Research Article
Matching Sensor Ontologies with Simulated Annealing Particle Swarm Optimization
| (1) | Input: Source and target ontologies and , number of iteration , initial temperature , | | (2) | population size | | (3) | for ( = 0; < n; ++) | | (4) | for ( = 0; < 3; ++) | | (5) | [i] = (0, 1) | | (6) | [i] = (0, 1) | | (7) | [i] = | | (8) | calculate fitness [i] | | (9) | f [i] = fitness[i] | | (10) | end for | | (11) | end for | | (12) | = {[i]} | | (13) | = {[i]} | | (14) | = {[i]} | | (15) | while < do | | (16) | = | | (17) | for ( = 0; < n; ++) | | (18) | for ( = 0; < 3; ++) | | (19) | [i] = [i] + ([i]) + | | (20) | [i] = [i] + [i] | | (21) | update fitness[i] | | (22) | if (fitness[i] f [i]) | | (23) | P = 1 | | (24) | [i] = [i] | | (25) | else | | (26) | P = | | (27) | if (P(0, 1)) | | (28) | [i] = [i] | | (29) | end if | | (30) | end if | | (31) | f [i] = fitness[i] | | (32) | end for | | (33) | end for | | (34) | = {[i]} | | (35) | = {[i]} | | (36) | = {[i]} | | (37) | Gbest = {f [i]} | | (38) | end while | | (39) | Output Gbest |
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