752 publications from this institution
The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm can provide a good balance between these two key components with superior efficiency. In this paper, we first review some commonly used metaheuristic algorithms, and then compare the performance of bat algorithm with the so-called intermittent search strategy. From simulations, we found that bat algorithm is better than the optimal intermittent search strategy. We also analyse the comparison results and their implications for higher dimensional optimization problems. In addition, we also apply bat algorithm in solving business optimization and engineering design problems.
No abstract is provided for this article.
Binomial expansions and series are important for mathematical analysis concerning probability theory, approximation techniques and data modeling. This chapter introduces the fundamentals of binomial theorem, factorials and Pascal's coefficient triangle.
Though nature-inspired algorithms have been shown to be effective, we still lack some in-depth understanding of these algorithms. This chapter attempts to provide a unified framework to analyze algorithms from different perspectives with some mathematical rigor. Both convergence and stability are analyzed, together with some algorithmic complexity. Some key issues concerning benchmarking and comparison of nature-inspired algorithms are also highlighted.
A model of the interaction of pressure changes with strained premixed flames is formulated by extending previous work on interactions with nonstrained flames. By making the assumption of no divergence in the velocity field (∇ · u = 0) and writing the full equations in terms of mass-weighted coordinates (with explicit strain terms) following the flame sheet, we study the time-varying response of the mass burning rate to an imposed pressure disturbance. Numerical solution of the full nonlinear equations shows that strain has a strong effect on the flame response. It is found that, for large amplitude step pressure drops, the flame does not recover for moderate and small strain rates. As expected, for larger positive strain rates the flame recovers, because it is known that positive strain stabilizes premixed flames. The reverse happens for flames experiencing pressure drops in a convergent flow (negative strain). In this case, extinction of the flame by pressure drops becomes more likely as the convergence of the flow increases. Of particular interest for the negative strain case is the onset of the pulsating instability for a finite range of small values of pressure drop, which then gives way to a region of recovery if the pressure drop is larger, before finally for larger drops the extinction pressure drop is reached.
The calculus of variations is closely related to many optimization problems and computational sciences, especially in the formulation of finite element methods. In this chapter, we will briefly touch on these topics.
No abstract is provided for this article.
Modern optimisation algorithms are often metaheuristic, and they are very promising in solving NP-hard optimization problems. In this paper, we show how to use the recently developed Firefly Algorithm to solve nonlinear design problems. For the standard pressure vessel design optimisation, the optimal solution found by FA is far better than the best solution obtained previously in literature. In addition, we also propose a few new test functions with either singularity or stochastic components but with known global optimality, and thus they can be used to validate new optimisation algorithms. Possible topics for further research are also discussed.
Technological advances in tea production are critical to meet global demands for tea consumption. To illuminate differences in the scientific and commercial relevance of research programs between major tea-related research organizations around the world, we conducted a bibliometric analysis comparing the scientific outputs, including peer-reviewed publications and patents, of six major research organizations published between January 01, 2008 and July 11, 2020. For this competitive ranking analysis, we examined a number of papers, research topics, academic influence, capacity for development, capacity for collaboration, and capacity for technological innovation. Among the six research organizations, Anhui Agricultural University (in China) had the most publications, while the Chinese Academy of Agricultural Sciences, Tea Research Institute showed a higher capacity for development. The Council for Scientific and Industrial Research (in India) and the University of Shizuoka (Japan) both showed high academic influence, while the University of Shizuoka, Tea Research Association Tocklai and National Agriculture and Food Research Organization (Japan) showed a high capacity for collaboration. The Chinese Academy of Agricultural Sciences, Tea Research Institute applied for the most patents, while the Council for Scientific and Industrial Research applied for the most international patents.
Nature has provided rich models for computational problem solving, including optimizations based on the swarm intelligence exhibited by fireflies, bats, and ants. These models can stimulate computer scientists to think nontraditionally in creating tools to address application design challenges.
A small-world cellular automaton network has been formulated to simulate the long-range interactions of complex networks using unconventional computing methods in this paper. Conventional cellular automata use local updating rules. The new type of cellular automata networks uses local rules with a fraction of long-range shortcuts derived from the properties of small-world networks. Simulations show that the self-organized criticality emerges naturally in the system for a given probability of shortcuts and transition occurs as the probability increases to some critical value indicating the small-world behaviour of the complex automata networks. Pattern formation of cellular automata networks and the comparison with equation-based reaction-diffusion systems are also discussed
PreviousNext No AccessSEG Technical Program Expanded Abstracts 2003Biology‐derived algorithm in analytical element modelling of groundwater flowAuthors: Xin‐She YangXin‐She YangCivil & Computational Engineering Center, School of Engineering, University of Wales Swansea, Swansea SA2 8PP, UKhttps://doi.org/10.1190/1.1817601 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Permalink: https://doi.org/10.1190/1.1817601FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2003ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2003 Pages: 2452 publication data© 2003 Copyright © 2003 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 03 Jan 2005 CITATION INFORMATION Xin‐She Yang, (2003), "Biology‐derived algorithm in analytical element modelling of groundwater flow," SEG Technical Program Expanded Abstracts : 1581-1583. https://doi.org/10.1190/1.1817601 Plain-Language Summary PDF DownloadLoading ...
