Search Results - (( a distribution clustering algorithm ) OR ( parameter estimation research algorithm ))
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Application of image processing and adaptive neuro-fuzzy system for estimation of the metallurgical parameters of a flotation process
Published 2016“…The authors have already developed some reliable algorithms for measurement of the froth surface visual parameters such as bubble size distribution, froth color, velocity and stability. …”
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A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution
Published 2014“…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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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The findings of this research provide two new iterative algorithms for estimating the parameters of the AFT model with interval-censored data, and also two new resampling techniques for estimating the covariance matrix of estimators. …”
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An observation of different clustering algorithms and clustering evaluation criteria for a feature selection based on linear discriminant analysis
Published 2022“…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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Book Chapter -
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Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution
Published 2014“…Therefore, in this study, a new algorithm called Scheduled-Activity Energy Aware Distributed Clustering (SA-EADC) is proposed. …”
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Beta Distribution Weighted Fuzzy C-Ordered-Means Clustering
Published 2024“…The fuzzy C-ordered-means clustering (FCOM) is a fuzzy clustering algorithm that enhances robustness and clustering accuracy through the ordered mechanism based on fuzzy C-means (FCM). …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…This way, biomedical research’s cell culture can benefit from all this metaheuristic parameter estimation used. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
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Research Reports -
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Clustering Methods For Cluster-Based Routing Protocols In Wireless Sensor Networks: Comparative Study
Published 2017“…Our objective is exploring the literature to present a brief discussion of these algorithms, as well as examine and compare some of distributed, centralized and hybrid clustering algorithm based on several attributes. …”
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Enhanced segment particle swarm optimization for large-scale kinetic parameter estimation of escherichia coli network model
Published 2021“…Thus, this research aimed to estimate large-scale kinetic parameters of the main metabolic pathway of the E. coli model. …”
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Comparison between clustering algorithm for rainfall analysis in Kelantan / Wan Nurshazelin Wan Shahidan and Siti Nurasikin Abdullah
Published 2017“…Comparisons between the clustering algorithms were conducted in this study to identify which clustering algorithm is the most suitable and simple for rainfall distribution. …”
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Optimizing wireless sensor networks: A survey of clustering strategies and algorithms
Published 2024“…This study serves as a helpful source of knowledge that can encourage the further development of the enhancement of clustering algorithms for WSNs in response to modern technology needs.…”
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An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The results from this experiment show estimated optimal kinetic parameters values, shorter computation time, and better accuracy of simulated results compared with other estimation algorithms.…”
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An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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Parallel power load abnormalities detection using fast density peak clustering with a hybrid canopy-K-means algorithm
Published 2025“…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. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…This research is mainly aimed at introducing a deep learning approach to solve chaotic system parameter estimates like the Lorenz system. …”
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Conference or Workshop Item -
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Multi-Hop Selective Constructive Interference Flooding Protocol For Wireless Sensor Networks
Published 2019“…MSCIF integrates three main algorithms: clustering algorithm, selection algorithm, and a synchronized flooding. …”
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