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Parameter Self-Adaptation in an Ant Colony algorithm for Continuous Optimization

IEEE ACCESS 2019年 7卷 18464-18479页

作者： Abdelbar, Ashraf M. Salama, Khalid M. Brandon Univ Dept Math & Comp Sci Brandon MB R7A 6A9 Canada Univ Kent Sch Comp Canterbury CT2 7NZ Kent England

ACO(R) is a well-established ant colony optimization algorithm for continuous-domain optimization. We present an approach for the dynamic adaptation of the ACO(R) algorithm's controlling parameters, focusing on the search width parameter, based on using several pre-specified parameter configurations, which we call personalities. Before an ant starts to generate a candidate solution, it stochastically adopts a personality based on the relative past success of different personalities. The success of a personality is measured, in turn, by the survival rate of the previous solutions generated by the ants adopting that personality. The premise of our approach is that some personalities will be more appropriate than others for different phases of the search. In addition, our adaptive approach can accommodate solution recombination, the use of which within ACO(R) was recently explored in the previous work. It allows the frequency of applying recombination and the type of recombination operator to be dynamically adapted, by having one or more recombination personalities among the competing personalities. We evaluate these proposals experimentally on two applications: 1) training feedforward neural networks for classification using 65 benchmark datasets from the University of California Irvine repository and 2) optimizing several popular synthetic benchmark continuous-domain functions. Our experimental results indicate that our proposals perform better than the standard ACO(R) on both applications, to a statistically significant extent.

关键词： Collective intelligence evolutionary computation adaptive algorithm optimization methods ant colony optimization

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Synchro-squeezed adaptive wavelet transform with optimum parameters for arbitrary time series

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2019年 114卷 366-377页

作者： Qu, Hongya Li, Tiantian Chen, Genda Missouri Univ Sci & Technol 328 Butler Carlton Hall Rolla MO 65409 USA

In this study, a synchro-squeezed adaptive wavelet transform (SSAWT) is proposed and defined as an average of overlapped short-time wavelet transforms with optimized time varying resolution in a synchro-squeezed time-frequency representation. The time frequency resolution is automatically updated with a simplified procedure to determine optimal wavelet parameters. The instantaneous frequency spectra are accumulated over time to extract time-insensitive frequency characteristics in arbitrary time series. An illustrative signal with four time segments covering various frequency distribution cases indicated a 1.1% error of the proposed method, which is at least 5 times more accurate than the conventional synchro-squeezed wavelet transform. Due to synchro-squeezing process, SSAWT also exhibited more accurate results than the adaptive wavelet transform that has recently been developed by the authors. The proposed SSAWT was then applied to the impact echo responses experimentally recorded from a 60" x 36" x 7.25" concrete slab. The improvement in time-frequency resolution and corresponding frequency spectra led to more successful detections of deep or shallow or no delamination from 40 sets of experimental data within 1.5% estimation error in deep delamination depth and 5% estimation error in slab thickness. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Synchro-squeezed wavelet transform adaptive algorithm Continuous wavelet transform Time-varying frequency characteristics Signal processing Impact echo Concrete slab

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Power, routing, Modulation Level and Spectrum Assignment in all-optical and elastic networks

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OPTICAL SWITCHING AND NETWORKING 2019年 32卷 14-24页

作者： Vale, V. A. C. Almeida, R. C., Jr. Univ Fed Pernambuco Recife PE Brazil

The need for high data rates in telecommunications requires the constant search for improvements in these systems, especially in minimizing spectrum idleness in optical network. Currently, a solution to this issue is the elastic optical network, leading to numerous studies on the topic. As such, this article presents a study on elastic optical network, which considers physical layer effects (ASE noise and non-linearities) and their influence on the network layer, via the new PRMLSA problem (Power, Routing. Modulation Level and Spectrum Assignment). In the present study, this problem focuses on power, which directly influences the physical layer effects, obtaining promising results compared to current approaches.

