Search Results - (( java simulation optimization algorithm ) OR ( data operations clustering algorithm ))
Search alternatives:
- operations clustering »
- java simulation »
- data operations »
-
1
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. …”
Get full text
Get full text
Article -
2
Parallelization of noise reduction algorithm for seismic data on a beowulf cluster
Published 2010“…The proposed algorithm has been implemented on an experimental Beowulf cluster which consists of 12 nodes operating on Linux Ubuntu platform. …”
Get full text
Get full text
Citation Index Journal -
3
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. …”
Get full text
Get full text
Get full text
Thesis -
4
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
Get full text
Get full text
Get full text
Monograph -
5
Efficient genetic partitioning-around-medoid algorithm for clustering
Published 2019“…These algorithms mostly built upon the partitioning k-means clustering algorithm. …”
Get full text
Get full text
Thesis -
6
-
7
Application of kohonen neural network and rough approximation for overlapping clusters optimization
Published 2008“…In this paper, the Kohonen Self Organizing Map one of the most popular tools in the exploratory phase of pattern recognition is proposed for clustering the input data. Recently researchers found that to have precise and optimized clustering operations and also to capture the ambiguity that comes from the data sets, it is not necessary to have crisp boundaries in some clustering operation. …”
Get full text
Get full text
Article -
8
Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…The proposed algorithm is used as a pre-processing method for data followed by Gustafson-Kessel (GK) algorithm to classify credit scoring data. …”
Get full text
Get full text
Get full text
Thesis -
9
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. …”
Get full text
Get full text
Get full text
Get full text
Proceedings -
10
Design and analysis of management platform based on financial big data
Published 2023“…In addition, a financial data management platform based on distributed Hadoop architecture is designed, which combines MapReduce framework with the fuzzy clustering algorithm and the local outlier factor (LOF) algorithm, and uses MapReduce to operate in parallel with the two algorithms, thus improving the performance of the algorithm and the accuracy of the algorithm, and helping to improve the operational efficiency of enterprise financial data processing. …”
Get full text
Get full text
Get full text
Article -
11
BASE: a bacteria foraging algorithm for cell formation with sequence data
Published 2010“…The performance of the proposed algorithm is compared with that of a number of algorithms that are most commonly used and reported in the corresponding scientific literature, such as the CASE clustering algorithm for sequence data, the ACCORD bicriterion clustering algorithm and modified ART1, and using a defined performance measure known as group technology efficiency and bond efficiency. …”
Get full text
Get full text
Get full text
Article -
12
Determining number of clusters using firefly algorithm with cluster merging for text clustering
Published 2015“…Such a scenario requires a dynamic text clustering method that operates without initial knowledge on a data collection.In this paper, a dynamic text clustering that utilizes Firefly algorithm is introduced.The proposed, aFAmerge, clustering algorithm automatically groups text documents into the appropriate number of clusters based on the behavior of firefly and cluster merging process. …”
Get full text
Get full text
Book Section -
13
Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks
Published 2024thesis::doctoral thesis -
14
Fireflyclust: an automated hierarchical text clustering approach
Published 2017“…The proposed clustering method operates based on five phases: data pre-processing, clustering, item re-location, cluster selection and cluster refinement. …”
Get full text
Get full text
Get full text
Article -
15
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. …”
Review -
16
K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata
Published 2018“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
Get full text
Get full text
Get full text
Article -
17
Energy efficient geographical and power based clustering algorithm for heterogeneous wireless sensor networks
Published 2011“…To solve this problem in this paper, we propose Geographical and power based clustering algorithm (GPCA): a heterogeneous-aware clustering protocol, which has significant impact on the entire energy dissipation of WSNs. …”
Get full text
Get full text
Conference or Workshop Item -
18
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. …”
Get full text
Get full text
Thesis -
19
Energy Balancing Through Cluster Head Selection Using K-Theorem in Homogeneous Wireless Sensor Networks
“…In cluster based architecture, the role of cluster head is very c rucial for the successful operation of WSN because once the cluster head becomes non functional, the whole cluster becomes dysfunctional. …”
Get full text
Get full text
Conference or Workshop Item -
20
Energy Balancing Through Cluster Head Selection Using K-Theorem in Homogeneous Wireless Sensor Networks
Published 2008“…In cluster based architecture, the role of cluster head is very c rucial for the successful operation of WSN because once the cluster head becomes non functional, the whole cluster becomes dysfunctional. …”
Get full text
Get full text
Conference or Workshop Item
