Classifications of Dynamic Clustering based on Soft Computing

Subbalakshmi, Chatti; Krishna, G. Rama; Rao, S. Krishna Mohan

doi:10.17485/ijst/2015/v8i36/78980

Cited by 2 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In other words, the fraction of Mo 5+ ions in such glass samples is relatively low, hence, there is a reduction in the rate of increase of dielectric constant. The plots of variation of tanδ with the temperature for PbO-ZnF 2 -P 2 O 5 :MoO 3 glasses exhibit dipolar relaxation effects due to Mo 5+ ions state in Mo(V)O 3− [34,35]. In the present glass system, beyond 0.2 mol% of MoO 3, we have for the samples from M 3 to M 10 .…”

Section: Discussionmentioning

confidence: 99%

Role of molybdenum ions in lead zinc phosphate glass system by means of dielectric studies

Rao

Raju

Prasad

et al. 2018

Materials Science-Poland

View full text Add to dashboard Cite

PbO-ZnF 2 -P 2 O 5 glasses doped with different mol% (0.1 to 1.0) of MoO 3 have been prepared. Dielectric properties (ω), tanδ, σ AC , of the synthesized samples were calculated from frequency measurements versus temperature. Space charge polarization was used to analyze the temperature and frequency dispersions of dielectric constant (ω) and dielectric loss tanδ. Quantum mechanical tunneling model was employed to explain the origin of AC conductivity. The AC conductivity exhibited an increasing trend with increasing concentration of MoO 3 (up to 0.2 mol%) but the activation energy for conduction decreased. The plots of AC conductivity revealed that the relaxation dynamics depends on MoO 3 dopant concentration.

show abstract

Section: Discussionmentioning

confidence: 99%

Role of molybdenum ions in lead zinc phosphate glass system by means of dielectric studies

Rao

Raju

Prasad

et al. 2018

Materials Science-Poland

View full text Add to dashboard Cite

show abstract

“…The imperative part of the past studies utilized diverse logical models to section customers without considering the association between customer group and a campaign programs [3]. Due to progresses in preparing and information stock stockpiling ranges, huge associations are loading up the data of gigantic measure and the standard logical models are difficult to suspect the partitions [4]. A while later, the information that is useful is more often than not left untouched, and the more noteworthy points of interest of enhanced computational and data gathering capacities are simply recognized in halfway entirety [5].…”

Section: Introductionmentioning

confidence: 99%

Customer Data Clustering using Density based algorithm

Babu¹,

Prasanna²,

Pellakuri³

2018

IJET

View full text Add to dashboard Cite

This paper is about Clustering different segments of customers and their patterns of behaviour over different time intervals which are a very important application for business to maintain Business to Customer (B2C) Relationship. For clustering different segments of customers the input data will be taken from various business organizations like smart retail stores, and other stores. We take the input data from a particular amount of time like a year's data. All this data will be taken from the organization's databases. It has been observed that maintaining the old customers generate more profit when compared to attracting new ones. So, Customer retention is the important factor in our project. The main objective is to identify the elements with high profit and value to group them into different clusters. This will help to identify the high-value low-risk customers. From the results obtained, we can be able to propose some strategies to the organization that helps in retaining the old customers and improve the profits.

show abstract

Classifications of Dynamic Clustering based on Soft Computing

Cited by 2 publications

References 5 publications

Role of molybdenum ions in lead zinc phosphate glass system by means of dielectric studies

Role of molybdenum ions in lead zinc phosphate glass system by means of dielectric studies

Customer Data Clustering using Density based algorithm

Contact Info

Product

Resources

About