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Clustering Approach In Wireless Sensor Networks Based On K-Means: Limitations And Recommendations
Published 2019“…One of most popular cluster algorithms that utilizing into organize sensor nodes is K-means algorithm. …”
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Development Of Automatic Liver Segmentation Method For Three- Dimensional Computed Tomography Dataset
Published 2018“…The segmentation results from the algorithm developed are competitive. However, improvements still can be made.…”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster labelling process, a cluster labelling algorithm based on calculation of minimum-distance (MD) between cluster mean and class mean was developed to label the clusters. …”
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Harmony Search algorithm-based gasoline consumption modeling for Indonesia
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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
Published 2022“…The density-based spatial clustering of applications with noise (DBSCAN) and the K-means algorithm were used to develop clustering algorithms. …”
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Customer profiling using K-means clustering method / Nik Asyraniasna Nik Mohd Asri
Published 2024“…Through the analysis of various customer data sets, such as people, products, promotion, place, the K-means algorithm can detect clusters that correspond to consistent client groups. …”
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Exploring employee working productivity: initial insights from machine learning predictive analytics and visualization / Mohd Norhisham Razali ... [et al.]
Published 2023“…To address these challenges, we developed a predictive model using machine learning techniques to determine employee productivity within organizations. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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Prediction of device performance in SnO2 based inverted organic solar cells using machine learning framework
Published 2024“…The development of wearable electronic gadgets has spanned the research attention toward the design of flexible and high-performance organic solar cells. …”
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Modeling and optimization of cost-based hybrid flow shop scheduling problem using metaheuristics
Published 2023“…The experimental results proven that ACO performed well regarding mean fitness value for all benchmark problems. Besides this, CPU time for PSO was very high compared to other algorithms. …”
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan
Published 2022“…The aim of this research is to design and develop a routing protocol, which uses less energy through its efficient structural organization and methodology, and keeps the sensor network alive for a longer time. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. …”
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An IoT based system for magnify air pollution monitoring and prognosis using hybrid artificial intelligence technique
Published 2022“…The hypothesized artificial intelligence models are evaluated to the Root Mean Squares Error, Mean Squared Error and Mean absolute error, depending upon the performance measurements and a lower error value model is chosen. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…A similar degree between points was utilized to get similarity density, and then by means of maximum density points selecting them as weights of the Kohonen algorithm. …”
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…The aim of this study is to develop a machine learning (ML) based algorithm to improve the prediction of patient mortality for Malaysian ICU and evaluate the algorithm to determine whether it improves mortality prediction relative to the Simplified Acute Physiology Score (SAPS II) and Sequential Organ Failure Assessment Score (SOFA) scores. …”
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Mortality prediction in critically ill patients using machine learning score
Published 2020“…The aim of this study is to develop a machine learning (ML) based algorithm to improve the prediction of patient mortality for Malaysian ICU and evaluate the algorithm to determine whether it improves mortality prediction relative to the Simplified Acute Physiology Score (SAPS II) and Sequential Organ Failure Assessment Score (SOFA) scores. …”
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A COMPARISON STUDY OF DATA CLUSTERING AND VISUALISATION TECHNIQUES WITH VARIOUS DATA TYPES
Published 2020“…Meanwhile, the results of the predictive accuracy indicated that k-means clustering and self-organizing map (SOM) are the most suitable techniques for cluster analysis. …”
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Final Year Project Report / IMRAD
