Research and Application of Resource Information of Tree Growth Management

2013 ◽  
Vol 373-375 ◽  
pp. 1806-1809
Author(s):  
Guo Dong Han ◽  
Xin Qiang Li ◽  
Xian Hui Duan ◽  
Xu Ning Liu
Keyword(s):  
Decision Making ◽  
Knowledge Base ◽  
Tree Growth ◽  
Growth Management ◽  
Model Construction ◽  
Management Model ◽  
Resource Information ◽  
Related Information ◽  
Decision Making Model

In order to grasp the related information and parameters needed by the tree growth, and management, establish the authentic decision-making model of tree growth management using the effective resource information, the resource information of tree growth management are investigated from the perspective of ontology and knowledge base technology. The paper introduces the ontology and knowledge base technology, adopts the knowledge organizing pattern based on ontology, studies the structure and technique of knowledge of tree growth management, the ontology is regarded as the knowledge organizing pattern to establish the open knowledge base of tree growth management, and constructs the management model of tree growth. Practice has proved that the research and application of ontology in the resource information of tree growth management has important value for the model construction of tree growth management, achieves the sharing of resource information of tree growth management.

scholarly journals Research of Modern Information Technology on Tree Growth Management Decision Making Model

2013 ◽  
Vol 347-350 ◽  
pp. 2418-2421
Author(s):  
Yuan Li ◽  
Wen Qing Zhang ◽  
Hua Liu ◽  
Hui Qin Yang ◽  
Xu Ning Liu
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Tree Growth ◽  
Growth Management ◽  
Growth Conditions ◽  
Management Decision ◽  
Modern Information Technology ◽  
Management Decision Making ◽  
Modern Information ◽  
Decision Making Model

Tree growth management decision-making model can simulate growth management of tree and perform quantitative analysis of tree growth conditions. This paper explores the feasibility of modern information technology in management assessment of tree growth, information technology include neural network, ontology and expert system technology, then ontology technology is used to establish ontology database and knowledge base of tree growth management resource, the growth simulation and tree growth management ontology technology are used to build simulation models of tree growth, then expert systems and neural network technology are combined to simulate tree growth development process of decision-making model. The practice has proved that the research can not only predict the growth conditions of tree and dynamic grasp the growth process of the tree, but also can provide theoretical basis for the analysis and evaluation of tree growth management, greatly improving the level of tree growth management.

Research and Application of Ontology in Resource Information Model of Tree Growth Management

2013 ◽  
Vol 756-759 ◽  
pp. 1254-1258
Author(s):  
Xu Ning Liu ◽  
Hong Wei Song ◽  
Yuan Li ◽  
Jin Cui Kang
Keyword(s):  
Knowledge Base ◽  
Tree Growth ◽  
Growth Management ◽  
Information Model ◽  
Knowledge Organization ◽  
Resource Model ◽  
Traditional Methods ◽  
Resource Information ◽  
Resource Knowledge

In order to provide intellectual support for the construction of model resource of tree growth management, the paper carried out research on ontology and knowledge base technology, and the tree growth management resource information and ontology knowledge base were regarded as research target, which applied the ontology knowledge organization, then used semantic languages and resource model to study tree growth management resource knowledge base, discussed the acquisition, reasoning and other methods of tree growth management resource information. The practice has proved that resource information model of tree growth management based on ontology can acquire more parameters of tree growth management resource than traditional methods, which can provide sharing platform of resource information for tree growth management and contribute to construct the resource information model of tree growth management.

scholarly journals Research and Application of Growth Management Model of Tree

2012 ◽  
Vol 6-7 ◽  
pp. 175-179
Author(s):  
Li Ying Duan ◽  
Jun Ling Li ◽  
Qian Dong ◽  
Qing Yong Jin ◽  
Xu Ning Liu
Keyword(s):  
Growth Model ◽  
Tree Growth ◽  
Growth Management ◽  
Practical Significance ◽  
Management Model ◽  
Simulation Research ◽  
Research Technology ◽  
Management Measures ◽  
Database Technology ◽  
Tree Growth Model

