Improved Distance Power Inverse Ratio Method Based on Spatial Data Mining Technique
نویسندگان
چکیده
منابع مشابه
A Novel Technique for Steganography Method Based on Improved Genetic Algorithm Optimization in Spatial Domain
This paper devotes itself to the study of secret message delivery using cover image and introduces a novel steganographic technique based on genetic algorithm to find a near-optimum structure for the pair-wise least-significant-bit (LSB) matching scheme. A survey of the related literatures shows that the LSB matching method developed by Mielikainen, employs a binary function to reduce the numbe...
متن کاملDiagnosis of diabetes by using a data mining method based on native data
Background & Aim: Detecting the abnormal performance of diabetes and subsequently getting proper treatment can reduce the mortality associated with the disease. Also, timely diagnosis will result in irreversible complications for the patient. The aim of this study was to determine the status of diabetes mellitus using data mining techniques. Methods: This is an analytical study and its databas...
متن کاملMining Association Rules from Relational Data - Average Distance Based Method
The paper describes a new method for association rule discovery in relational databases, which contain both quantitative and categorical attributes. Most of the methods developed in the past are based on initial equi-depth discretization of quantitative attributes. These approaches bring the loss of information. Distance-based methods are another kind of methods. They try to respect the semanti...
متن کاملModel Based Spatial Data Mining for Power Markets
In this paper, we use model-driven data mining techniques to address the issue of realistically assigning service areas to electrical power substations as well as placing substations in a synthetic city. In model based analysis, a system’s state variables and domain knowledge are used to determine the details about the processes underlying the system behavior. This research is motivated by the ...
متن کاملCUSTOMER CLUSTERING BASED ON FACTORS OF CUSTOMER LIFETIME VALUE WITH DATA MINING TECHNIQUE
Organizations have used Customer Lifetime Value (CLV) as an appropriate pattern to classify their customers. Data mining techniques have enabled organizations to analyze their customers’ behaviors more quantitatively. This research has been carried out to cluster customers based on factors of CLV model including length, recency, frequency, and monetary (LRFM) through data mining. Based on LRFM,...
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: DEStech Transactions on Computer Science and Engineering
سال: 2018
ISSN: 2475-8841
DOI: 10.12783/dtcse/aiie2017/18199