Build Evidence Chain Relational Model Based on Chinese Judgment Documents

Multidimensional Space Structure for Adaptable Data Model

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.c6318.098319 ◽

2019 ◽

Vol 8 (3) ◽

pp. 7753-7758

Keyword(s):

Data Model ◽

Cartesian Product ◽

Data Representation ◽

Space Structure ◽

Automated System ◽

Relational Model ◽

Multidimensional Data ◽

Multidimensional Space ◽

Model Based ◽

Five Axes

The article presents an adaptable data model based on multidimensional space. The main difference between a multidimensional data representation and a table representation used in relational Database Management Systems (DBMSs) is that it is possible to add new elements to sets defining the axes of multidimensional space at any time. This changes the data model. The tabular representation of the relational model does not allow you to change the model itself during the operation of an automated system. Three levels of multidimensional data presentation space are considered. There are axis of multidimensional space, the Cartesian product of the sets of axis values and the values of space points. The five axes of multidimensional space defined in the article (entities, attributes, identifiers, time, modifiers) are basic for the design of an adaptable automated system. It is shown that it is possible to use additional axes for greater granularity of the stored data. The multidimensional space structure defined in the article for an adaptable data model is a flexible set for storing a relational domain model. Two types of operations in multidimensional information space are defined. Relations of the relational model are formed dynamically depending on the conditions imposed on the coordinates of the points. Thus, an adaptable data representation model based on multidimensional space can be used to create flexible dynamic automated information systems.

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Grey Correlation Model Based on Diatom Indices Evaluating Water Quality of Longjiang River

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.448-453.43 ◽

2013 ◽

Vol 448-453 ◽

pp. 43-47 ◽

Cited By ~ 1

Author(s):

Xin Tang ◽

De Suo Cai ◽

Wen Ting Yao

Keyword(s):

Water Quality ◽

Water Quality Assessment ◽

Quality Standard ◽

Relational Model ◽

Water Quality Standard ◽

Diatom Index ◽

Model Based ◽

Diatom Indices ◽

Grey Relational

In order to evaluate the water quality of Longjiang river comprehensively, diatoms of 15 sampling sites are collected to establish the Grey Relational Model based on three diatom indexesIPS, IBD and IDG. From the Cluster analysis of sampling sites and the box plot of diatom index, IBD is the best, then the IPS, the diatom index weights on water quality assessment are 0.637 for IBD, 0.2583 for IPS, 0.1074 for IDG respectively. Finally, by comparing the water quality standard level based on Grey Relational Model, it can be known that the water quality of most sampling sites is fine except that site No.1 and No.3 belong to III water quality standard. The result shows that it is more comprehensive and reasonable to use the Grey Relational Model based on diatom index rather than individual diatom index to assess water quality.

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