With the application of growth model and computer techniques in tree growth management, in order to grasp growth pattern of tree, further improve the level of tree growth management, and make the research on the tree growth model gradually develop towards the intelligent and science. The paper carried out simulation research technology for management model of the tree growth, meanwhile the database technology and modeling technology are used in the tree growth model, so the management model of tree growth is established, then visually display the states which are at different stages of tree growth management, which can contribute to predict the development states of tree growth. The research on tree growth model has important theory and practical significance in understanding the yield of the various parts of the tree and in taking the reasonable management measures.

Applying the Multi-Criteria Decision Making Model for Ranking Commercial Banks: The Case of Vietnam

2019 ◽  
pp. 125-133
Author(s):  
Duong Truong Thi Thuy ◽  
Anh Pham Thi Hoang
Keyword(s):  
Decision Making ◽  
Commercial Banks ◽  
Decision Model ◽  
Business Models ◽  
Multi Criteria Decision Making ◽  
Ideal Solution ◽  
Topsis Method ◽  
Decision Making Model

Banking has always played an important role in the economy because of its effects on individuals as well as on the economy. In the process of renovation and modernization of the country, the system of commercial banks has changed dramatically. Business models and services have become more diversified. Therefore, the performance of commercial banks is always attracting the attention of managers, supervisors, banks and customers. Bank ranking can be viewed as a multi-criteria decision model. This article uses the technique for order of preference by similarity to ideal solution (TOPSIS) method to rank some commercial banks in Vietnam.

Multi-Attribute Decision-Making Model by Applying Grey Numbers

Informatica ◽  
2009 ◽  
Vol 20 (2) ◽  
pp. 305-320 ◽  
Author(s):  
Edmundas Kazimieras Zavadskas ◽  
Arturas Kaklauskas ◽  
Zenonas Turskis ◽  
Jolanta Tamošaitienė
Keyword(s):  
Decision Making ◽  
Multi Attribute Decision Making ◽  
Decision Making Model

EXPERT MANAGEMENT SYSTEMS OF AGROTECHNOLOGIES IN CLOUD INFORMATION TECHNOLOGY

1970 ◽  
pp. 12-17
Author(s):  
I. М. Mikhaylenko ◽  
V. N. Timoshin
Keyword(s):  
Decision Making ◽  
Pattern Recognition ◽  
Information System ◽  
Knowledge Base ◽  
Information Technologies ◽  
Agricultural Sector ◽  
Perennial Grasses ◽  
Management Decision ◽  
Agricultural Technologies ◽  
Automation Systems

The transition to "intellectual" agriculture is the main vector of modernization of the agricultural sector of the economy. It is based on integrated automation and robotization of production, the use of automated decision-making systems. This is inevitably accompanied by a significant increase in data flow from sensors, monitoring systems, meteorological stations, drones, satellites and other external systems. Farm management has the opportunity to use various online applications for accurate recommendations and making various kinds of management decisions. In this regard, the most effective use of cloud information technologies, allowing implementing the most complex information and technical level of automation systems for management of agricultural technologies. The purpose of this work is to test the approach to creating expert management decision support systems (DSS) through the knowledge base (KB), formed in the cloud information system. For this, we consider an example of constructing a DSS for choosing the optimal date for preparing forage from perennial grasses. A complete theoretical and algorithmic database of the analytical DSS implemented in the data processing center of the cloud information system is given. On its basis, a KB is formed for a variety of different decision-making conditions. This knowledge base is transmitted to the local DSS. To make decisions about the optimal dates for the preparation of the local DSS, two variants of algorithms are used. The first option is based on management models, and the second uses the pattern recognition method. The approbation of the algorithms was carried out according to the BZ from 50 cases. According to the results of testing, the method of pattern recognition proved to be more accurate, which provides a more flexible adjustment of the situation on the local DSS to a similar situation in the KB. The considered technique can be extended to other crops.

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