Search Results - (( java simulation optimization algorithm ) OR ( data identification clustering algorithm ))
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Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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Development of an effective clustering algorithm for older fallers
Published 2022“…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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An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding
Published 2020“…Data entities may belongs to further than one cluster in the fuzzy clustering (soft clustering), and a set of membership levels are allied with each group. …”
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An efficient fuzzy clustering algorithm for mining user session clusters on web log data
Published 2021“…In addition, the methodologies to preprocess the net log data as well as data cleanup client identification and session identification are going to be mentioned. …”
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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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RFID-enabled supply chain detection using clustering algorithms
Published 2015“…Based on evaluation that have done, we found that Farthest First is the best algorithm for 1000 (small data) and 10000 (bigger data). …”
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Document clustering for knowledge discovery using nature-inspired algorithm
Published 2014“…As the internet is overload with information, various knowledge based systems are now equipped with data analytics features that facilitate knowledge discovery.This includes the utilization of optimization algorithms that mimics the behavior of insects or animals.This paper presents an experiment on document clustering utilizing the Gravitation Firefly algorithm (GFA).The advantage of GFA is that clustering can be performed without a pre-defined value of k clusters.GFA determines the center of clusters by identifying documents with high force.Upon identification of the centers, clusters are created based on cosine similarity measurement.Experimental results demonstrated that GFA utilizing a random positioning of documents outperforms existing clustering algorithm such as Particles Swarm Optimization (PSO) and K-means.…”
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Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering
Published 2004“…Similar data then undergoes fuzzy c-means iterative process to determine their cluster centers. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…The simulation is implemented with iFogSim and java programming language. …”
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Clustering includes the identification of subsets of the data that are similar. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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A modified π rough k-means algorithm for web page recommendation system
Published 2018“…Hence, this study carried out several objectives to augment the support of modified clustering algorithm. Firstly, an extended K-Means clustering algorithm (called X-Means algorithm) is proposed to filter/remove the noise from user session data to eliminate outliers or irrelevant pages. …”
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Frequent patterns minning of stock data using hybrid clustering association algorithm
Published 2009“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…As these clustering algorithms require the number of clusters as input parameter of the algorithms, the study of number of clusters for the clustering is served as focus in this paper. …”
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Proceedings -
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT
Published 2023“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”
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A hybrid of fuzzy c-means clustering and Latent Dirichlet Allocation for analysing philanthropic corporate social responsibility activities / Nik Siti Madihah Nik Mangsor
Published 2023“…Then, text pre-processing for data cleaning was performed followed by identification of the best Latent Dirichlet Allocation (LDA) topic modelling technique that was used to integrate document clustering.…”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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