关键词： Elastic optical network All-optical networks Power assignment Gauss-noise adaptive algorithm ASE noise Non-linearities

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adaptive poromechanics computations based on a posteriori error estimates for fully mixed formulations of Biot's consolidation model

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2019年 347卷 264-294页

作者： Ahmed, Elyes Radu, Florin Adrian Nordbotten, Jan Martin Univ Bergen Dept Math POB 7800 N-5020 Bergen Norway Princeton Univ Dept Civil & Environm Engn Princeton NJ 08544 USA

This paper is concerned with the analysis of coupled mixed finite element methods applied to the Biot's consolidation model. We consider two mixed formulations that use the stress tensor and Darcy velocity as primary variables as well as the displacement and pressure. The first formulation is with a symmetric stress tensor while the other enforces the symmetry of the stress weakly through the introduction of a Lagrange multiplier. The well-posedness of the two formulations is shown through Galerkin's method and suitable a priori estimates. The two formulations are then discretized with the backward Euler scheme in time and with two mixed finite elements in space. We present next a general and unified a posteriori error analysis which is applicable for any flux- and stress-conforming discretization. Our estimates are based on H-1(Omega)-conforming reconstruction of the pressure and d a suitable [H-1(Omega)](d)-conforming reconstruction of the displacement;both are continuous and piecewise affine in time. These reconstructions are used to infer a guaranteed and fully computable upper bound on the energy-type error measuring the differences between the exact and the approximate pressure and displacement. The error components resulting from the spatial and the temporal discretization are distinguished. They are then used to design an adaptive space-time algorithm. Numerical experiments illustrate the efficiency of our estimates and the performance of the adaptive algorithm. (C) 2018 The Author(s). Published by Elsevier B.V.

关键词： Biot's poro-elasticity problem Mixed variational formulations A posteriori error analysis Energy-type estimates Space and time errors adaptive algorithm

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An Efficient High-Order Time-Step algorithm With Proportional-Integral Control Strategy for Semirecursive Vehicle Dynamics

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IEEE ACCESS 2019年 7卷 40833-40842页

作者： Pan, Yongjun Xiang, Saidi Mikkola, Aki Chongqing Univ Sch Automot Engn Chongqing 400044 Peoples R China Lappeenranta Univ Technol Dept Mech Engn Lappeenranta 53850 Finland

Dynamics of complex mechanical systems can be modeled and solved efficiently, often even in faster-than-real-time by employing semi-recursive formulations and their various versions. To simulate complex mechanical systems accurately and efficiently, an optimal combination of a multibody formulation and a numerical time integration scheme is critical. To this end, this paper introduces a procedure based on the double-step semi-recursive formulation and adaptive time-step algorithm. The introduced adaptive time-step is based on proportional-integral controller that is particularly suitable for efficient computation of vehicle dynamics. The introduced proportional integral control strategy accounts the local truncation error and recent alteration concerning the local truncation error which improves the numerical stability and efficiency. As numerical examples, a 15-degree-of-freedom sedan vehicle model and a 17-degrees-of-freedom light truck model are analyzed by using the double-step semi-recursive formulation with an adaptive time-step algorithm. The results highlight the efficiency gain of the presented adaptive time-step algorithm. It can be concluded that the introduced approach is suitable for efficient simulation of highly nonlinear dynamics model.

关键词： adaptive algorithm proportional integral control strategy semi-recursive formulation efficient simulation vehicle dynamics

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adaptive BEM with optimal convergence rates for the Helmholtz equation

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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING 2019年第Apr.1期346卷 260-287页

作者： Bespalov, Alex Betcke, Timo Haberl, Alexander Praetorius, Dirk Univ Birmingham Sch Math Birmingham B15 2TT W Midlands England UCL Ctr Inverse Problems Gower St London WC1E 6BT England TU Wien Inst Anal & Sci Comp Wiedner Hauptstr 8-10 A-1040 Vienna Austria

We analyze an adaptive boundary element method for the weakly-singular and hypersingular integral equations for the 2D and 3D Helmholtz problem. The proposed adaptive algorithm is steered by a residual error estimator and does not rely on any a priori information that the underlying meshes are sufficiently fine. We prove convergence of the error estimator with optimal algebraic rates, independently of the (coarse) initial mesh. As a technical contribution, we prove certain local inverse-type estimates for the boundary integral operators associated with the Helmholtz equation. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Boundary element method Helmholtz equation A posteriori error estimate adaptive algorithm Convergence Optimality

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Learning-Aided Physical Layer Authentication as an Intelligent Process

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第3期67卷 2260-2273页

作者： Fang, He Wang, Xianbin Hanzo, Lajos Western Univ Dept Elect & Comp Engn London ON N6A 5B9 Canada Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England

