Search Results - intelligence based clustering algorithm*

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    Time series data intelligent clustering algorithm for landslide displacement prediction by Han, Liu, Shang, Tao, Shu, Jisen, Khan Chowdhury, Ahmed Jalal

    Published 2018
    “…To address this problem, an intelligent clustering algorithm for time series data in landslide displacement prediction based on nonlinear dynamic time bending is proposed in this paper. …”
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    Development of an intelligent prediction tool for rice yield based on machine learning techniques by Md. Sap, Mohd. Noor, Awan, A. M.

    Published 2006
    “…Whereas kernel-based clustering algorithm is developed for finding clusters in climate data. …”
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    Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin by Nordin, Daarin Nadia

    Published 2020
    “…Thus, this project proposes a solution to the problems by utilizing the machine learning approach which is the Agglomerative clustering algorithm. Previous studies shows that homogenous grouping of autistics students yields positive results, therefore, this project proposes to design and develop a clustering model system known as the CASDSS (Clustering Autism Spectrum Disorder Students System) where the main goal of this system is to create a homogenous grouping of the ASD students based on their behaviour, skills and intelligence. …”
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    Optimizing the Management of Knowledge Assets using Swarm Intelligence by Yusof, Yuhanis, Baharom, Fauziah, Mohamed, Athraa Jasim

    Published 2018
    “…Hence, the produced clusters will be of different quality. This study presents the employment of swarm intelligence algorithm, i.e Firefly Algorithm, to automatically cluster text document without the use of k value. …”
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    An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

    Published 2004
    “…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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    Clustering Based Affinity Propagation In Vanets : Taxonomy And Opportunity Of Research by Talib, Mohammed Saad, Hassan, Aslinda, Abal Abas, Zuraida, Hassan, Ali Abdul Hussian, Ali, Mohanad Faeq, Al-Araji, Zaid Jasim

    Published 2019
    “…This paper is to investigate and analyze several challenges and their present solutions which based on different developed clustering approaches based on the affinity propagation algorithm. …”
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    A Center-Based Stable Evolving Clustering Algorithm With Grid Partitioning And Extended Mobility Features For VANETs by Talib, Mohammed Saad, Abdullah, Nihad Ibrahim, Hassan, Aslinda, Abal Abas, Zuraida, Mohammed Al-Khazraji, Ali Abdul-Jabbar, Alamery, Thamer, Ibrahim, Ali Jalil

    Published 2020
    “…An improvement percentage of the efficiency in (CEC-GP) over the benchmarks Center based stable clustering (CBSC) and evolving data clustering algorithm (EDCA) is 65% and 394% respectively.…”
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    Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

    Published 2005
    “…Intelligent systems based on machine learning techniques, such as classification, clustering, are gaining wide spread popularity in real world applications. …”
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    Centre based evolving clustering framework with extended mobility features for vehicular ad-hoc networks by Talib, Mohammed Saad

    Published 2021
    “…Finally, CEC-GP shows a better stability performance compared with "Centre-based Stable Clustering (CBSC)" and "Evolving Data Clustering Algorithm (EDCA)" based on different performance metrics such as the clustering efficiency, the cluster head, and cluster member duration, the cluster head change rate, and the number of created clusters. …”
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    Clustering Based on Customers’ Behaviour in Accepting Personal Loan using Unsupervised Machine Learning by Lim, Wai Ping, Goh, Ching Pang

    Published 2023
    “…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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    Experimental analysis of firefly algorithms for divisive clustering of web documents by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2014
    “…This paper studies two clustering algorithms that are based on the Firefly Algorithm (FA) which is a recent swarm intelligence approach.We perform experiments utilizing the Newton’s Universal Gravitation Inspired Firefly Algorithm (GFA) and Weight-Based Firefly Algorithm (WFA) on the 20_newsgroups dataset.The analysis is undertaken on two parameters.The first is the alpha (α) value in the Firefly algorithms and latter is the threshold value required during clustering process. …”
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