Efficient Fast Approximation for Aircraft Fuel Consumption for Decision-Making and Policy Analysis

2017 ◽  
Author(s):  
Jefry Yanto ◽  
Rhea P. Liem
Keyword(s):  
Decision Making ◽  
Policy Analysis ◽  
Fuel Consumption ◽  
Aircraft Fuel

Cultivating Trustworthy Artificial Intelligence in Digital Government

2020 ◽  
pp. 089443932098012
Author(s):  
Teresa M. Harrison ◽  
Luis Felipe Luna-Reyes
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Policy Analysis ◽  
Public Trust ◽  
Governance Structures ◽  
Cognitive Tools ◽  
Lens Model ◽  
Digital Government ◽  
Government Decision ◽  
Decision Making Processes

While there is growing consensus that the analytical and cognitive tools of artificial intelligence (AI) have the potential to transform government in positive ways, it is also clear that AI challenges traditional government decision-making processes and threatens the democratic values within which they are framed. These conditions argue for conservative approaches to AI that focus on cultivating and sustaining public trust. We use the extended Brunswik lens model as a framework to illustrate the distinctions between policy analysis and decision making as we have traditionally understood and practiced them and how they are evolving in the current AI context along with the challenges this poses for the use of trustworthy AI. We offer a set of recommendations for practices, processes, and governance structures in government to provide for trust in AI and suggest lines of research that support them.

scholarly journals A Study on Sustainable Consumption of Fuel—An Estimation Method of Aircraft

Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7559
Author(s):  
Lisha Li ◽  
Shuming Yuan ◽  
Yue Teng ◽  
Jing Shao
Keyword(s):  
Neural Network ◽  
Fuel Consumption ◽  
Influencing Factors ◽  
Carbon Emission ◽  
Estimation Method ◽  
Civil Aviation ◽  
Accurate Estimation ◽  
Low Carbon ◽  
Fuel Price ◽  
Aircraft Fuel

Though the development of China’s civil aviation and the improvement of control ability have strengthened the safety operation and support ability effectively, the airlines are under the pressure of operation costs due to the increase of aircraft fuel price. With the development of optimization controlling methods in flight management systems, it becomes increasingly challenging to cut down flight fuel consumption by control the flight status of the aircraft. Therefore, the airlines both at home and abroad mainly rely on the accurate estimation of aircraft fuel to reduce fuel consumption, and further reduce its carbon emission. The airlines have to take various potential factors into consideration and load more fuel to cope with possible negative situation during the flight. Therefore, the fuel for emergency use is called PBCF (Performance-Based Contingency Fuel). The existing PBCF forecasting method used by China Airlines is not accurate, which fails to take into account various influencing factors. This paper aims to find a method that could predict PBCF more accurately than the existing methods for China Airlines.This paper takes China Eastern Airlines as an example. The experimental data of flight fuel of China Eastern Airlines Co, Ltd. were collected to find out the relevant parameters affecting the fuel consumption, which is followed by the establishment of the LSTM neural network through the parameters and collected data. Finally, through the established neural network model, the PBCF addition required by the airline with different influencing factors is output. It can be seen from the results that the all the four models are available for the accurate prediction of fuel consumption. The amount of data of A319 is much larger than that of A320 and A330, which leads to higher accuracy of the model trained by A319. The study contributes to the calculation methods in the fuel-saving project, and helps the practitioners to learn about a particular fuel calculation method. The study brought insights for practitioners to achieve the goal of low carbon emission and further contributed to their progress towards circular economy.

Policy analysis and decision making in the military forces:

2020 ◽  
pp. 187-202
Author(s):  
Paula Lorena Mora-Hernández ◽  
Juan David Gélvez-Ferreira ◽  
Michael Weintraub ◽  
Sebastián Bitar
Keyword(s):  
Decision Making ◽  
Policy Analysis ◽  
Military Forces ◽  
The Military

Policy analysis and evidence-based decision making at the local level

2018 ◽  
pp. 131-152
Author(s):  
Karen Mossberger ◽  
David Swindell ◽  
Nicholet Deschine Parkhurst ◽  
Kuang-Ting Tai
Keyword(s):  
Decision Making ◽  
Policy Analysis ◽  
Local Level ◽  
Evidence Based ◽  
Evidence Based Decision Making

1. The history and evolution of foreign policy analysis

2016 ◽  
Author(s):  
Valerie M. Hudson
Keyword(s):  
Decision Making ◽  
Foreign Policy ◽  
International Relations ◽  
Policy Analysis ◽  
Research Agenda ◽  
International Politics ◽  
Classical Period ◽  
Foreign Policy Analysis ◽  
The 1950S ◽  
Large Groups

This chapter traces the history and evolution of foreign policy analysis (FPA) as a subfield of international relations (IR) from its beginnings in the 1950s through its classical period until 1993. It begins with a discussion of three paradigmatic works that laid the foundation of FPA: Decision Making as an Approach to the Study of International Politics (1954), by Richard C. Snyder, H. W. Bruck, and Burton Sapin; ‘Pre-theories and Theories of Foreign Policy’ (1966), by James N. Rosenau; and Man–Milieu Relationship Hypotheses in the Context of International Politics (1956), by Harold and Margaret Sprout. These three works created three main threads of research in FPA: focusing on the decision making of small/large groups, comparative foreign policy, and psychological/sociological explanations of foreign policy. The chapter also reviews classic FPA scholarship during the period 1954–1993 and concludes with an assessment of contemporary FPA’s research agenda.

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