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Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning by Usman F., Nanda, Sumantyo J.T.S.

“…Overall, the four machine learning algorithms have outstanding performance, with a coefficient determinant of more than 0.9. …”

The Evolutionary Convergent Algorithm: A Guiding Path of Neural Network Advancement by Hosseini E., Al-Ghaili A.M., Kadir D.H., Daneshfar F., Gunasekaran S.S., Deveci M.

“…In this study, a new idea centered on seed growth, Seed Growth Algorithm (SGA), as a conditional convergent evolutionary algorithm is proposed for optimizing several discrete and continuous optimization problems. …”

Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui by Yang , Dong Rui

“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Machine learning classifications of multiple organ failures in a malaysian intensive care unit by Norliyana, Nor Hisham Shah, Normy Norfiza, Abdul Razak, Athirah, Abdul Razak, Asma’, Abu-Samah, Fatanah, M. Suhaimi, Ummu Kulthum, Jamaludin

“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. Ninety-eight ICU patients’ data were obtained retrospectively from Universiti Malaya Medical Centre for analysis. …”
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Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit by Shah N.N.H., Razak N.N.A., Razak A.A., Abu-Samah A., Suhaimi F.M., Jamaluddin U.

“…This study demonstrates the performances of different machine learning algorithms in the classification of multiple organ failures. …”

An adaptive opposition-based learning selection: The case for jaya algorithm by Nasser, Abdullah B., Kamal Z., Zamli, Hujainah, Fadhl, Ghanem, Waheed Ali H. M., Saad, Abdul-Malik H. Y., Mohammed Alduais, Nayef Abdulwahab

“…Over the years, opposition-based Learning (OBL) technique has been proven to effectively enhance the convergence of meta-heuristic algorithms. …”
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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION by CATUR ANDRYANI, NUR AFNY

“…The proposed training algorithms discussed in this thesis are derived for fixed size RBF network and being compared with Extreme Learning Machine (ELM) as the ELM technique just randomly assigned centers and width of the hidden neurons and update the output connected weights. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation by Alia, Osama Moh’d Radi

“…Fuzzy clustering algorithms, which fall under unsupervised machine learning, are among the most successful methods for image segmentation. …”
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Harmony search-based fuzzy clustering algorithms for image segmentation. by Alia, Osama Moh’d Radi

“…However, two main issues plague these clustering algorithms: initialization sensitivity of cluster centers and unknown number of actual clusters in the given dataset. …”
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Development of Hybrid Convolutional Neural Network and Radial Basis Function for Autism Spectrum Disorder Classification by Huey Chern, Lim

“…Hence, this study proposed hybrid deep learning algorithms for ASD classification. Two algorithms merged: U-net neural network and Radial Basis Function (RBF) for medical image segmentation. …”
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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour by Pebrianti, Dwi, Ariawan, Angga, Bayuaji, Luhur, Mahdiana, Deni, ,, Rusdah

“…The single Classifier test with the Naïve Bayes algorithm produces the highest accuracy value of 72.7%, while using k-NN algorithm is 81.5%. …”
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Evaluation of deep learning algorithm for inflow forecasting: a case study of Durian Tunggal Reservoir, Peninsular Malaysia by Latif S.D., Ahmed A.N., Sathiamurthy E., Huang Y.F., El-Shafie A.

Change vulnerability forecasting using deep learning algorithm for Southeast Asia by Amelia Ritahani, Ismail, Nur ‘Atikah, Mohd Ali, Junaida, Sulaiman

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A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

“…This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. …”
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Design of artificial intelligence-based electronic Malay language learning tool for visually impaired children by Yeoh, Sing Hsia

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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective by Ul haq, Riaz, Norrozila, Sulaiman, Muhammad, Alam

“…Machine learning algorithms are iteration based algorithms, as the new knowledge is based on the previous predicted /calculated knowledge which helps to decrease errors in order to increase efficiency. …”
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