scholarly journals Fuzzy Cluster Analysis and Prediction of Psychiatric Health Data Based on BPNN

2022 ◽  
Vol 16 ◽  
pp. 497-503
Author(s):  
Hong Xiang ◽  
Anrong Wang ◽  
Guoqun Fu ◽  
Xue Luo ◽  
Xudong Pan
Keyword(s):  
Neural Network ◽  
Mental Disorders ◽  
Test Data ◽  
Fuzzy Clustering ◽  
Clustering Analysis ◽  
Scientific Basis ◽  
Behavioral Characteristics ◽  
Early Prevention ◽  
Fuzzy Clustering Analysis ◽  
Internal Relations

PMH (psychiatry/mental health) is affected by many factors, among which there are numerous connections, so the prediction of PMH is a nonlinear problem. In this paper, BPNN (Back Propagation Neural Network) is applied to fuzzy clustering analysis and prediction of PMH data, and the rules and characteristics of PMH and behavioral characteristics of people with mental disorders are analyzed, and various internal relations among psychological test data are mined, thus providing scientific basis for establishing and perfecting early prevention and intervention of mental disorders in colleges and universities. Artificial neural network is a mathematical model of information processing, which is composed of synapses similar to the structure of brain neurons. The fuzzy clustering analysis and data prediction ability of optimized PMH data are obviously improved. Applying BPNN to the fuzzy clustering analysis and prediction of PMH data, analyzing the rules and characteristics of PMH and the behavioral characteristics of patients with mental disorders, can explore various internal relations among psychological test data, and provide scientific basis for establishing early prevention and intervention of mental disorders.

A Study on the Application of Fuzzy Clustering Analysis in Juvenile Delinquency Prevention

2013 ◽  
Vol 12 (7) ◽  
pp. 1358-1365
Author(s):  
Yau-Ren Shiau ◽  
Ching-Hsing Tsai ◽  
Yung-Hsiang Hung ◽  
Jui-Huan Wu
Keyword(s):  
Juvenile Delinquency ◽  
Fuzzy Clustering ◽  
Clustering Analysis ◽  
Delinquency Prevention ◽  
Fuzzy Clustering Analysis

scholarly journals Fuzzy clustering analysis to study geomagnetic coastal effects

2005 ◽  
Vol 23 (4) ◽  
pp. 1157-1163 ◽  
Author(s):  
M. Sridharan ◽  
N. Gururajan ◽  
A. M. S. Ramasamy
Keyword(s):  
Cluster Analysis ◽  
Fuzzy Clustering ◽  
Computer Technology ◽  
Clustering Analysis ◽  
East Coast ◽  
Equatorial Electrojet ◽  
Analytical Technique ◽  
Fuzzy Clustering Analysis ◽  
The Subject

Abstract. The utility of fuzzy set theory in cluster analysis and pattern recognition has been evolving since the mid 1960s, in conjunction with the emergence and evolution of computer technology. The classification of objects into categories is the subject of cluster analysis. The aim of this paper is to employ Fuzzy-clustering technique to examine the interrelationship of geomagnetic coastal and other effects at Indian observatories. Data from the observatories used for the present studies are from Alibag on the West Coast, Visakhapatnam and Pondicherry on the East Coast, Hyderabad and Nagpur as central inland stations which are located far from either of the coasts; all the above stations are free from the influence of the daytime equatorial electrojet. It has been found that Alibag and Pondicherry Observatories form a separate cluster showing anomalous variations in the vertical (Z)-component. H- and D-components form different clusters. The results are compared with the graphical method. Analytical technique and the results of Fuzzy-clustering analysis are discussed here.

Research on User Clustering of Recommended System Based on Fuzzy Clustering

2014 ◽  
Vol 513-517 ◽  
pp. 1540-1544
Author(s):  
Li Hua Zhang ◽  
Wei Liu
Keyword(s):  
Fuzzy Clustering ◽  
Clustering Analysis ◽  
Recommendation System ◽  
Information Overload ◽  
Fuzzy Clustering Analysis ◽  
User Clustering ◽  
Objective Classification ◽  
Distance Education System ◽  
High Quality Service

Today's society is a society of information explosion, the popularity of the Internet and development bring a lot of convenience to people, people can easily get a lot of information on the network, however, facing so many information, people prone to the problems of "information overload" and "resources disorientation. Therefore, the recommended system came into being, the recommendation system can provide people with the most in need and most concern to avoid the time of the search and comparison. This article intends to use the very mature recommendation system in the field of electronic commerce to distance education system and promotes personalized learning, shifting the traditional "what teachers teach, what students receive" to "what the students need, what the system provides, which is consistent of constructivism study philosophy. The analysis of users interested as the basis of the recommendation system, users clustering is very important, the objective classification of fuzzy clustering analysis can recommend for users to enjoy high-quality service.

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