Intelligent Decision Making Based on Data Mining Using Differential Evolution Algorithms and Framework for ETL Workflow Management

2010 ◽  
Author(s):  
Maqbool Uddin Shaikh ◽  
Saif Ur Rehman Malik ◽  
Ahsan Qureshi ◽  
Sarah Yaqoob
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Differential Evolution ◽  
Workflow Management ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Evolution Algorithms ◽  
Differential Evolution Algorithms ◽  
Etl Workflow

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2011 ◽  
pp. 141-156
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2008 ◽  
pp. 2964-2977
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

Adapted Visual Analytics Process for Intelligent Decision-Making: Application in a Medical Context

2020 ◽  
Vol 19 (01) ◽  
pp. 241-282 ◽  
Author(s):  
Hela Ltifi ◽  
Emna Benmohamed ◽  
Christophe Kolski ◽  
Mounir Ben Ayed
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Intelligent Decision Making ◽  
The Past ◽  
Intelligent Decision ◽  
Intelligent Decision Support Systems ◽  
Intelligent Decision Support

The theoretical and practical researches on Visual Analytics for intelligent decision-making tasks have remarkably advanced in the past few years. Intelligent Decision Support Systems (IDSS) introduce effective and efficient paths from raw data to decision by involving visualization and data mining technologies. Data mining-based DSS produces potentially interesting patterns from data. The transition from extracted patterns to knowledge is a delicate task. In this context, we propose to adapt a common visual analytics process for creating a path that enables the user (decision-maker) to automatically explore and visually extract insights by interacting with the patterns. This proposal is inspired from integrating traditional visual analytics concepts with the mental model of knowledge visualization. The idea is to combine an automatic and visual analysis of patterns to generate knowledge for the purpose of decision-making. To validate our proposal, we have applied it to a medical case study for the fight against Nosocomial Infections in Intensive Care Units. The developed platform was evaluated according to the utility and usability dimensions.

Research on the Online Intelligent Decision-Making System of Power-Grid Security Based on Power Grid Crisis Management

2014 ◽  
Vol 889-890 ◽  
pp. 1555-1558 ◽  
Author(s):  
Shi Hua Li
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Crisis Management ◽  
Power Grid ◽  
Actual Condition ◽  
Grid Security ◽  
Limit Values ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Decision Making System

Power grid crisis happening at home and abroad warns the urgency of power grid crisis management. It is necessary to research on online intelligent decision-making system of power-grid security based on data mining. This paper studies the status of foreign online intelligent decision-making system of power-grid security and the concrete application of foreign online intelligent decision-making system of power-grid security. Based on advanced data mining technology, by online updating safety limit-rules and automatically digging out the running rules, the safe limit values are in line with actual condition of power-grid, dispatchers can adjust the grid by running this limit and can obtain a larger cross-section delivery power-flow. In such a way, it not only can ease the power shortage situation of the system, but also improve poor power transmission ability, and produce economic benefits.

Study on Decision-Making System and its Data Mining Application of Logistics Intelligent

2013 ◽  
Vol 433-435 ◽  
pp. 2424-2428
Author(s):  
Xun Wang
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Improved Genetic Algorithm ◽  
Mining Technology ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Decision Making System ◽  
Irregular Data ◽  
Improve Service Quality

The most useful function of data mining technology is extracting valuable information and knowledge from irregular data. This paper briefly described the steps of data mining technology, elaborated logistics intelligent decision-making system components, proposed an improved genetic algorithm, took logistics distribution center location problem as argumentation. Applied data mining technology to logistics smart decisions, it can improve service quality, and establish long-term friendly and cooperative relations with customers.

Intelligent Logistics Decision System Based on Economic Benefit

2014 ◽  
Vol 644-650 ◽  
pp. 5681-5684 ◽  
Author(s):  
Jing Xin Wu
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision System ◽  
Mining Technology ◽  
Strong Function ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Decision Making System ◽  
Irregular Data ◽  
Intelligent Logistics

The data mining technology has strong function of extracting unknown information and knowledge with potential value from irregular data. The data mining procedures are introduced in this paper, it is applied in the intelligent decision system, and application and the solving steps are analyzed. The composition of intelligent logistics decision system is described. Finally, the simulation is taken, and the genetic algorithm of data mining technology is proposed and it is applied in the intelligent decision-making system of logistics. The simulation results show that the system can be applied in the logistics planning and decision making, the data mining technology can provide guidance for decision layer.

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