Fuzzy mathematical clustering analysis
Fuzzy clustering is a multifaceted technology that uses fuzzy mathematical methods to classify objective things by establishing fuzzy similarity relationships based on the characteristics, affinity and similarity between them.
The main algorithms are transfer closure method, dynamic direct clustering method and maximum tree method, etc., of which dynamic direct clustering method has the least amount of computation.
In practical applications it is necessary to go through processing steps such as data preprocessing, especially normalization, to select appropriate fuzzy relations to establish fuzzy similarity matrix, and then to perform clustering and pattern recognition.
Application of Fuzzy Cluster Analysis in the Assessment of Students’ Quality
The assessment of students’ quality has an important role in the development of schools.
This paper evaluates students’ quality in five aspects: moral, intellectual, physical, ability and labor.
First of all, the obtained data are specification; then, the fuzzy similarity matrix is constructed; finally, the cluster analysis is carried out by using the netting method for the evaluation of students’ qualities, which is simple and easy to understand and the computation amount is small to achieve the expected results.
Application of fuzzy mathematics in clustering analysis of blood protein polymorphism of livestock and poultry
The research on the polymorphism of animal and plant dung proteins in China has been progressing rapidly, and there are more and more domestic and foreign reports on this. However, this research has a history of nearly one hundred years, and the real development is in the past ten years. China’s late start, the research and application of recent years faster, has been pushed to the ground, the county stage, it can be seen that the popularization of this research and application in China is not far away 1. Southwest College of Nationalities, 2. Xichang Agricultural College 3. This study shows that China’s animal husbandry and veterinary work has entered the molecular level stage. Because the research and method of protein polymorphism is simple, time-saving and money-saving, grassroots units can be applied. However, the key problem of this method is cluster analysis. There are many methods of cluster analysis, such as genetic distance cluster analysis, shortest genetic distance cluster analysis, class average cluster analysis, and genetic similarity coefficient analysis, such as the matrix method, but there is no unified specific analysis method in the cluster analysis of livestock and poultry protein polymorphism. For this reason, we according to the principles of fuzzy mathematics **** theory of genetic similarity coefficients for cluster analysis, is now introduced for colleagues to apply reference. Fuzzy mathematics is the study and treatment of some fuzzy phenomena of mathematics. However, it is not to turn math into fuzzy, but to use fuzzy means to achieve the precise purpose in many control processes. The genetic similarity coefficient is also a common index for cluster analysis in the study of protein polymorphism in livestock and poultry.
Application of fuzzy mathematical cluster analysis in the study of carp hybrid progeny traits
Hybrid carp are similar to their parents, and in mathematical language there is a problem of fuzziness.
Using fuzzy mathematical cluster analysis, we first establish a fuzzy similarity matrix, get the clustering classification mapping of carp growth traits, and finally get the conclusion that the F1 generation of triple-hybrid carp and lotus-won carp is more similar to the parent than the parent.
This has some significance in the theory and production of fish hybrid selection