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electrical_grid_stability_simulated_regression

electrical_grid_stability_simulated_regression

active ARFF CC BY 4.0 Visibility: public Uploaded 23-07-2024 by Bruno Belucci Teixeira
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From original source: ----- The local stability analysis of the 4-node star system (electricity producer is in the center) implementing Decentral Smart Grid Control concept. Additional Information The analysis is performed for different sets of input values using the methodology similar to that described in [Schafer, Benjamin, et al. 'Taming instabilities in power grid networks by decentralized control.' The European Physical Journal Special Topics 225.3 (2016): 569-582.]. Several input values are kept the same: averaging time: 2 s; coupling strength: 8 s^-2; damping: 0.1 s^-1 Has Missing Values? No ----- Columns with index 13 were deleted from the dataset, usually because they related to some kind of index.

13 features

stab (target)numeric10000 unique values
0 missing
tau1numeric10000 unique values
0 missing
tau2numeric10000 unique values
0 missing
tau3numeric10000 unique values
0 missing
tau4numeric10000 unique values
0 missing
p1numeric10000 unique values
0 missing
p2numeric10000 unique values
0 missing
p3numeric10000 unique values
0 missing
p4numeric10000 unique values
0 missing
g1numeric10000 unique values
0 missing
g2numeric10000 unique values
0 missing
g3numeric10000 unique values
0 missing
g4numeric10000 unique values
0 missing

19 properties

10000
Number of instances (rows) of the dataset.
13
Number of attributes (columns) of the dataset.
0
Number of distinct values of the target attribute (if it is nominal).
0
Number of missing values in the dataset.
0
Number of instances with at least one value missing.
13
Number of numeric attributes.
0
Number of nominal attributes.
Percentage of instances belonging to the least frequent class.
Number of instances belonging to the least frequent class.
0
Number of binary attributes.
0
Percentage of binary attributes.
0
Percentage of instances having missing values.
0
Percentage of missing values.
0.96
Average class difference between consecutive instances.
100
Percentage of numeric attributes.
0
Number of attributes divided by the number of instances.
Percentage of instances belonging to the most frequent class.
0
Percentage of nominal attributes.
Number of instances belonging to the most frequent class.

1 tasks

0 runs - estimation_procedure: 10-fold Crossvalidation - target_feature: stab
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