Review of Research on Irrigation Decision Control

2021 ◽  
Author(s):  
Jie Chen ◽  
Xuan Ji ◽  
Junhui Wu ◽  
Yusheng Wu ◽  
Kaiyan Lin ◽  
...  
Keyword(s):  
Author(s):  
E. I. Kazakova ◽  
E. N. Govorukha ◽  
S. Chernovol ◽  
V. Cherepov ◽  
R. Romashov ◽  
...  

2018 ◽  
Vol 95 (3) ◽  
pp. 1999-2017 ◽  
Author(s):  
Paolo Arena ◽  
Marco Calí ◽  
Luca Patané ◽  
Agnese Portera ◽  
Angelo G. Spinosa
Keyword(s):  

2018 ◽  
Vol 27 (8) ◽  
pp. 1950-1957
Author(s):  
Deborah Ejem ◽  
J. Nicholas Dionne-Odom ◽  
Yasemin Turkman ◽  
Sara J. Knight ◽  
Dan Willis ◽  
...  

2004 ◽  
Vol 31 (2) ◽  
pp. 261
Author(s):  
N. U. Ahmed ◽  
Yongjuan He

In this paper we demonstrate that by use of modern Systems and Optimal Control theory, it is possible to formulate optimum immigration and job creation strategies while maintaining population level close to certain pre-specified targets. With this objective in mind, we consider a simplified dynamic model based on a previous model developed in (Ahmed and Rahim, 2001:325-358) to describe the population distribution in Canada. Numerical results demonstrate that the model population is in close agreement with the actual population. This model was then used to formulate a control problem with immigration and job creation rates being the decision (control) variables. Using optimal control theory, optimum immigration and job creation policies were determined. Results are illustrated by numerical simulation and they are found to be very encouraging.


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