scholarly journals Research on the Framework of Intelligent Command Decision System for Flood Control

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Yao Zhang
Keyword(s):  
Decision Making ◽  
Intelligent Systems ◽  
Flood Control ◽  
Intelligent System ◽  
Decision Makers ◽  
Intelligent Decision Making ◽  
Related Information ◽  
Control Command ◽  
Decision Making System ◽  
Key Issues

Starting from the process of flood control and flood control decision-making, the shortcomings of the traditional flood control and flood control command and decision-making system are analyzed, and an intelligent decision-making system for flood control and flood control is proposed. The structure and functions of the system framework are elaborated in detail, and the key issues in the process of building intelligent systems are pointed out. Based on the real-time information monitoring system, this intelligent system can predict the next phase of hydrometeorology, flood and other related information, help decision makers to identify risks, and optimize the best flood control dispatching plan for decision makers to choose.

scholarly journals An Intelligent Decision-Making Support System for the Detection and Staging of Prostate Cancer in Developing Countries

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Jun Zhang ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Kanghuai Liu
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Developing Countries ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Diagnostic System ◽  
Medical Personnel ◽  
Medical Systems ◽  
Intelligent Decision Making ◽  
Diagnosis Rate

Most developing countries face huge challenges in the medical field; scarce medical resources and inadequate medical personnel will affect the development and stability of the society. Therefore, for most developing countries, the development of intelligent medical systems can greatly alleviate the social contradictions arising from this problem. In this study, a new data decision-making intelligent system for prostate cancer based on perceptron neural network is proposed, which mainly makes decisions by associating some relevant disease indicators and combining them with medical images. Through data collection, analysis and integration of medical data, as well as the disease detection and decision-making process, patients are given an auxiliary diagnosis and treatment, so as to solve the problems and social contradictions faced by most developing countries. Through the study of hospitalization information of more than 8,000 prostate patients in three hospitals, about 2,156,528 data items were collected and compiled for experiment purposes. Experimental data shows that when the patient base increases from 200 to 8,000, the accuracy of the machine-assisted diagnostic system will increase from 61% to 87%, and the doctor’s diagnosis rate will be reduced to 81%. From the study, it is concluded that when the patient base reaches a certain number, the diagnostic accuracy of the machine-assisted diagnosis system will exceed the doctor’s expertise. Therefore, intelligent systems can help doctors and medical experts treat patients more effectively.

Reducing the Risk of Wrong Choice in Group Decision Making by Optimal Weight Allocating to Decision Makers

2018 ◽  
Vol 7 (2) ◽  
pp. 1-23 ◽  
Author(s):  
Mohammad Azadfallah
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Potential Risk ◽  
Group Decision ◽  
Decision Makers ◽  
Topsis Method ◽  
Numerical Examples ◽  
Multiple Attribute ◽  
Key Issues ◽  
The Ideal

How to determine a weight for decision makers (DMs) is one of the key issues in Multiple Attribute Group Decision Making (MAGDM). While, some experts (or DMs) clearly wiser and more powerful in such matters than others, it has often seen that experts play their roles with same weights of importance. Meanwhile, it will lead to the wrong choice (or decision risk) and loss of values. Since, in the absence of any other standards about how to reduce this potential risk for bias, in this article, based on judgment matrices and error analysis, the author presents two new algorithm taken from crisp (the correlation-based approach) and interval (the ideal-based approach) TOPSIS method, respectively. Finally, two numerical examples are given to demonstrate the feasibility of the developed method.

scholarly journals Intelligent decision-making system for autonomous robots

2011 ◽  
Vol 21 (4) ◽  
pp. 671-684 ◽  
Author(s):  
Zdzisław Kowalczuk ◽  
Michał Czubenko
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Autonomous Robots ◽  
Personality Psychology ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Cognitive Behavioural ◽  
Decision Making System ◽  
Instrumental Role

Intelligent decision-making system for autonomous robots The paper gives an account of research results concerning a project on creating a fully autonomous robotic decision-making system, able to interact with its environment and based on a mathematical model of human cognitive-behavioural psychology, with some key elements of personality psychology included. The principal idea of the paper is focused on the concept of needs, with a certain instrumental role of emotions.

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