Search Results - (( developing knowledge clustering algorithm ) OR ( java simulation optimization algorithm ))
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The implementation of z-numbers in fuzzy clustering algorithm for wellness of chronic kidney disease patients
Published 2019“…Consequently, the implementation of z-numbers in fuzzy clustering algorithm is taken into consideration, where it has more authority to describe the knowledge of human being and extensively used in uncertain information development. …”
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Reliability fuzzy clustering algorithm for wellness of elderly people
Published 2019“…As a consequence, this research will present the idea in developing to design robust and reliable fuzzy clustering particularly in dealing with knowledge of human being.…”
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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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Algorithm Development of Bidirectional Agglomerative Hierarchical Clustering Using AVL Tree with Visualization
Published 2024thesis::doctoral thesis -
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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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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
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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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Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan
Published 2019“…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase
Published 2004“…We proposed KMeans clustering algorithm that is based on multidimensional scaling, joined with neural knowledge based technique algorithm for supporting the learning module to generate interesting clusters that will generate interesting rules for extracting knowledge from stock exchange databases efficiently and accurately.…”
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A Clustering Algorithm for Evolving Data Streams Using Temporal Spatial Hyper Cube
Published 2023“…Evaluation based on both the real world and synthetic datasets has proven the superiority of the developed BOCEDS TSHC clustering algorithm over the baseline algorithms with respect to most of the clustering met-rics. � 2022 by the authors. …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…We divide our problem in two modules.In first module we define Fuzzy Rule Base System to determined vague information in stock exchange databases.After normalizing massive amount of data we will apply our proposed approach, Mining Frequent Patterns with Neural Networks.Future prediction (e.g., political condition, corporation factors, macro economy factors, and psychological factors of investors) perform an important rule in Stock Exchange, so in our prediction model we will be able to predict results more precisely.In second module we will generate clustering algorithm. 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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An adaptive density-based method for clustering evolving data streams / Amineh Amini
Published 2014“…Due to these characteristics the traditional densitybased clustering is not applicable. Recently, a number of density-based algorithms have been developed for clustering data streams. …”
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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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Towards lowering computational power in IoT systems: Clustering algorithm for high-dimensional data stream using entropy window reduction
Published 2024“…Lately, a fully online buffer-based clustering algorithm for handling evolving data streams (BOCEDS) was developed. …”
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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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An Evolutionary Stream Clustering Technique for Outlier Detection
Published 2020“…Clustering data streams appeared to be the most popular studies among the researchers due to their developing field. …”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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