Case Study of Evolutionary Process Visualization Using Complex Networks

Author(s):  
Patrik Dubec ◽  
Jan Plucar ◽  
Lukáš Rapant
2021 ◽  
Vol 336 ◽  
pp. 05020
Author(s):  
Piotr Hadaj ◽  
Marek Nowak ◽  
Dominik Strzałka

A case study based on the real data obtained from the Polish PSE System Operator of the highest voltages electrical energy network is shown. The data about the interconnection exchange and some complex networks (graphs) parameters were examined, after the removal of selected nodes. This allowed to test selected network parameters and to show that the breakdown of only three nodes in this network can cause significant drop of its average efficiency.


2020 ◽  
Vol 100 (2) ◽  
pp. 1725-1740 ◽  
Author(s):  
Chenquan Gan ◽  
Qingdong Feng ◽  
Qingyi Zhu ◽  
Zufan Zhang ◽  
Yushu Zhang ◽  
...  

Author(s):  
Jorge E. Pacheco ◽  
Cristina H. Amon ◽  
Susan Finger

During conceptual design, designers need tools to help improve design decisions and reduce design times. We are working to develop techniques to create Bayesian surrogate models that respond to designers’ needs during conceptual stages of the design process. Bayesian surrogate models give analytical form to the overall performance of a system and can evolve along with the design. Bayesian surrogate models provide a mathematically rigorous framework in which computational models can be updated based on previous outcomes. In this paper, we present techniques that allow the addition or suppression of parameters without discarding previously obtained information. We also present a case study that illustrates how a surrogate model is constructed in stages when parameters are added or suppressed during the design process. Visualization tools, such as plots of the main effects of parameters, can be derived from surrogate models. These tools can be used to provide knowledge about the parameters that influence the design. Finally, a design problem is used to illustrate how Bayesian surrogate models can inform the designer about tradeoffs that would not be apparent from simulation data alone.


2020 ◽  
Vol 05 (01) ◽  
pp. 13-31
Author(s):  
Jigang Sui ◽  
Ying Liu

Technology and institutions are important driving forces for industrial development, but the relationship between them has not yet reached a consensus due to different economic theories. On the basis of the evolutionary theory, this paper aims to study the roles co-evolution of technology and institutions played in the development of emerging industry. Taking electric vehicles in China as a case study and the five-year plans for the nodes of industrial development, this paper analyzes the co-evolutionary process of technology and institutions at different stages of industrial development, and concludes that it was institutions that promoted technology innovation during the industrial incubation and infancy periods, while during the growth period, it was technology that drove institutions’ innovation. In order to promote the development of electric vehicle industry, it is necessary to further strengthen institutional innovation for technological and industrial development.


2011 ◽  
Vol 2 (1) ◽  
pp. 63-85 ◽  
Author(s):  
Eunice Oliveira ◽  
Carlos Henggeler Antunes ◽  
Álvaro Gomes

The incorporation of preferences into Evolutionary Algorithms (EA) presents some relevant advantages, namely to deal with complex real-world problems. It enables focus on the search thus avoiding the computation of irrelevant solutions from the point of view of the practical exploitation of results (thus minimizing the computational effort), and it facilitates the integration of the DM’s expertise into the solution search process (thus minimizing the cognitive effort). These issues are particularly important whenever the number of conflicting objective functions and/or the number of non-dominated solutions in the population is large. In EvABOR (Evolutionary Algorithm Based on an Outranking Relation) approaches preferences are elicited from a decision maker (DM) with the aim of guiding the evolutionary process to the regions of the space more in accordance with the DM’s preferences. The preferences are captured and made operational by using the technical parameters of the ELECTRE TRI method. This approach is presented and analyzed using some illustrative results of a case study of electrical networks.


2013 ◽  
Vol 37 (4) ◽  
pp. 457-481 ◽  
Author(s):  
Daniel Alves ◽  
Ana Isabel Queiroz

This article proposes a methodology to address the urban evolutionary process, demonstrating how it is reflected in literature. It focuses on “literary space,” presented as a territory defined by the period setting or as evoked by the characters, which can be georeferenced and drawn on a map. It identifies the different locations of literary space in relation to urban development and the economic, political, and social context of the city. We suggest a new approach for mapping a relatively comprehensive body of literature by combining literary criticism, urban history, and geographic information systems (GIS). The home-range concept, used in animal ecology, has been adapted to reveal the size and location of literary space. This interdisciplinary methodology is applied in a case study to nineteenth- and twentieth-century novels involving the city of Lisbon. The developing concepts of cumulative literary space and common literary space introduce size calculations in addition to location and structure, previously developed by other researchers. Sequential and overlapping analyses of literary space throughout time have the advantage of presenting comparable and repeatable results for other researchers using a different body of literary works or studying another city. Results show how city changes shaped perceptions of the urban space as it was lived and experienced. A small core area, correspondent to a part of the city center, persists as literary space in all the novels analyzed. Furthermore, the literary space does not match the urban evolution. There is a time lag for embedding new urbanized areas in the imagined literary scenario.


2011 ◽  
Vol 17 (3) ◽  
pp. 183-202 ◽  
Author(s):  
Vito Trianni ◽  
Stefano Nolfi

Evolutionary robotics (ER) is a powerful approach for the automatic synthesis of robot controllers, as it requires little a priori knowledge about the problem to be solved in order to obtain good solutions. This is particularly true for collective and swarm robotics, in which the desired behavior of the group is an indirect result of the control and communication rules followed by each individual. However, the experimenter must make several arbitrary choices in setting up the evolutionary process, in order to define the correct selective pressures that can lead to the desired results. In some cases, only a deep understanding of the obtained results can point to the critical aspects that constrain the system, which can be later modified in order to re-engineer the evolutionary process towards better solutions. In this article, we discuss the problem of engineering the evolutionary machinery that can lead to the desired result in the swarm robotics context. We also present a case study about self-organizing synchronization in a swarm of robots, in which some arbitrarily chosen properties of the communication system hinder the scalability of the behavior to large groups. We show that by modifying the communication system, artificial evolution can synthesize behaviors that scale properly with the group size.


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