The invention relates to a
water quality anomaly detection feature selection method and
system based on an improved pigeon inspired optimization
algorithm, and belongs to the field of
machine learning. Executing an improved pigeon
flock algorithm, and evaluating the pigeon
flock; endowing the position and speed of the pigeon with the lowest fitness to the globally optimal pigeon; the speed of the pigeons is updated, the speed of the pigeons is converted through a
Sigmoid function, and the positions of the pigeons are updated according to the output value of the
Sigmoid function; when an iteration stopping condition is met, returning to a
global optimal pigeon; otherwise, mutating the pigeon
flock, and updating the position and the speed through the literanism;
ranking the varied pigeons according to fitness values, calculating an ideal destination, and updating the positions of the pigeons; according to the method, the self-adaptive iterative map and the
compass factor are set, and meanwhile, an Litalian mechanism is introduced, so that information interaction and cooperation can be carried out among pigeon individuals, the common evolution of a group is promoted, and the search capability of the group is further optimized.