Search Results - ((centered learning) OR (based learning)) (algorithms OR algorithm)
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A harmony search-based learning algorithm for epileptic seizure prediction
Published 2016“…The proposed harmony search-based learning algorithm is used in the task of epileptic seizure prediction. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
Published 2016“…Nowadays, there are increasingly numbers of studies on seeking ways to mine Twitter for sentiment analysis. Machine learning approach such as immune system based learning methods is an alternative way for sentiment classification.This method is centered on prominent immunological theory as computation mechanisms that emulate processes in biological immune system in achieving higher probability for pattern recognition. …”
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Activity recognition using optimized reduced kernel extreme learning machine (OPT-RKELM) / Yang Dong Rui
Published 2019“…One of the major research problems is the computation resources required by machine learning algorithm used for classification for HAR. …”
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Harmony Search-Based Fuzzy Clustering Algorithms For Image Segmentation
Published 2011“…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.
Published 2011“…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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RECURSIVE LEARNING ALGORITHMS ON RBF NETWORKS FOR NONLINEAR SYSTEM IDENTIFICATION
Published 2010“…This thesis proposes derivative free learning, using finite difference, methods for fixed size RBF network in comparison to gradient based learning for the application of system identification. …”
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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
Published 2022“…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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A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…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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Design of artificial intelligence-based electronic Malay language learning tool for visually impaired children
Published 2011“…The simulation results indicate that the algorithm is able to suggest a word, based on the design settings. …”
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Technical job distribution at BSD SHARP service center using combination of naïve Bayes and K-Nearest neighbour
Published 2022“…In this study, an automatic system based on Machine Learning will be designed for the technicians work distribution by using a combination of k Nearest Neighbor (k-NN) and Naïve Bayes. …”
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A Mininet emulation study for SDN fat tree data center sleep mode routing algorithms
Published 2025“…2024 by the authors; licensee Learning Gate.…”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Super-opposition spiral dynamic-based fuzzy control for an inverted pendulum system
Published 2022“…An improvement on the spiral dynamic algorithm (SDA), this method uses a concept centered on opposition-based learning, which is used to evaluate the fitness of agents at the opposite location to the current solution. …”
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Classification of acute leukemia using image processing and machine learning techniques / Hayan Tareq Abdul Wahhab
Published 2015“…This combination resulted in a new algorithm we named CBCSA. Based on the Relative Ultimate Measurement Accuracy for Area, the proposed algorithm was able to achieve an accuracy of 96% and 94% in the extraction of the blast cell region and the nuclear region, respectively. …”
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Using web questionnaire for web-based course evaluation: advantages and disadvantages
Published 2017“…This article examines some advantages and disadvantages of conducting Web survey research especially for Web-based course evaluation at Iranian university E-learning centers. …”
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Personalized one-shot local adaptation federated learning for mortality prediction in multi-center Intensive Care Unit
Published 2024“…The increasing volumes of electronic healthcare records (EHR) encourage the development of the application and research of machine learning (ML) in digital health. Promoting ML in healthcare based on EHR can enhance health management for increased intelligence, safety, and efficiency. …”
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Clustering ensemble learning method based on incremental genetic algorithms
Published 2012“…In the first and second phases, a threshold fuzzy c-means clustering algorithm as a clusterer and a pattern ensemble learning method based on the incremental genetic-based algorithms are proposed respectively. …”
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Prediction of Ground Surface Deformation Induced by Earthquake on Urban Area Using Machine Learning
Published 2023“…Overall, the four machine learning algorithms have outstanding performance, with a coefficient determinant of more than 0.9. …”
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