Principal Component Analysis and Qualitative Spatial Reasoning
نویسنده
چکیده
In this big data modern age, enormous size of data is a challenge for the computer algorithms as well as hardware because important information is hidden in the data. Principal Component Analysis (PCA) is used to transform the data so that meaningful information becomes explicit. The huge dimensional data can be approximated with a few dimensions. Qualitative Spatial Reasoning (QSR), spatial or network, uses pairwise intersection to determine relations between objects. The 9-Intersection model is commonly used to classify the relations. The performance of QSR can be improved by reducing the number of intersections. PCA has been successfully applied to several domains including image processing, data mining and web document analysis, but its connection to QSR is nonexistent. Herein we show how (1) PCA can be applied to intersection dimension reduction for QSR spatial data, and (2) the 9-Intersection can be reduced to 4-Intersection for all spatial as well as non-spatial objects.
منابع مشابه
Mixed Qualitative/Quantitative Dynamic Simulation of Processing Systems
In this article the methodology proposed by Li and Wang for mixed qualitative and quantitative modeling and simulation of temporal behavior of processing unit is reexamined and extended to more complex case. The main issue of their approach considers the multivariate statistics of principal component analysis (PCA), along with clustered fuzzy digraphs and reasoning. The PCA and fuz...
متن کاملData Reduction and Regression Using Principal Component Analysis in Qualitative Spatial Reasoning and Health Informatics
The central idea of principal component analysis (PCA) is to reduce the dimensionality of a dataset consisting of a large number of interrelated variables, while retaining as much as possible of the variation present in the dataset. In this paper, we use PCA based algorithms in two diverse genres, qualitative spatial reasoning (QSR) to achieve lossless data reduction and health informatics to a...
متن کاملEvaluation and Geographical analysis of the principal components affecting urban economic sustainability, Case study: Cities of Chaharmahal and Bakhtiari Province
Abstract Aims & Backgrounds: Today, economic challenges are one of the most important obstacles to achieving sustainability in the cities of developing countries. Therefore, recognition and geographical analysis of the factors affecting the economic sustainability of cities are among the important goals and priorities of urban and regional planning. Methodology: This research has been done by q...
متن کاملتحلیل فضایی در مطالعات جغرافیایی
Spatial analysis as the main approach of geography was reviewed and searched through its historical development. The results of this exploratory research showed that this approach was born after the Second World War due to the overall interest of geographers to develop universal theories and laws. The advocators of this field believed that the old regional geography was not able to develop ...
متن کاملChemical and Physical Indicators in Drinking Water and Water Sources of Boroujerd Using Principal Components Analysis
Abstract Background and Objective: Quality control of drinking water is important for maintaining health and safety of consumers, and the first step is to study the water quality variables. This study aimed to evaluate the chemical and physical indicators, water quality variables and qualitative classification of drinking water stations and water sources in Boroujerd. Material and Methods...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016