Research Article
[Retracted] Evolving Long Short-Term Memory Network-Based Text Classification
Algorithm 2
Evolving long short-term memory networks.
(i) | Output: optimized population | (ii) | Input: {initial parameters of MOGA} | (iii) | begin | (iv) | Obtain initial random solutions ; | (v) | Call Algorithm 1 by considering ; | (vi) | Sort according to ; | (vii) | / Selection operator/ | (viii) | ; | | While do | (ix) | / and indicate final generation and children elimination / | (x) | Randomly select ;/ mutation point / | (xi) | ; | (xii) | for do | (xiii) | Evaluate fitness of | (xiv) | if , then | (xv) | remove ; | (xvi) | ; | (xvii) | else | (xviii) | ; | (xix) | end | (xx) | end | / Mutation / | | for crossover do | | Consider two solutions randomly as and ;/ , , and are children / | | ; | | Computer fitness of | | if then | | remove ; | | else | | remove ; | | end | | end | | end | / Ranking / Apply nondominated sorting on ; | | return | | end |
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