scholarly journals Research on Micro-Grid Group Intelligent Decision Mechanism under the Mode of Block-Chain and Multi-Agent Fusion

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4196
Author(s):  
Fu ◽  
Wang ◽  
Wang ◽  
Shi ◽  
Yang ◽  
...  

This paper aims to study the problems of surplus interaction, poor real-time performance, and excessive processing of information in the micro-grid scheduling and decision-making process. Firstly, the micro-grid dual-loop mobile topology structure is designed by using the method of block-chain and multi-agent fusion, realizing the real-time update of the decision-making body. Secondly, on the basis of optimizing the decision-making body, a two-layer model of intelligent decision-making under the decentralized mechanism is established. Aiming at the upper model, based on the theory of block-chain consensus mechanism, this paper proposes an improved evolutionary game algorithm. The maximum risk-benefit in the decision-making process is the objective function, which realizes the evaluation and optimization of decision tasks. For the lower layer model, based on the block-chain distributed ledger theory, this paper proposes an improved hybrid game reinforcement learning algorithm, with the maximum controllable load participation as the objective function, and realizes the optimal configuration of distributed energy in the micro-grid. This paper reveals the rules of group intelligent decision making in micro-grid under multi-task. Finally, the effectiveness of the proposed algorithm is verified by using Beijing Jin-feng Energy Internet Park data.

Author(s):  
Malti Bansal ◽  
Naman Oberoi ◽  
Mohd. Sameer

As we know, there are so many changes arriving right now ion the banking industries which are really complex industries. Every day, huge amount of data is processed and gathered. With this increase in size, it is becoming more difficult for banking institutions to manage this data and handle other segments of their business. This paper presents the scope of IoT in the banking domain and how various transformations could potentially bring game changing reforms in the traditional methodology. Banking institutions need to integrate IoT in their systems to increase their market share by providing services catered to a clients need based on the data that’s being processed in real time. In future, IoT will be able to create such technologies which will be able to connect physical objects so that objects can do their own intelligent decision making.


2014 ◽  
Vol 926-930 ◽  
pp. 1140-1143
Author(s):  
Hui Gao ◽  
Hong Jiang Wu ◽  
Hai Yan Zhao

This paper combines the technical features of multi-agent to form the intelligent decision supporting system for exercise prescription of psychological disorder based on multi-agent. And studies for the system decision-making process and system implementation are also presented. Meanwhile, it shows the insufficiency of the intelligent decision supporting system to lay a foundation for the realization of computerization in exercise prescription of psychological disorder.


Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang

This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.


2018 ◽  
Vol 122 (1252) ◽  
pp. 988-1002 ◽  
Author(s):  
Weishi Chen ◽  
Jie Zhang ◽  
Jing Li

ABSTRACTAn intelligent decision-making method was proposed for airport bird-repelling based on a Support Vector Machine (SVM) and bird-strike risk assessment. The bird-strike risk assessment model is established with two exponential functions to separate the risk levels, while the SVM method includes two steps of training and testing. After the risk assessment, the Bird-Repelling Strategy Classification Model (BRSCM) was trained based on the expert knowledge and large amount of historical bird information collected by the airport linkage system for bird detection, surveillance and repelling. Then, in the testing step, the BRSCM was continuously optimised according to the real-time intelligent bird-repelling strategy results. Through several bird-repelling examples of a certain airport, it is demonstrated that the decision accuracy of BRSCM is relatively high, and it could solve new problems by self-correction. The proposed method achieved the optimised operation of multiple bird-repelling devices against real-time bird information with great improvement of bird-repelling effects, overcoming the tolerance of birds to the bird-repelling devices due to their long-term repeated operation.


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