2020 ◽  
Vol 1 (12) ◽  
pp. 79-82
Author(s):  
M. U. USUPOV ◽  

The article deals with the application of adaptive methods of capital management at enterprises of the Toktogul district of the Kyrgyz Republic. This area of economic work is considered a key point in the functioning of the firm. Questions of formation and effective use of own and borrowed capital largely depend on the use of modern methods of analysis.


Robotica ◽  
2021 ◽  
pp. 1-17
Author(s):  
Seyed Mostafa Almodarresi ◽  
Marzieh Kamali ◽  
Farid Sheikholeslam

Abstract In this paper, new distributed adaptive methods are proposed for solving both leaderless and leader–follower consensus problems in networks of uncertain robot manipulators, by estimating only the gravitational torque forces. Comparing with the existing adaptive methods, which require the estimation of the whole dynamics, presented methods reduce the excitation levels required for efficient parameter search, the convergence time, and the complexity of the regressor. Additionally, proposed schemes eliminate the need for velocity information exchange between the agents. Global asymptotic synchronization is shown by introducing new Lyapunov functions. Simulation results are provided for a network of 10 4-DOF robot manipulators.


Wind Energy ◽  
2011 ◽  
Vol 15 (6) ◽  
pp. 847-863 ◽  
Author(s):  
Angus C.W. Creech ◽  
Wolf-Gerrit Früh ◽  
Peter Clive

2021 ◽  
Vol 3 ◽  
pp. 38-46
Author(s):  
I. N. Myagkova ◽  
◽  
V. R. Shirokii ◽  
R. D. Vladimirov ◽  
O. G. Barinov ◽  
...  

The potential is investigated of predicting the time series of the Dst geomagnetic index using various adaptive methods: artificial neural networks (classical multilayer perceptrons), decision trees (random forest), gradient boosting. The prediction is based on the parameters of the solar wind and interplanetary magnetic field measured at the Lagrange point L1 in the ACE spacecraft experiment. It is shown that the best prediction skill of the three adaptive methods is demonstrated by gradient boosting.


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