Search Results - (( data distribution clustering algorithm ) OR ( parameter optimization based algorithm ))*

Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things by Hadi, Ahmed Adnan

“…Therefore, we propose a prominent approach that integrates each of the NN, a meta-heuristic based on an evolutionary genetic algorithm (GA), and a core online-offline clustering (Core). …”
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Hyper-heuristic framework for sequential semi-supervised classification based on core clustering by Adnan, Ahmed, Muhammed, Abdullah, Abd Ghani, Abdul Azim, Abdullah, Azizol, Huyop @ Ayop, Fahrul Hakim

“…This article presents a prominent framework that integrates each of the NN, a meta-heuristic based on evolutionary genetic algorithm (GA) and a core online-offline clustering (Core). …”
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution by Nokhanji, Nooshin

“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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Fuzzy Soft Set Clustering for Categorical Data by Iwan Tri Riyadi, Yanto, Ani, Apriani, Rofiul, Wahyudi, Cheah, Wai Shiang, Suprihatin, in, Rahmat, Hidayat

“…This research provides categorical data with fuzzy clustering technique due to soft set theory and multinomial distribution. …”
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Statistical performance of agglomerative hierarchical clustering technique via pairing of correlation-based distances and linkage methods by Nurshaziana, Mohamad Shamsuri

“…Five tables of summary for choosing appropriate clustering algorithms according to data distribution were produced. …”
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A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution by Nokhanji, Nooshin, Mohd Hanapi, Zurina, Subramaniam, Shamala, Mohamed, Mohamad Afendee

“…Energy aware distributed clustering (EADC) is one of the cluster-based routing protocols proposed for networks with nonuniform node distribution, which can effectively balance the energy consumption among the nodes. …”
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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. …”

A cluster-based hybrid replica control protocol for high availability in data grid by Mabni, Zulaile

“…In Data Grid, data replication is a widely used technique for managing data, where exact copies of data or replicas are created and stored at many distributed sites. …”
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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

“…The data distribution issue remains an unsolved clustering problem in data mining, especially in dealing with imbalanced datasets. …”
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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

“…The data distribution issue remains an unsolved clustering problem in data mining, especially in dealing with imbalanced datasets. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis by Tie, K. H., A., Senawi, Chuan, Z. L.

“…The k-means and the Gaussian mixture distribution were adopted as the clustering algorithms and each algorithm was tested on four datasets with four distinct clustering evaluation criteria: Calinski-Harabasz, Davies-Bouldin, Gap and Silhouette. …”
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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization by Hussain Mohammad Yousef Abu Dalbouh

A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…Black Hole (BH) optimization algorithm has been underlined as a solution for data clustering problems. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Optimizing wireless sensor networks: A survey of clustering strategies and algorithms by Hamim, Sakib Iqram, Azamuddin, Ab Rahman

“…Clustering helps in the distribution of energy evenly in the network minimizing the number of unnecessary transmissions. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Topological Clustering via Adaptive Resonance Theory With Information Theoretic Learning by Masuyama, Naoki, Loo, Chu Kiong, Ishibuchi, Hisao, Kubota, Naoyuki, Nojima, Yusuke, Liu, Yiping

“…Other types of the ART-based topological clustering algorithms have been developed, however, these algorithms have various drawbacks such as a large number of parameters, sensitivity to noisy data. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Development of an effective clustering algorithm for older fallers by Goh, Choon Hian, Wong, Kam Kang, Tan, Maw Pin *, Ng, Siew Cheok, Chuah, Yea Dat, Kwan, Ban Hoe

“…The proposed algorithm was developed through the stages of: data pre-processing, feature identification and extraction with either t-Distributed Stochastic Neighbour Embedding (t-SNE) or principal component analysis (PCA)), clustering (K-means clustering, Hierarchical clustering, and Fuzzy C-means clustering) and characteristics interpretation with statistical analysis. …”
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