Forecasting of locational marginal price components with artificial intelligence and sensitivity analysis: A study under tropical weather and renewable power for the Mexican Southeast

2022 ◽  
Vol 206 ◽  
pp. 107793
Author(s):  
A. Livas-García ◽  
O. May Tzuc ◽  
E. Cruz May ◽  
Rasikh Tariq ◽  
M. Jimenez Torres ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Sensitivity Analysis ◽  
Renewable Power ◽  
Locational Marginal Price ◽  
Tropical Weather ◽  
Marginal Price

Treatment of Uncertainty in an Oncology Protocol by Probabilistic and Artificial Intelligence Approaches

1988 ◽  
Vol 27 (01) ◽  
pp. 23-33 ◽  
Author(s):  
Fiorella de Rosis ◽  
G. Steve ◽  
C. Biagini ◽  
R. Maurizi-Enrici
Keyword(s):  
Artificial Intelligence ◽  
Sensitivity Analysis ◽  
Expert System ◽  
Probabilistic Model ◽  
Decision Process ◽  
Clinical Decision ◽  
Final Diagnosis ◽  
Decision Models ◽  
Expert System Shell ◽  
Subjective Estimation

SummaryThe decision process for diagnosis and treatment of Hodgkin’s disease at the Institute of Radiology of Rome has been modelled integrating the guidelines of a protocol with uncertainty aspects. Two models have been built, using a PROSPECTOR-like Expert System shell for microcomputers: the first of them treats the uncertainty by the inferential engine of the shell, the second is a probabilistic model. The decisions suggested in a group of simulated and real cases by a section of the two models have been compared with an “objective” final diagnosis; this analysis showed that, in some cases, the two models give different suggestions and that “approximations” of the shell’s inferential engine may induce wrong conclusions. A sensitivity analysis of the probabilistic model showed that the outputs are greatly influenced by variations of parameters, whose subjective estimation appears to be especially difficult. This experience gives the opportunity to consider the risks of building clinical decision models based on Expert System shells, if the assumptions and approximations hidden in the shell have not been previously analyzed in a careful and critical way.

Distribution locational marginal price-based transactive day-ahead market with variable renewable generation

2020 ◽  
Vol 259 ◽  
pp. 114103 ◽  
Author(s):  
M. Nazif Faqiry ◽  
Lawryn Edmonds ◽  
Hongyu Wu ◽  
Anil Pahwa
Keyword(s):  
Renewable Generation ◽  
Locational Marginal Price ◽  
Marginal Price
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