scholarly journals Smart Financial Management System Based on Data Ming and Man-Machine Management

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Maotao Lai
Keyword(s):  
Data Mining ◽  
Support System ◽  
Financial Management ◽  
Management System ◽  
Management Decision ◽  
Data Mining Algorithm ◽  
Management Support ◽  
Mining Algorithm ◽  
Financial Management System ◽  
Improved Algorithm

To begin, the architecture of an intelligent financial management system is thoroughly investigated, and a new architecture of an intelligent financial management support system based on data mining is developed. Second, it goes over the definition and structure of a data warehouse and data mining, as well as how to use data mining strategy and technology in financial management. Data mining in relation to technology is being investigated, as is the development of an intelligent data mining algorithm. The flaws of the intelligent data mining algorithm are discovered through an analysis and summary of the algorithm, and an improved algorithm is proposed to address the flaws. Related mining experiments are carried out on the improved algorithm, and the experiment shows that it has certain advantages. Then, using an intelligent forecasting financial management decision as an example, the intelligent financial management based on data mining is thoroughly investigated, the basic design framework for intelligent financial management is established, and the application of a data mining model in decision support system is introduced.

scholarly journals Development of a Decision Support System for Urban Planning by Using K-means ++ Algorithm

2020 ◽  
Vol 31 (3) ◽  
pp. 78
Author(s):  
Hussein Ali Salih ◽  
Ahmed Shihab Ahmed ◽  
Jalal Qais Jameel
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Urban Planning ◽  
Decision Support System ◽  
Support System ◽  
Decision Making Process ◽  
Data Mining Algorithm ◽  
Mining Algorithm ◽  
Coordination Framework

This article depicts a decision support system (DSS) devoted to the coordinated administration of urban frameworks. This framework defines the information and related treatments normal to a few civil managers and characterizes the necessities and functionalities of the PC devices created to enhance the conveyance, execution, and coordination of metropolitan administrations to the populace. The cooperative framework called Decision Support System for Urban Planning (DSS-UP) is made out of a universal planning and coordination framework. So, it helps the decision-making process, a DSS was created as a learning-based framework gave derivation components that empower urban architect to settle on key decisions as far as specialized meditations on civil foundations. The learning-based framework stores experts_ information and additionally answers for past issues. Preparatory execution comes about demonstrate that DSS-UP viably and effectively underpins the decision-making process identified with overseeing urban foundations by using K-means++ data mining algorithm.

Applications of Data Mining Algorithm in Equipment Fault Diagnosis

2014 ◽  
Vol 644-650 ◽  
pp. 2551-2555
Author(s):  
Rong Xiang Li ◽  
Zeng Lei Zhang ◽  
Yun Liu ◽  
Shan Chao Tu
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Decision Tree ◽  
Decision Trees ◽  
Data Mining Algorithm ◽  
Basic Principles ◽  
Mining Algorithm ◽  
Id3 Algorithm ◽  
Better Than ◽  
Improved Algorithm

The Basic Principles of Data mining Decision-tree ID3 is opened out. The main deficiencies are analysed. An improved algorithm based on the ID3 is calculated. For fault diagnosis of engine exemple, traditional ID3 algorithm and the improved algorithm are applied to estimate the fault diagnosis of engine separately. Decision Trees of traditional ID3 algorithm and the improved algorithm are construct. Experiment result display the accuracy of improved algorithm is better than traditional ID3. The improved algorithm is more fit to applied to the equipment fault diagnosis.

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