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Automatic Microaneurysms Detection for Early Diagnosis of Diabetic Retinopathy Using Improved Discrete Particle Swarm Optimization

Usharani Bhimavarapu, Gopi Battineni
2022 Journal of Personalized Medicine  
The particle swarm optimization clustering combined the membership functions by grouping the high similarity data into clusters.  ...  Different fuzzy models were applied and the outcomes were compared with our probability discrete particle swarm optimization algorithm.  ...  Data Availability Statement: Not applicable. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jpm12020317 pmid:35207805 pmcid:PMC8878235 fatcat:rq6cfmlyqjd7tmpov2nj6i7oe4

Research on the Performance Optimization of Hadoop in Big Data Environment

Jia Min-Zheng
2015 International Journal of Database Theory and Application  
So to improve the particle swarm, integrated the advantages of other algorithms.  ...  Now mainly from two aspects of optimization of particle swarm optimization, on the one hand is to optimize the algorithm convergence speed, on the other hand, focuses on the specific task is optimized.  ...  performance, in standard particle swarm optimization algorithm, the main suitable for continuously differentiable function to search, but the values of discrete function, its performance will become very  ... 
doi:10.14257/ijdta.2015.8.5.26 fatcat:xkngejznxveirmo4e3z7rbkxqm

Combinatorial Clustering Algorithm of Quantum-Behaved Particle Swarm Optimization and Cloud Model

Mi-Yuan Shan, Ren-Long Zhang, Li-Hong Zhang
2013 Mathematical Problems in Engineering  
We propose a combinatorial clustering algorithm of cloud model and quantum-behaved particle swarm optimization (COCQPSO) to solve the stochastic problem.  ...  The fuzzy combinatorial optimization algorithm of cloud model and quantum-behaved particle swarm optimization (FCOCQPSO) in vague sets (IVSs) is more expressive than the other fuzzy sets.  ...  Fuzzy particle swarm optimization clustering algorithm is a novel method for solving real problems by using both the fuzzy rules and the characteristics of particle swarm optimization.  ... 
doi:10.1155/2013/406047 fatcat:3zmj3xxzvnf6lnyvatmfrvibjy

Routing Attacks Detection Method of Wireless Sensor Network

Yongzhong Li, Miao Du, Yi Li
2018 DEStech Transactions on Computer Science and Engineering  
With the deficiency of global search ability for K-means clustering algorithm, K-means clustering algorithm based on particle swarm optimization (PSO-KM) is proposed in this paper.  ...  For the particularity and security threats of wireless sensor networks, we proposed an anomaly detection method based on particle swarm optimization K-means clustering algorithm to detect routing attacks  ...  K-MEANS CLUSTERING ALGORITHM BASED ON PARTICLE SWARM OPTIMIZATION Particle Swarm Optimization (PSO) Particle swarm optimization algorithm [2] [3] [4] [5] is proposed by American social psychology James  ... 
doi:10.12783/dtcse/wicom2018/26273 fatcat:ftlvee7rx5hyto4ezlobycgzra

Particle Swarms: The Second Decade

Riccardo Poli, Jim Kennedy, Tim Blackwell, Alex Freitas
2008 Journal of Artificial Evolution and Applications  
Finally, we would like to thank EPSRC (Extended Particle Swarms project, GR/T11234/01) for financial support. Riccardo Poli Jim Kennedy Tim Blackwell Alex Freitas  ...  ACKNOWLEDGMENTS We would like to thank the Editor-in-Chief, Stefano Cagnoni, for his support in putting together this special issue.  ...  In "A discrete particle swarm optimization algorithm for uncapacitated facility location problem," A. R. Guner and M.  ... 
doi:10.1155/2008/108972 fatcat:7f3uhnr2ufgbxcblo5vjnyru7q

A Systematic Assessment of Numerical Association Rule Mining Methods

Minakshi Kaushik, Rahul Sharma, Sijo Arakkal Peious, Mahtab Shahin, Sadok Ben Yahia, Dirk Draheim
2021 SN Computer Science  
Different authors have presented various algorithms for each numerical association rule mining method; therefore, it is hard to select a suitable algorithm for a numerical association rule mining task.  ...  Initially, the concept of numerical association rule mining started with the discretization method, and later, many other methods, e.g., optimization, distribution are proposed in state-of-the-art.  ...  Particle Swarm Optimization Particle Swarm Optimization (PSO) is a population-based optimization algorithm for nonlinear functions.  ... 
doi:10.1007/s42979-021-00725-2 fatcat:yhtda5qukrgf3hwmso6w4sh5fe

Clustering Stock Exchange data by Using Evolutionary Algorithms for Portfolio Management

Results show superiority of ant colony algorithms and particle swarm optimization algorithm and imperialist competitive to other three methods for clustering stocks.  ...  In present paper, imperialist competitive algorithm and ant colony algorithm and particle swarm optimization algorithm have been used to cluster stocks of Tehran stock exchange.  ...  Three algorithms of imperialist competition, Particle swarm optimization, ant colony have been used for clustering.  ... 
doi:10.35808/ersj/432 fatcat:fiobk2bowjevzdta4hgvngqgii

A New Approach for Data Clustering Based on PSO with Local Search

K. Premalatha, A.M. Natarajan
2008 Computer and Information Science  
In this paper a modification strategy is proposed for the particle swarm optimization (PSO) algorithm and applied in the data sets.  ...  This paper looks into the use of Particle Swarm Optimization (PSO) for cluster analysis.  ...  Therefore, a swarm represents a number of candidates clustering for the current data vectors. Initial Population One particle in the swarm represents one possible solution for clustering.  ... 
doi:10.5539/cis.v1n4p139 fatcat:2jmdjosl2nctpbdqaedbazfpfq

