MODIFIED ALTERNATIVE DECISION RULE IN THE PRE-CLUSTERING ALGORITHM
نویسندگان
چکیده
منابع مشابه
Alternative KPSO-Clustering Algorithm
This paper presents an evolutionary particle swarm optimization (PSO) learning-based method to optimally cluster N data points into K clusters. The hybrid PSO and K-means algorithm with a novel alternative metric, called Alternative KPSO-clustering (AKPSO), is developed to automatically detect the cluster centers of geometrical structure data sets. The alternative metric is known has more robus...
متن کاملahp algorithm and un-supervised clustering in auto insurance fraud detection
this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...
15 صفحه اولA Modified Clustering Algorithm in WSN
Nowadays many applications use Wireless Sensor Networks (WSN) as their fulfill the purpose of collection of data from a particular phenomenon. Their data centric behavior as well as harsh restrictions on energy makes WSN different from many other networks known. During this work the energy management problem of WSN is studied, by using our proposed modified algorithm. It is a clustering algorit...
متن کاملA Clustering Algorithm in Group Decision Making
The homogeneous requirement of the AHP has stifled its general application and thus hindered the further development of group decision making, which is becoming increasingly popular with the multi-business corporations. In this paper, we adopted the correlation degree of individual preference vectors as the measurement of individuals similarity based on AHP vector space VAHP proposed by Zahir i...
متن کاملA Hybrid Data Clustering Algorithm Using Modified Krill Herd Algorithm and K-MEANS
Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Informatics, Control, Measurement in Economy and Environment Protection
سال: 2016
ISSN: 2083-0157,2391-6761
DOI: 10.5604/20830157.1201309