Search Results - (( intelligence based using algorithm ) OR ( intelligence data clustering algorithm ))

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

“…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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Improvement on agglomerative hierarchical clustering algorithm based on tree data structure with bidirectional approach by Dalbouh H.A., Md Norwawi N.

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Optimizing the Management of Knowledge Assets using Swarm Intelligence by Yusof, Yuhanis, Baharom, Fauziah, Mohamed, Athraa Jasim

“…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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Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield. by Md. Sap, Mohd. Noor, Awan, A. Majid

“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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Intelligent transmission line fault diagnosis using the Apriori associated rule algorithm under cloud computing environment by Al-Jumaili A.H.A., Muniyandi R.C., Hasan M.K., Singh M.J., Paw J.K.S.

“…In this paper, the optimised Apriori association rule algorithm is used as technical support to realise the function of interlocking fault diagnosis in the intelligent fault diagnosis system module. …”

Classification and detection of intelligent house resident activities using multiagent by ,, Mohd. Marufuzzaman, M. B. I., Raez, M. A. M., Ali, Rahman, Labonnah F.

“…The intelligent home research requires understanding of the human behavior and recognizing patterns of activities of daily living (ADL).However instead of understand the psychosomatic nature of human early projects in this area simply employed intelligence to the household appliance.This paper proposed an algorithm for detecting ADL.The proposed method is based on two opposite state entity extraction.The method reflects on the common data flow of smart home event sequence.The developed algorithm clusters the smart home events by isolating opposite status of home appliance. …”
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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

“…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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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

“…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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Hybrid intelligent approach for network intrusion detection by Al-Mohammed, Wael Hasan Ali

“…Due to the prevailing limitations of finding novel attacks, high false detection, and accuracy in previous intrusion detection approaches, this study has proposed a hybrid intelligent approach for network intrusion detection based on k-means clustering algorithm and support vector machine classification algorithm. …”
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Minimizing the number of stunting prevalence using the euclid algorithm clustering approach by Zarlis, Muhammad, Oktavia, Tanty, Buaton, Relita, Ernawan, Ferda, Andrian, Kevin

“…The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

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Expectation maximization clustering algorithm for user modeling in web usage mining system by Mustapha, Norwati, Jalali, Manijeh, Jalali, Mehrdad

“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Multi-objective clustering algorithm using particle swarm optimization with crowding distance (MCPSO-CD) by Rashed, Alwatben Batoul, Hamdan, Hazlina, Mohd Sharef, Nurfadhlina, Sulaiman, Md Nasir, Yaakob, Razali, Abubakar, Mansir

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Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System by Tawafan, Adnan, Sulaiman , Marizan, Ibrahim, Zulkifilie

“…This paper proposes an intelligent algorithm using an adaptive neural- Takagi Sugeno-Kang (TSK) fuzzy modeling approach based on subtractive clustering to detect high impedance fault. …”
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Fuzzy subtractive clustering (FSC) with exponential membership function for heart failure disease clustering by Annisa Eka Haryati, ., Sugiyarto, Surono, Tommy Tanu, Wijaya, Goh, Khang Wen, Aris, Thobirin

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Document clustering using hybrid lda- kmeans by Foong, O.-M., Ismail, A.N.

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Document clustering using hybrid lda- kmeans by Foong, O.-M., Ismail, A.N.

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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

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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

“…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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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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