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Titlebook: Computational Intelligence in Power Engineering; Bijaya Ketan Panigrahi,Ajith Abraham,Swagatam Das Book 2010 Springer-Verlag Berlin Heidel

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樓主: broach
11#
發(fā)表于 2025-3-23 10:35:32 | 只看該作者
12#
發(fā)表于 2025-3-23 17:27:32 | 只看該作者
Durchsetzung einer neuen Strategie,VM). SVM is a relatively new computational learning method based on the statistical learning theory. The proposed technique is used for developing protection schemes for Thyristor Controlled Series Compensated (TCSC) Line using post fault current samples for half cycle (10 samples) from the inceptio
13#
發(fā)表于 2025-3-23 19:45:51 | 只看該作者
Die Notwendigkeit von Strategien,ll have more and more PQ-sensitive loads such as microprocessor-based devices, critical manufacturing processes, and data centers [1]. Our future global competitiveness demands disturbance-free operation of the digital devices that empower the productivity of our economy. It is expected that the Sma
14#
發(fā)表于 2025-3-23 22:51:49 | 只看該作者
15#
發(fā)表于 2025-3-24 03:34:03 | 只看該作者
https://doi.org/10.1007/978-3-211-69367-4ately, are of non-convex and sometimes discrete nature has encouraged many researchers to develop new optimization techniques to overcome such difficulties. Particle Swarm Optimization (PSO) is one of the newly developed optimization techniques with many attractive features. Early experimentations o
16#
發(fā)表于 2025-3-24 06:55:34 | 只看該作者
https://doi.org/10.1007/978-3-211-69367-4both single-input and dual-input power system stabilizers (PSSs). Conventional PSS (CPSS) and the three dual-input IEEE PSSs (PSS2B, PSS3B, and PSS4B) are optimally tuned to obtain the optimal transient performances. A comparative performance study of these four variants of PSSs is also made. It is
17#
發(fā)表于 2025-3-24 12:24:22 | 只看該作者
18#
發(fā)表于 2025-3-24 15:04:50 | 只看該作者
19#
發(fā)表于 2025-3-24 19:23:37 | 只看該作者
,Agilit?t für die Strategieausrichtung,ltimachine power systems. The eigenvalue analysis and the nonlinear simulation results show the robustness and the effectiveness of the DEPSSs to damp out the local as well as the interarea modes of oscillations and work effectively over a wide range of loading conditions.
20#
發(fā)表于 2025-3-25 01:03:39 | 只看該作者
Rudolf Streicher,Georg Turnheimal predictor has the form of another neural network. The developed system of prediction was tested on the real data of the Polish Power System. The results have been compared to the appropriate values generated by other methods.
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