Development of an intelligent model to estimate the height of caving–fracturing zone over the longwall gobs

2016 ◽  
Vol 30 (7) ◽  
pp. 2145-2158 ◽  
Author(s):  
Mohammad Rezaei
Author(s):  
Mauricio Drelichman ◽  
Hans-Joachim Voth

Why do lenders time and again loan money to sovereign borrowers who promptly go bankrupt? When can this type of lending work? As the United States and many European nations struggle with mountains of debt, historical precedents can offer valuable insights. This book looks at one famous case—the debts and defaults of Philip II of Spain. Ruling over one of the largest and most powerful empires in history, King Philip defaulted four times. Yet he never lost access to capital markets and could borrow again within a year or two of each default. Exploring the shrewd reasoning of the lenders who continued to offer money, the book analyzes the lessons from this historical example. Using detailed new evidence collected from sixteenth-century archives, the book examines the incentives and returns of lenders. It provides powerful evidence that in the right situations, lenders not only survive despite defaults—they thrive. It also demonstrates that debt markets cope well, despite massive fluctuations in expenditure and revenue, when lending functions like insurance. The book unearths unique sixteenth-century loan contracts that offered highly effective risk sharing between the king and his lenders, with payment obligations reduced in bad times. A fascinating story of finance and empire, this book offers an intelligent model for keeping economies safe in times of sovereign debt crises and defaults.


2018 ◽  
Vol 150 ◽  
pp. 21-27 ◽  
Author(s):  
Jian Wei Ho ◽  
Johnson Wong ◽  
Percis Teena Christopher Subhodayam ◽  
Kwan Bum Choi ◽  
Divya Ananthanarayanan ◽  
...  

2011 ◽  
Vol 217-218 ◽  
pp. 1293-1296
Author(s):  
Hua Zheng ◽  
Li Xie ◽  
Li Zi Zhang

This article describes an intelligent simulation method for measuring price risk, which is still one of the important problems for various risk managements and need to be studied profoundly. To solve this problem, risk measured in terms of Value at Risk on electricity price is proposed by intelligent simulation. In this work, prices under various market scenarios are produced by intelligent model using fuzzy neural network (FNN). After that, the quantitative model for price risk analysis is built in the form of a function of the estimated probability distribution of price, where price VAR is determined from the distribution according to parameter set, i.e. confidence level. The proposed method is more realistic and effective than variance approach to provide the assessment of the potential loss of electricity price over some period of time.


2017 ◽  
Vol 132 (2) ◽  
pp. 1213-1239 ◽  
Author(s):  
Alireza Baghban ◽  
Fathollah Pourfayaz ◽  
Mohammad Hossein Ahmadi ◽  
Alibakhsh Kasaeian ◽  
Seyed Mohsen Pourkiaei ◽  
...  

2000 ◽  
Author(s):  
David Nielsen ◽  
Ranga Pitchumani

Abstract Variabilities in the preform structure in situ in the mold are an acknowledged challenge to effective permeation control in the Resin Transfer Molding (RTM) process. An intelligent model-based controller is developed which utilizes real-time virtual sensing of the permeability to derive optimal decisions on controlling the injection pressures at the mold inlet ports so as to track a desired flowfront progression during resin permeation. This model-based optimal controller employs a neural network-based predictor that models the flowfront progression, and a simulated annealing-based optimizer that optimizes the injection pressures used during actual control. Preform permeability is virtually sensed in real-time, based on the flowfront velocities and local pressure gradient estimations along the flowfront. Results are presented which illustrate the ability of the controller in accurately steering the flowfront for various fill scenarios and preform geometries.


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