# Read e-book online Advances in Swarm Intelligence: Third International PDF

By Zvi Retchkiman Konigsberg (auth.), Ying Tan, Yuhui Shi, Zhen Ji (eds.)

ISBN-10: 3642309755

ISBN-13: 9783642309755

ISBN-10: 3642309763

ISBN-13: 9783642309762

This booklet and its better half quantity, LNCS vols. 7331 and 7332, represent the court cases of the 3rd foreign convention on Swarm Intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The a hundred forty five revised complete papers offered have been rigorously reviewed and chosen from 247 submissions. The papers are equipped in 27 cohesive sections overlaying all significant issues of swarm intelligence learn and developments.

**Read Online or Download Advances in Swarm Intelligence: Third International Conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 Proceedings, Part I PDF**

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**Additional info for Advances in Swarm Intelligence: Third International Conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 Proceedings, Part I**

**Example text**

The best previous visited position of the particle is denoted as pbesti = ( pbesti1 , pbesti 2 ," , pbestid ) . The velocity and the position of the particle are updated according to the following two equations: vijk +1 = w × vijk + c1 × r1 × ( pbestij − xijk ) + c2 × r2 × ( gbest j − xijk ) xijk +1 = xijk + vijk +1 (1) (2) Where j = 1,2, " d . Both r1 and r2 are random numbers, which uniformly distributed between [0, 1]. Both c1 and c2 are the positive constant, c1 = c2 =2 [5]. w is inertial weight calculated in the following form for a quick convergence and good result, w = wmax − iter × wmax − wmin itermax (3) Where, wmax and wmin are the inertial and final weights respectively.

0 j j m m 2 j j j i T 1 2 Ne e A SI-Based Algorithm for Structural Damage Detection 25 Objective Function. The objective function is defined as a problem minimizing differences between the experimental and analytical modal results. The minimization of objective function is expressed as a bound-constrained nonlinear least-squares (BCNLS) problem as follows, minNe f (α ) = α∈R 1 1 N 2 r (α ) = ∑ ri 2 (α ) 2 2 i =1 l ≤ α ≤ u, r : R Ne →R (9) N r (α ) N ×1 = ⎡⎣ r f (α )TNm ×1 , rϕ (α )TNm ×1 ⎤⎦ T (10) Where r (α) = (r (α), r (α),… , r (α)) , is a N-dimensional vector-valued function, N = 2 N ≥ N .

The velocity of the particle can be represented by ， another vector, vi = ( vi1 , vi 2 " vid ) . The best previous visited position of the particle is denoted as pbesti = ( pbesti1 , pbesti 2 ," , pbestid ) . The velocity and the position of the particle are updated according to the following two equations: vijk +1 = w × vijk + c1 × r1 × ( pbestij − xijk ) + c2 × r2 × ( gbest j − xijk ) xijk +1 = xijk + vijk +1 (1) (2) Where j = 1,2, " d . Both r1 and r2 are random numbers, which uniformly distributed between [0, 1].

### Advances in Swarm Intelligence: Third International Conference, ICSI 2012, Shenzhen, China, June 17-20, 2012 Proceedings, Part I by Zvi Retchkiman Konigsberg (auth.), Ying Tan, Yuhui Shi, Zhen Ji (eds.)

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