A New K-Means Clustering Algorithm for Customer Classification in Precision Marketing

Xinwu Li, Xiaoling Du
2021 Converter  
Firstly, integrates K-means algorithm with particle swarm optimization according to analyzing the source of the K-means calculation limitations; Secondly, improves the improved algorithm in its operation  ...  K-means is wildly used in data mining and clustering for its powerful data clustering ability, but its inherent limitations affect its application fields and accuracy.  ...  Improving K-means with particle swarm optimization algorithm 3.1Source analysis of the original algorithm limitations The clustering result stability is still a big problem for K-means algorithm when  ... 
doi:10.17762/converter.227 fatcat:ovbi4ss7d5cxfichsb6ptidnc4

Research on the Effect of DPSO in Team Selection Optimization under the Background of Big Data

Qian Zhao, Lian-ying Zhang
2018 Complexity  
By comparing the iterative results of genetic algorithm, ordinary particle swarm algorithm, and discrete particle swarm algorithm, it is found that the DPSO algorithm is effective and preferred in the  ...  The simulation experiment method is used to qualitatively analyze the main parameters of the particle swarm optimization in this paper.  ...  The above selections are calculated using genetic algorithms, ordinary particle swarm optimization algorithms, and discrete particle swarm optimization algorithms.  ... 
doi:10.1155/2018/1386407 fatcat:srnyzarn6rgwpgithy42rtwyt4

Rough Set-Based Dataset Reduction Method Using Swarm Algorithm and Cluster Validation Function

Kuang-Yu Huang, Ting-Hua Chang, Shann-Bin Chang
2015 2015 48th Hawaii International Conference on System Sciences  
A Rough Set (RS) based dataset reduction method using SWARM optimization algorithm and a cluster validation function is proposed.  ...  While many other solutions are possible, the proposed method yields the solution which satisfies the optimal discretization conditions by means of a newly-designed cluster validation index function.  ...  Swarm algorithm PSO is a computational technique for solving combinatorial-type optimization problems [22] .  ... 
doi:10.1109/hicss.2015.180 dblp:conf/hicss/HuangCC15 fatcat:ko7xijfvnnacvp47hbolv6hlrm

Recent Advances in Particle Swarm Optimization for Large Scale Problems

Danping Yan, Yongzhong Lu
2018 Journal of Autonomous Intelligence  
As a branch of the swarm intelligence based algorithms, particle swarm optimization (PSO) for coping with large scale problems and its expansively diverse applications have been in rapid development over  ...  Up to date, how to develop new optimization algorithms for these large scale problems and how to expand the scalability of existing optimization algorithms have posed further challenges in the domain of  ...  Acknowledgments This work is in part supported by the Fundamental Research Funds for the Central Universities in China (HUST: 2016YXMS105).  ... 
doi:10.32629/jai.v1i1.15 fatcat:rqtausu6dbg4jksq62hwbhr3tu

Fuzzy Decision Tree and Particle Swarm Optimization for Mining of Time Series Data

Maya Nayak, Satyabrata Dash
2011 International Journal of Computer Applications  
Particle Swarm Optimization (PSO) technique is used to optimize cluster centers which can be inputs to a fuzzy decision tree for pattern classification of time varying database like the power signal data  ...  inputs to the K-means algorithm for disturbance event detection.  ...  In order to overcome this problem a simpler hybrid K-means clustering algorithm along with Particle swarm optimization (PSO) technique [16, 17] is used for clustering the features into distinct groups  ... 
doi:10.5120/2230-2845 fatcat:fnkavhdemjdsfjl6wa6upmxdwu

A Review of Particle Swarm Optimization Feature Selection Classification and Hybridizations

Madan Madhaw
2015 International Journal on Recent and Innovation Trends in Computing and Communication  
Particle swarm optimization (PSO) is a recently grown, popular, evolutionary and conceptually simple but efficient algorithm which belongs to swarm intelligence category.  ...  Tree Swarm Optimizer as a 12/2015 [43 ] NO Subhajit C PSO, KNN Yes Proposed a PSO- al [13] Induction Algorithm new tool for Data Mining algorithm for Kar et al. [ 44] ,SVM Target or maximum epochs reached  ...  Pseudo code for PSO: 3/2007 Qi Shen C Vector Support particle Proposed swarm discrete Gong Dunwei feature subset.  ... 
doi:10.17762/ijritcc2321-8169.150418 fatcat:xat334s3hrhmbi3gjawi4lqffi

Deployment of Wireless Sensor Networks for Oilfield Monitoring by Multiobjective Discrete Binary Particle Swarm Optimization

Zhen-Lun Yang, Angus Wu, Hua-Qing Min
2016 Journal of Sensors  
The deployment problem is formulated as a constrained multiobjective optimization problem and solved through a novel scheme based on multiobjective discrete binary particle swarm optimization to produce  ...  Simulation results validated that comparing to the three existing state-of-the-art algorithms, that is, NSGA-II, JGGA, and SPEA2, the proposed scheme is superior in locating the Pareto-optimal front and  ...  In this paper, a multiobjective discrete binary particle swarm optimization algorithm is studied in solving the deployment problem of IWSN for oilfield monitoring.  ... 
doi:10.1155/2016/9358358 fatcat:a2bto3ohqvhjhkbqbr3tfjj2ny
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