scholarly journals CPRQ: Cost Prediction for Range Queries in Moving Object Databases

2021 ◽  
Vol 10 (7) ◽  
pp. 468
Author(s):  
Shengnan Guo ◽  
Jianqiu Xu
Keyword(s):  
Random Forest ◽  
Regression Model ◽  
Polynomial Regression ◽  
Database Management System ◽  
Moving Object ◽  
Cost Prediction ◽  
Random Forest Regression ◽  
Object Databases ◽  
Tree Regression Model ◽  
Moving Object Databases

Predicting query cost plays an important role in moving object databases. Accurate predictions help database administrators effectively schedule workloads and achieve optimal resource allocation strategies. There are some works focusing on query cost prediction, but most of them employ analytical methods to obtain an index-based cost prediction model. The accuracy can be seriously challenged as the workload of the database management system becomes more and more complex. Differing from the previous work, this paper proposes a method called CPRQ (Cost Prediction of Range Query) which is based on machine-learning techniques. The proposed method contains four learning models: the polynomial regression model, the decision tree regression model, the random forest regression model, and the KNN (k-Nearest Neighbor) regression model. Using R-squared and MSE (Mean Squared Error) as measurements, we perform an extensive experimental evaluation. The results demonstrate that CPRQ achieves high accuracy and the random forest regression model obtains the best predictive performance (R-squared is 0.9695 and MSE is 0.154).

A Survey of Spatio-Temporal Data Warehousing

2010 ◽  
pp. 949-977
Author(s):  
Leticia Gómez ◽  
Bart Kuijpers ◽  
Bart Moelans ◽  
Alejandro Vaisman
Keyword(s):  
Moving Objects ◽  
Route Planning ◽  
Geographic Information ◽  
Moving Object ◽  
Attribute Data ◽  
Object Databases ◽  
Spatio Temporal ◽  
Eu Project ◽  
The University ◽  
Moving Object Databases

Geographic Information Systems (GIS) have been extensively used in various application domains, ranging from economical, ecological and demographic analysis, to city and route planning. Nowadays, organizations need sophisticated GIS-based Decision Support System (DSS) to analyze their data with respect to geographic information, represented not only as attribute data, but also in maps. Thus, vendors are increasingly integrating their products, leading to the concept of SOLAP (Spatial OLAP). Also, in the last years, and motivated by the explosive growth in the use of PDA devices, the field of moving object data has been receiving attention from the GIS community. However, not much has been done in providing moving object databases with OLAP functionality. In the first part of this article we survey the SOLAP literature. We then move to Spatio-Temporal OLAP, in particular addressing the problem of trajectory analysis. We finally provide an in-depth comparative analysis between two proposals introduced in the context of the GeoPKDD EU project: the Hermes-MDC system, and Piet, a proposal for SOLAP and moving objects, developed at the University of Buenos Aires, Argentina.

Application of improved random forest algorithm and fuzzy mathematics in physical fitness of athletes

2020 ◽  
pp. 1-13
Author(s):  
Tianye Gao ◽  
Jian Liu
Keyword(s):  
Random Forest ◽  
Young People ◽  
Physical Fitness ◽  
Regression Model ◽  
Comprehensive Evaluation ◽  
Indicator System ◽  
Influential Factor ◽  
Random Forest Regression ◽  
Explanatory Variables ◽  
The Impact

The comprehensive indicators of the physical fitness of young athletes and the specific modes of transportation, working and leisure activities as explanatory variables are not in line with the normal distribution. Moreover, there is a high correlation between explanatory variables, and fitting traditional regression models does not meet the assumptions, and multiple collinearity problems will occur, and good results will not be obtained. The random forest regression model has excellent performance in overcoming these difficulties. Therefore, the random forest regression model is constructed to evaluate the impact of various factors on the physical fitness of young people. This paper studies the impact of various factors on the health level of young people’s body and combines the source data and research goals to establish a comprehensive evaluation index system and an influential factor indicator system. In addition, this paper uses AHP to conduct comprehensive evaluation, and obtains the comprehensive physical quality of young people, and gives corresponding suggestions according to the actual situation.

ASSIGNMENT QUERY AND ITS IMPLEMENTATION IN MOVING OBJECT DATABASES

2010 ◽  
Vol 09 (03) ◽  
pp. 349-372 ◽  
Author(s):  
ALİ R. KONAN ◽  
TAFLAN İ. GÜNDEM ◽  
MURAT E. KAYA
Keyword(s):  
Nearest Neighbor ◽  
Perfect Match ◽  
Moving Object ◽  
Location Based Services ◽  
Matching Problem ◽  
Total Cost ◽  
Wide Range ◽  
Weighted Bipartite Graph ◽  
Object Databases ◽  
Moving Object Databases

Moving object databases (MOD) are being used in a wide range of location-based services that are of growing interest in many application areas. In the literature, several query types such as nearest neighbor, reverse nearest neighbor, k-nearest neighbor, and proximity queries have been considered in MOD. In this paper, we propose a novel operator called the assignment operator as a query type for MOD. The assignment operator is an operator used in a query to solve the assignment problem (also known as the weighted bipartite graph-matching problem). Assignment operator finds a perfect match between two sets of objects in a manner that minimizes a total cost. For instance, a set of moving objects such as taxi cabs are assigned to a set of customers in a manner that minimizes the total cost of traveling for the taxis. A possible implementation of the assignment operator in MOD and its performance evaluation are given.

Sign in / Sign up

Export Citation Format

Share Document