Interpretation of changes of global temperature is important for our understanding of the climate system and for our confidence in projections for the future. Massive efforts have been devoted to improve the accuracy ...
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Interpretation of changes of global temperature is important for our understanding of the climate system and for our confidence in projections for the future. Massive efforts have been devoted to improve the accuracy of reproducing the global temperature by the available climate models, but the hindcasts are still inaccurate. Notwithstanding the need to further advance climate models, one may consider data-driven approaches, providing practically useful results in a simpler and faster way. Without assuming any prior knowledge about physics and without imposing a model structure that encapsulates the existing knowledge about the underlying processes, we hindcast global temperature by automatically identified evolutionary computation models. We use 60 years of records of global temperature and climate drivers, with training and testing periods being 1950-1999 and 2000-2009, respectively. This paper demonstrates that the global temperature observed in the past is mimicked with reasonably good accuracy. evolutionary computation holds promise for modeling the global climate system, which looks hopelessly complex in classical perspective.
A preliminary investigation of cerebral stroke samples injected into a mass spectrometer is performed from an evolutionary computation perspective. The detection and resolution of peptide peaks is pursued for the purp...
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A preliminary investigation of cerebral stroke samples injected into a mass spectrometer is performed from an evolutionary computation perspective. The detection and resolution of peptide peaks is pursued for the purpose of automatically and accurately determining unlabeled peptide quantities. A theoretical peptide peak model is proposed and a series of experiments are then pursued (most within a distributed computing environment) along with a data preprocessing strategy that includes (i) a deisotoping step followed by (ii) a peak picking procedure, followed by (iii) a series of evolutionary computation experiments oriented towards the investigation of their capability for achieving the aforementioned goal. Results from four different genetic algorithms (GA) and one differential evolution (DE) algorithm are reported with respect to their ability to find solutions that fit within the framework of the presented theoretical peptide peak model. Both unconstrained and constrained (as determined by a course grained preprocessing stage) solution space experiments are performed for both types of evolutionary algorithms. Good preliminary results are obtained.
In recent years, various networks have come to exist in our surroundings. Not only the Internet and airline routes can be thought of as networks: protein interactions are also networks. An economic network design prob...
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In recent years, various networks have come to exist in our surroundings. Not only the Internet and airline routes can be thought of as networks: protein interactions are also networks. An economic network design problem can be discussed by assuming that a vertex is an economic player and that a link represents some connection between economic players. In this paper, the Airlines network is taken up as an example of an economic network design problem, and the Airlines network which the profit of the entire Airlines industry is maximized is clarified. The Airlines network is modeled based on connections models proposed by Jackson and Wolinsky, and the utility function of the network is defined. In addition, the optimization simulation using the evolutionary computation is shown for a domestic airline in Japan. (c) 2013 Wiley Periodicals, Inc. Electron Comm Jpn, 96(11): 16-25, 2013;Published online in Wiley Online Library (***). DOI 10.1002/ecj.11531
Service oriented computing has emerged as a popular software development paradigm. In the era of Cloud computing, Big data, the Internet of Things (IoT) and Smart Cities, Web service composition has been extensively r...
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Service oriented computing has emerged as a popular software development paradigm. In the era of Cloud computing, Big data, the Internet of Things (IoT) and Smart Cities, Web service composition has been extensively researched. Web service composition aims to find the best way of combining services, which accomplish simple tasks, into a more sophisticated composite application. evolutionary computation lends itself to tackling the problem of Web service composition, since it allows for the optimisation of the overall Quality of Service attributes of the composite solution. In order to gain a better understanding of the different evolutionary computation-based approaches applied to this problem, a number of literature surveys have been written in this area. However, these surveys do not focus on the technical aspects of using evolutionary computation to this end, instead focusing on the general application of methods. Thus, the focus of this survey is on analysing existing works from a technical perspective, paying particular attention to the following key decisions when choosing an evolutionary computation-based approach for Web service composition: a) the representation of candidates, b) the fitness evaluation strategy, c) the handling of correctness constraints, d) the choice of evolutionary algorithms and operators. Based on these analyses, current trends, limitations,and future research paths are identified.
Extended evolutionary algorithms for solving the optimal reactive power dispatch are presented. In these approaches, based on evolutionary programming and evolution strategies, mutations in standard deviations have be...
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Extended evolutionary algorithms for solving the optimal reactive power dispatch are presented. In these approaches, based on evolutionary programming and evolution strategies, mutations in standard deviations have been controlled using a dynamic limits strategy. The proposals have been exhaustively analysed and compared with a state-of-the-art method. Good and reliable performance has been achieved and validation tests using the standard IEEE57 system are reported.
evolutionary computation methods, such as evolutionary algorithms or swarm intelligence algorithms, have been successfully applied to a wide range of difficult problems. These include classical NP-hard combinatorial o...
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evolutionary computation methods, such as evolutionary algorithms or swarm intelligence algorithms, have been successfully applied to a wide range of difficult problems. These include classical NP-hard combinatorial optimization problems and a variety of hard real-world optimization problems. Real-world problems, in particular, are difficult to solve using traditional search methods because often they are nonlinear, highly constrained, multiobjective, and can include a number of uncertainties.
In summary, the course is an in-depth introduction to evolutionary computing techniques and other nature inspired algorithms in the area of computational intelligence, enabling the students to understand the current w...
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In summary, the course is an in-depth introduction to evolutionary computing techniques and other nature inspired algorithms in the area of computational intelligence, enabling the students to understand the current work in the field and providing starting points for novel research. The feedback from the students has been very positive and encouraging. I have been gratified many times at the end of a semester "when students have come to me to comment on how much they have learned from this course, rigorous as it is. Students have frequently commented that through this course, they not only have been trained in these techniques but, given the highly practical and experimental nature of this type of work, have the opportunity to develop their skills by tackling problems related to industrial needs or to leading edge research.
RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to rec...
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RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to recur in multiple genes within a single organism or across the same gene in several organisms and provide a common regulatory mechanism. Search algorithms, such as RNAMotif, can be used to mine nucleotide sequence databases for these repeating motifs. RNAMotif allows users to capture essential features of known structures in detailed descriptors and can be used to identify, with high specificity, other similar motifs within the nucleotide database. However, when the descriptor constraints are relaxed to provide more flexibility, or when there is very little a priori information about hypothesized RNA structures, the number of motif 'hits' may become very large. Exhaustive methods to search for similar RNA structures over these large search spaces are likely to be computationally intractable. Here we describe a powerful new algorithm based on evolutionary computation to solve this problem. A series of experiments using ferritin IRE and SRP RNA stem-loop motifs were used to verify the method. We demonstrate that even when searching extremely large search spaces, of the order of 10(23) potential solutions, we could find the correct solution in a fraction of the time it would have taken for exhaustive comparisons.
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