In the image inpainting based on the sample block, the quality of image restoration is directly related to the repair order, and the existing algorithms ignore the respective proportions of the image texture features ...
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Various evolutionary algorithms are being developed to search the optimal solution of various problems in the real world. Evolutionary algorithms search solutions showing the optimal fitness to given problem using the...
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This paper presents a design computation system supporting scientific computing methods relevant to architectural and engineering design under the paradigm of visual programming. The objective of this research work is...
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ISBN:
(纸本)9789881902672
This paper presents a design computation system supporting scientific computing methods relevant to architectural and engineering design under the paradigm of visual programming. The objective of this research work is to expand and advance the palette of methods employed in academic and professional design environments. The tools contain methods for linear algebra, non-linear solvers, network analysis and algorithms for classical operational research problems such as cutting and packing, clustering and routing. A few decades ago the idea that computing would become so pervasive in the realm of architecture and engineering as it is today was confronted with deep scepticism. The thesis of this paper is that while it may be equally implausible that such methods are relevant today it may be the next natural evolution in the direction of design computation. The current state of the presented software package is still in early alpha version and it is available online for evaluation.
MESH is an epsilon-approximate algorithm to find the minimum zone center of a given roundness profile, with epsilon = 10(-d), where d is the number of required decimal digits. The proposed MESH algorithm is able to pr...
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MESH is an epsilon-approximate algorithm to find the minimum zone center of a given roundness profile, with epsilon = 10(-d), where d is the number of required decimal digits. The proposed MESH algorithm is able to provide only the accuracy that is necessary to find the minimum zone error roundness (circularity). The basic principle is to exhaustively assess all MZR center candidates located at the cross points of a mesh, with spacing directly related to the target accuracy. Criteria for the selection of the required manufacturing (designer's) target accuracy (product specifications) are discussed. This result has been made possible by previous work on the limit search space to be searched. The algorithm effectiveness has been shown by computation experiments up to 16,384 cloud datapoints and by comparison with genetic algorithms and an exact method from the literature. The MESH algorithm can also serve for benchmarking purposes to assess the performance of other algorithms in terms of both accuracy and speed. The extension to other form tolerances of the exhaustive mesh based approach is discussed. (C) 2015 Elsevier Inc. All rights reserved.
Given an n-vertex graph or digraph G, a spanning subgraph S is a kspanner of G if for every u, v ε V(G), the distance from u to v in S is at most k times longer than the distance in G. This paper establishes some rel...
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Design spaces that consist of millions or billions of design combinations pose a challenge to current methods for identifying optimal solutions. Complex analyses can also lead to lengthy computation times that further...
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ISBN:
(纸本)9780791850107
Design spaces that consist of millions or billions of design combinations pose a challenge to current methods for identifying optimal solutions. Complex analyses can also lead to lengthy computation times that further challenge the effectiveness of an algorithm in terms of solution quality and run-time. This work explores combining the design space exploration approach of a Multi-Objective Genetic Algorithm with different instance-based, statistical, rule-based and ensemble classifiers to reduce the number of unnecessary function evaluations associated with poorly performing designs. Results indicate that introducing a classifier to identify child designs that are likely to push the Pareto frontier toward an optima reduce the number of function calculations by 75-85%, depending on the classifier implemented.
In this paper, we present an efficient algorithm for the computation of triangular Shepard interpolation method. More precisely, it is well known that the triangular Shepard method reaches an approximation order bette...
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In this paper, we present an efficient algorithm for the computation of triangular Shepard interpolation method. More precisely, it is well known that the triangular Shepard method reaches an approximation order better than the Shepard one (DellAccio et al., 2016), but it needs to identify useful general triangulation of the node set. Here we propose a searching technique used to detect and select the nearest neighbor points in the interpolation scheme (Cavoretto et al., 2016, 2017). It consists in determining the closest points belonging to the different neighborhoods and subsequently applies to the triangulation -based approach. Numerical experiments and some geological applications show efficiency and accuracy of the interpolation procedure. (C) 2018 Elsevier B.V. All rights reserved.
The mesh of buses (MBUSs) is a parallel computation model which consists of n × n processors, n row buses and n column buses. Upper and lower bounds for the routing problem over MBUSs are discussed. We first show...
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Given a set of obstacles and two distinguished points in the plane the problem of finding a collision-free path subject to a certain optimization function is a fundamental problem that arises in many fields, such as m...
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Evolutionary computation techniques, which are based on a powerful principle of evolution: survival of the fittest, constitute an interesting category of heuristic search. These stochastic algorithms whose search meth...
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ISBN:
(纸本)0780329031
Evolutionary computation techniques, which are based on a powerful principle of evolution: survival of the fittest, constitute an interesting category of heuristic search. These stochastic algorithms whose search methods model some natural phenomena: genetic inheritance and Darwinian strife for survival, have been applied to a large number of hard, real-world problems from a variety of domains: social systems, machine learning, operations research, ecology, engineering, immune systems, economics, management, etc. Any evolutionary algorithm applied to a particular problem must address the issue of genetic representation of solutions to the problem and genetic operators that would alter the genetic composition of offspring during the reproduction process. Additional heuristics should be incorporated in the algorithm as well;some of these heuristic rules provide guidelines for initializing the population of potential solutions, for setting various parameters of the system (e.g., population size, probabilities of operators, etc.) and for evaluating individuals in the population. This paper discusses some practical issues connected with applications of evolutionary techniques.
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