Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transient Stability Assessment of Power Systems Based on Local Learning
  Machine and Bacterial Colony Chemotaxis Algorithm   In order to improve the classification accuracy of transient stability
assessment of power systems, a novel method based on local learning machine and
an improved bacterial colony chemotaxis (BCC) algorithm is proposed, where
local learning machine(LLM) is used to build a TSA model. Considering the
possible real-time information provided by PMU, a group of system-level
classification features extracted from the power system operation parameters
are employed as inputs, and the stability result is used as output of the LLM
model. The relation ship between input and output is trained and the ideal
model is obtained by applying the improved BCC combined with chaotic search
strategy to determine the optimal parameters of LLM automatically. The
effectiveness of the proposed method is shown by the simulation results on the
New England 10-unit-39-bus power system.

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The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
17
The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
18
The categories of this paper are: econ
3
The categories of this paper are: physics
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
4
The categories of this paper are: cond-mat
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The categories of this paper are: hep-th