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We develop a scalable evolutionary computational approach utilizing massively parallel high performance computing for political redistricting optimization and analysis at fine levels of granularity.
Ant colony optimization is an evolutionary computational technique proposed by Dorigo et al. [6].
Having a malware taxonomy can facilitate the design of mitigation strategies such as those based on evolutionary computational intelligence.
We introduce in this work an evolutionary computational algorithm with sophisticated procedures for optimization of three-phase gravity separators.
To tackle this issue, this study presents an evolutionary computational approach for structural damage detection using the self-powered wireless sensor data.
Considering experiences in road extraction and also exploiting distributed evolutionary computational approaches, in this paper a new framework for road map updating from remotely sensed data is proposed.
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Although we do not model this process further in this paper, from research in evolutionary computation and computational neuroscience (e.g. the Leabra algorithm [74]) it is known that Hebbian learning can bias the copying operator or the hill-climbing operator so as to structure the exploration distribution of variants, thus potentially optimizing evolutionary search [29].
These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic.
Computational approaches, particularly those based on evolutionary computation (EC), are particularly promising for automating large-scale biological system design.
Computational intelligence includes fields such as neural networks, fuzzy systems, evolutionary computing, and artificial life.
Stegmayer presented a novel integrated computational intelligence approach for biological data mining that involves neural networks and evolutionary computation [7].
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