Taxonomy of nature inspired computational intelligence: A remote sensing perspective

Abstract

---The concepts in geospatial sciences are generally vague, ambiguous and imprecise. Also, a combination of spectral, spatial and radiometric resolution of space-borne sensors presents a selective and incomplete look of the geospatial feature/object under its view from the space. Recently, the nature inspired computational intelligence (CI) techniques have emerged as an efficient mechanism to handle diverse uncertainty characteristics. This paper proposes that the human-mind model based computational intelligence techniques, the artificial immune system based computational intelligence techniques; the swarm intelligence based computational intelligence techniques and the emerging geo-sciences based intelligent techniques can be considered as the four pillars of nature inspired CI techniques and hence redefines and extends the taxonomy of nature inspired CI. Researchers have shown keen interest on the applications of natural computing in divergent domains. Scanty references are available on the applications of nature inspired computing in the area of remote sensing. We hence also propose the taxonomy of the most recent nature inspired CI techniques that have been adapted till date for geo-spatial feature extraction and analyze their performances. We also construct a technology timeline of these recent nature inspired CI techniques.Keywords---Natural computation; computational intelligence; geo-spatial feature extraction.

Swarm Intelligence for Frequency Management in Smart Grids

“…These developments cover artificial neural networks (Haykin, 2009;Schmidhuber, 2011;Dzemyda et al, 2007Dzemyda et al, , 2013Medvedev et al, 2011;Ivanikovas et al, 2011), evolutionary computation (Simon, 2013;Eiben and Smith, 2003;Filatovas et al, 2015;Kurasova, 2013, 2014), fuzzy set theory (Ross, 2010), artificial immune systems (Al-Enezi et al, 2010), etc. Some taxonomy of nature inspired artificial intelligence is given in Goel et al (2012). One of widely used nature inspired artificial intelligence techniques is swarm intelligence.…”

Introduction to Evolutionary Computation

“…Instead of simulating the evolution of organisms, swarm intelligence focuses on the interaction among several agents and their environment. In literature, a large number of swarm optimization approaches have been discussed [4,34], and many researchers have presented different taxonomies [21]. Ant colony optimization (ACO) [11] is a metaheuristic used to find approximate solutions to many optimization problems.…”