Intelligent decision-making with bird-strike risk assessment for airport bird repellent

2018 ◽  
Vol 122 (1252) ◽  
pp. 988-1002 ◽  
Author(s):  
Weishi Chen ◽  
Jie Zhang ◽  
Jing Li
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Real Time ◽  
Expert Knowledge ◽  
Assessment Model ◽  
Classification Model ◽  
Support Vector ◽  
Bird Strike ◽  
Intelligent Decision Making ◽  
Intelligent Decision

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.

scholarly journals IoT in Online Banking

2021 ◽  
Vol 2 (4) ◽  
pp. 219-222
Author(s):  
Malti Bansal ◽  
Naman Oberoi ◽  
Mohd. Sameer
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Market Share ◽  
Online Banking ◽  
Huge Amount ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Banking Institutions ◽  
Physical Objects

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.

EBDMSS

2012 ◽  
pp. 265-284
Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Support System ◽  
Balanced Scorecard ◽  
Business Strategy ◽  
Business Managers ◽  
Web Based ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wide Range

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.

EBDMSS

2011 ◽  
pp. 549-568
Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Support System ◽  
Balanced Scorecard ◽  
Business Strategy ◽  
Business Managers ◽  
Web Based ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wide Range

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.

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 ◽  
...  
Keyword(s):  
Decision Making ◽  
Objective Function ◽  
Real Time ◽  
Decision Making Process ◽  
Layer Model ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Multi Agent ◽  
Block Chain ◽  
Micro Grid

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.

scholarly journals Intelligent Decision-Making of Scheduling for Dynamic Permutation Flowshop via Deep Reinforcement Learning

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1019
Author(s):  
Shengluo Yang ◽  
Zhigang Xu ◽  
Junyi Wang
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Real Time ◽  
Dynamic Scheduling ◽  
Scheduling Problems ◽  
Permutation Flowshop ◽  
Scheduling System ◽  
Single Action ◽  
Intelligent Decision Making ◽  
Intelligent Decision

Dynamic scheduling problems have been receiving increasing attention in recent years due to their practical implications. To realize real-time and the intelligent decision-making of dynamic scheduling, we studied dynamic permutation flowshop scheduling problem (PFSP) with new job arrival using deep reinforcement learning (DRL). A system architecture for solving dynamic PFSP using DRL is proposed, and the mathematical model to minimize total tardiness cost is established. Additionally, the intelligent scheduling system based on DRL is modeled, with state features, actions, and reward designed. Moreover, the advantage actor-critic (A2C) algorithm is adapted to train the scheduling agent. The learning curve indicates that the scheduling agent learned to generate better solutions efficiently during training. Extensive experiments are carried out to compare the A2C-based scheduling agent with every single action, other DRL algorithms, and meta-heuristics. The results show the well performance of the A2C-based scheduling agent considering solution quality, CPU times, and generalization. Notably, the trained agent generates a scheduling action only in 2.16 ms on average, which is almost instantaneous and can be used for real-time scheduling. Our work can help to build a self-learning, real-time optimizing, and intelligent decision-making scheduling system.

scholarly journals Risk assessment to curb COVID-19 contagion: A preliminary study using remote sensing and GIS

2020 ◽  
Author(s):  
Shruti Kanga ◽  
Gowhar Meraj ◽  
Sudhanshu ◽  
Majid Farooq ◽  
M. S. Nathawat ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Risk Reduction ◽  
Industrial Revolution ◽  
Risk Mitigation ◽  
Intelligent Decision Making ◽  
Risk Indices ◽  
Intelligent Decision ◽  
Eastern Zone ◽  
Integrated Hazard

Abstract Globally, COVID-19 pandemic has become a threat to humans and to the socio-economic systems they have developed since the industrial revolution. Hence, governments and stakeholders are calling for strategies that could help to restore the normalcy while dealing with this pandemic effectively. Since, till now, the disease is yet to have a cure; therefore, only risk-based decision-making can help governments to achieve a solution that is sustainable in the long term. To help the decision-makers to explore viable actions, we here propose a risk assessment framework for analyzing COVID-19 risk to areas, using integrated hazard and vulnerability components associated with this pandemic for effective risk mitigation. The study is carried on a region administrated by Jaipur municipal corporation (JMC), India. Based on the current understanding of this disease, we hypothesized different COVID-19 risk indices (C19Ri) of the wards of JMC such as proximity to hotspots, total population, population density, availability of clean water and associated land use/ land cover, are related with COVID-19 contagion and calculated them in a GIS-based multi-criteria risk reduction method. The results showed disparateness in COVID-19 risk areas with higher risk in north-eastern and south-eastern zone wards within the boundary of JMC. We proposed to prioritize wards that are under higher risk zones for intelligent decision-making regarding COVID-19 risk reduction through appropriate management of resources-related policy consequences. This study aims to serve as a baseline study to be replicated in other parts of the country or world to eradicate the threat of COVID-19 effectively.

Sign in / Sign up

Export Citation Format

Share Document