New perspectives in computational intelligence: nothing so intelligent as randomness, nothing so effective as asymmetry
DOI: 10.1504/IJCISTUDIES.2009.025336 | Bruno Apolloni, Simone Bassis | Leaving the expert systems framework of the 80s and the early connectionist paradigm of the 90s, the scientific community is now drawn by social computing paradigms, where a huge number of agents individually do an elementary job and jointl... | 6- 36 |
Qualitative classification of descent phases in commercial flight data
DOI: 10.1504/IJCISTUDIES.2009.025336 | Edward Smart, Honghai Liu, Chris Jesse, David Brown | Flight data from commercial aircraft in the descent is analysed using one-class classification techniques to identify possible unstable approaches. The method considers snapshots of flight parameters at certain heights in the descent and id... | 37 - 49 |
Computation of the Frechet mean, variance and interpolation for a pool of neural networks over the manifold of special orthogonal matrices
DOI: 10.1504/IJCISTUDIES.2009.025336 | S. Fiori | The present manuscript tackles the problem of merging the connection patterns learnt by a pool of neural networks that share the manifold of special orthogonal matrices as parameter space. The merging technique is implemented as an averagin... | 50 - 71 |
Mean particle swarm optimisation for function optimisation
DOI: 10.1504/IJCISTUDIES.2009.025336 | Kusum Deep, Jagdish Chand Bansal | In this paper, a new particle swarm optimisation algorithm, called MeanPSO, is presented, based on a novel philosophy by modifying the velocity update equation. This is done by replacing two terms of original velocity update equation by two... | 72 - 92 |
Glowworm swarm optimisation: a new method for optimising multi-modal functions
DOI: 10.1504/IJCISTUDIES.2009.025336 | K.N. Krishnanand, D. Ghose | This paper presents an exposition of a new method of swarm intelligence based algorithm for optimising multi-modal functions. The main objective of using this method is to ensure capture of all local maxima of the function. The application ... | 93 - 119 |
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