Search Results - (( java implementation based algorithm ) OR ( learning process clustering algorithm ))

Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…Today, with online marketing, banking, healthcare and other services, even the average householder is aware of encryption. The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…There are two general paradigms for pattern recognition classification which are supervised and unsupervised learning. The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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An improved pheromone-based kohonen self-organising map in clustering and visualising balanced and imbalanced datasets by Azlin, Ahmad, Rubiyah, Yusof, Nor Saradatul Akmar, Zulkifli, Mohd Najib, Ismail

“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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An Improved Pheromone-Based Kohonen Self- Organising Map in Clustering and Visualising Balanced and Imbalanced Datasets by Ahmad, Azlin, Yusof, Rubiyah, Zulkifli, Nor Saradatul Akma, Ismail, Mohd Najib

“…However, similar to other clustering algorithms, this algorithm requires sufficient data for its unsupervised learning process. …”
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An energy-efficient spectrum-aware reinforcement learning-based clustering algorithm for cognitive radio sensor networks by Mustapha, Ibrahim, Mohd Ali, Borhanuddin, A. Rasid, Mohd Fadlee, Sali, Aduwati, Mohamad, Hafizal

“…In this paper, we propose a reinforcement learning-based spectrum-aware clustering algorithm that allows a member node to learn the energy and cooperative sensing costs for neighboring clusters to achieve an optimal solution. …”
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Quantifying usability prioritization using K-means clustering algorithm on hybrid metric features for MAR learning by Lim K.C., Selamat A., Mohamed Zabil M.H., Selamat M.H., Alias R.A., Puteh F., Mohamed F., Krejcar O.

Analysis of Chinese patents associated with incremental clustering algorithms: A review / Archana Chaudhari by Chaudhari, Archana, Mulay, Preeti, Kumar Tiwari, Amit

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Automatic Number Plate Recognition on android platform: With some Java code excerpts by ., Abdul Mutholib, Gunawan, Teddy Surya, Kartiwi, Mira

“…The main challenges of implementing ANPR algorithm on mobile phone are how to produce a higher coding efficiency, lower computational complexity, and higher scalability. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S., Al-Jumaily A.

“…Parallel power loads anomalies are processed by a fast-density peak clustering technique that capitalizes on the hybrid strengths of Canopy and K-means algorithms all within Apache Mahout's distributed machine-learning environment. …”

An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. …”
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An improved self organizing map using jaccard new measure for textual bugs data clustering by Ahmed, Attika

“…One of the commonly used algorithm for bug clustering is K-means, which is considered a simplest unsupervised learning algorithm for clustering, yet it tends to produce smaller number of cluster. …”
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Classification of JPEG files by using extreme learning machine by Ali, Rabei Raad, Mohamad, Kamaruddin Malik, Jamel, Sapiee, Ahmad Khalid, Shamsul Kamal

“…This paper proposes an Extreme Learning Machine (ELM) algorithm to assign a class label of JPEG or Non-JPEG image for files in a continuous series of data clusters. …”
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Image segmentation using an adaptive clustering technique for the detection of acute leukemia blood cells images by Jabar F.H.A., Ismail W., Salam R.A., Hassan R.

Integrated bisect K-means and firefly algorithm for hierarchical text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

“…However, the Bisect K-means which is a well-known hierarchical clustering algorithm is only able to generate local optimal solutions due to the employment of K-means as part of its process. …”
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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

“…A design proposal was outlined to provide an adaptive client/server approach to stream audio contents using Real-Time Transport Protocol (RTP) involving architecture based on the Java Media Framework (JMF) Application Programmable Interfaces (API).RTP protocol is the Internet-standard protocol for the transport of real-time data, including audio and video and can be implemented by using Java Media Framework (JMF). …”
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Comparative analysis of K-Means and K-Medoids for clustering exam questions / Nurul Zafirah Mokhtar by Mokhtar, Nurul Zafirah

“…The cluster detection algorithm searches for clusters of data which are similar to one another by using similarity measures. …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Data clustering is one of the most popular branches in machine learning and data analysis. …”
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Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

“…Focusing on clustering algorithms, the study employs popular methods like K-Means Clustering, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Agglomerative Hierarchical Clustering, and Mean Shift Clustering to understand customer characteristics and behaviors. …”
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