Reliability in statistical techniques

Reliability addresses the question of whether repeated application of a procedure will produce similar results.

J Scott Armstron, Fred Collopy,
Error measures for generalising about forecasting methods: Emperical comparisons;
Pg 69-80; International Journal of Forecasting; Vol 8; Year 1992

From before:

Stability is consistency of results, during validation phase, with different samples of data

(Monica Adya and Fred Collopy, J Forecast. 17 481-495 (1998) )

To look at stability in SA, we will define stability as
the consistency of (SA) results within candidate (networks) solutions;

this can be easily justified for SA results in FFNN because we already know that there is high redundancy in free parameters in FFNNs. Therefore, the SA technique that shows consistency between all the networks - and also shows corresponding change in consistency when the data quality is seen to change... promises to be a better technique???