Search Results - (( pattern ((means algorithm) OR (bees algorithm)) ) OR ( pattern research algorithm ))
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1
Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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2
Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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3
Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms
Published 2019“…This paper investigates the optimization approach of PID controller for double-link flexible robotic manipulator using metaheuristic algorithm. This research focus on population-based metaheuristic that is particle swarm optimization (PSO) and artificial bees algorithm (ABC) to tune the PID control parameters of the system. …”
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Proceeding -
4
Prediction of Rainfall Trends using Mahalanobis-Taguchi System
Published 2025“…Finally, the validation with T mean-based error (Tmbe) using Mean Absolute Error (MAE) revealed a pattern of errors to provide insight to find the significant parameters of MTS. ? …”
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Frequent patterns minning of stock data using hybrid clustering association algorithm
Published 2009“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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Conference or Workshop Item -
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In order to achieve the objective, this research is separated into two phases. Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). …”
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7
Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
Published 2008“…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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8
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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9
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…A comprehensive performance study has been reported that PrefixSpan, one of the sequential pattern mining algorithms, outperforms GSP, SPADE, as well as FreeSpan in most cases, and PrefixSpan integrated with pseudoprojection technique is the fastest among those tested algorithms. …”
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10
Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…Hence, it is critical for an anomaly detection algorithm to detect data anomalies patterns. Nonetheless, the process of detecting anomalies in streaming data is laborious. …”
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11
Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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12
A modified π rough k-means algorithm for web page recommendation system
Published 2018“…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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13
Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images
Published 2024Subjects:Conference Paper -
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Pemahaman guru matematik Tahun Enam tentang pembahagian nombor bulat / Hoi Sim Min
Published 2018“…This study also found that teachers have four general patterns of thought and an algorithm to solve the problem of division of whole numbers, that is, the general pattern of thought of partition, measurement, repeated subtraction, the inverse of multiplication , and long division algorithm. …”
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Thesis -
15
RFID and ZigBee integrated environment for indoor localization
Published 2023“…Engineering research; Nearest neighbor search; Pattern recognition; Radio frequency identification (RFID); Zigbee; Indoor environment; Indoor localization; Indoor localization systems; Indoor locations; Integrated environment; K nearest neighbor algorithm; Wireless technologies; Indoor positioning systems…”
Conference Paper -
16
Clustering of rainfall data using k-means algorithm
Published 2019“…K-Means algorithm is used to obtain optimal rainfall clusters. …”
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17
Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification
Published 2015“…Based on our experimental results, the AP algorithm achieved 93.9 % accuracy rate against all pattern classification techniques including PPCA, KNN, and GMM. …”
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Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…Addition of hybrid automata algorithm to run pattern and non-pattern recognition based control methods is an advantage to increase accuracy in differentiating forward stroke or hand return activity. …”
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19
Biceps brachii surface EMG classification using neural networks
Published 2012“…In this module, statistical features such as mean, maximum, variance and standard deviation are computed to represent the signal pattern. …”
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20
DATA ANALYTICS FOR HOSPITAL OPERATIONS
Published 2015“…Biomedical statistical researchers have experimented algorithms to achieve findings and associations within the aspects of the data given. …”
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Final Year Project