Performance of the existing physical layer authentication schemes could be severely affected by the imperfect estimates and variations of the communication link attributes used. The commonly adopted static hypothesis testing for physical layer authentication faces significant challenges in time-varying communication channels due to the changing propagation and interference conditions, which are typically unknown at the design stage. To circumvent this impediment, we propose an adaptive physical layer authentication scheme based on machine-learning as an intelligent process to learn and utilize the complex time-varying environment, and hence to improve the reliability and robustness of physical layer authentication. Explicitly, a physical layer attribute fusion model based on a kernel machine is designed for dealing with multiple attributes without requiring the knowledge of their statistical properties. By modeling the physical layer authentication as a linear system, the proposed technique directly reduces the authentication scope from a combined N-dimensional feature space to a single-dimensional (scalar) space, hence leading to reduced authentication complexity. By formulating the learning (training) objective of the physical layer authentication as a convex problem, an adaptive algorithm based on kernel least mean square is then proposed as an intelligent process to learn and track the variations of multiple attributes, and therefore to enhance the authentication performance. Both the convergence and the authentication performance of the proposed intelligent authentication process are theoretically analyzed. Our simulations demonstrate that our solution significantly improves the authentication performance in time-varying environments.

关键词： Intelligent authentication multiple physical layer attributes kernel machine adaptive algorithm

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Bearing fault diagnosis with nonlinear adaptive dictionary learning

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2019年第9-12期102卷 4227-4239页

作者： Lu, Yanfei Xie, Rui Liang, Steven Y. Georgia Inst Technol George W Woodruff Sch Mech Engn Atlanta GA 30332 USA Univ Georgia Dept Stat Athens GA 30602 USA Donghua Univ Coll Mech Engn Shanghai 201620 Peoples R China

The monitoring of rotating machinery condition has been a critical component of the Industry 4.0 revolution in enhancing machine reliability and facilitating intelligent manufacturing. The introduction of condition-based monitoring has effectively reduced the catastrophic events and maintenance cost across various industries. One of the major challenges of the diagnosis remains as majority of the diagnostic model requires off-line analysis and human intervention. The offline analysis, which is normally done by previous experience, involves tuning model parameters to improve the performance of the diagnostic model. However, for newly developed models, the knowledge of the unknown parameters does not exist. One way to resolve this issue is through learning using adaptation. The adaptation algorithm adjusts itself by newly acquired data. Hence, improvement of the model performance is achieved. In this paper, a nonlinear adaptive dictionary learning algorithm is proposed to achieve early fault detection of bearing elements without using the conventional computation heavy algorithm to update the dictionary. Deterministic and random data separation is implemented using the autoregressive model to reduce the background noise. The filtered data is further analyzed by the Infogram to reveal the impulsiveness and cyclostationary signature of the vibration signal. The dictionary is initialized using random parameters. Instead of using the k means singular value decomposition algorithm to compute the dictionary for adaptation, the unscented Kalman filter (UKF) is implemented to update the dictionaries using the filtered signal from the Infogram. The updating algorithm does not require computation of the dictionary, and no previous knowledge of the dictionary's parameters is needed. The updated dictionary contains the detected fault signature from the Infogram and, therefore, is used for further fault analysis. The proposed algorithm has the advantage of self-adaptation, the cap

关键词： Ball bearing Fault diagnosis Dictionary learning adaptive algorithm

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Fast adaptive switching technique of impulsive noise removal in color images

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JOURNAL OF REAL-TIME IMAGE PROCESSING 2019年第4期16卷 1077-1098页

作者： Malinski, Lukasz Smolka, Bogdan Silesian Tech Univ Div Ind Informat Krasinskiego 8 PL-40019 Katowice Poland Silesian Tech Univ Inst Automat Control Akad 16 PL-44100 Gliwice Poland

In the paper, a family of switching filters designed for the impulsive noise removal in color images is analyzed. The framework of the proposed denoising techniques is based on the concept of cumulated distances between the processed pixel and its neighbors. To increase the filtering efficiency, a robust scheme, in which the sum of distances to only the most similar pixels of the neighborhood serves as a measure of impulsiveness, was elaborated. As this trimmed measure is dependent on the image local structure, an adaptive mechanism was also incorporated. Additionally, a very fast design, which enables image denoising in practical applications, is proposed and the choice of the filter output, which is used to replace the noisy pixels, is discussed. The described family of filters was evaluated on a large set of natural test images and compared with the state-of-the-art restoration methods. The analysis of the achieved results shows that the novel filters outperform the existing techniques in terms of both denoising accuracy and computational complexity. In this way, the proposed techniques can be recommended for the application in various image and video enhancement tasks.

关键词： Impulsive noise reduction Color image enhancement and restoration Image quality adaptive algorithm Switching filter

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An adaptive algorithm for Forest Fire Spread Based on Genetic algorithm

An Adaptive Algorithm for Forest Fire Spread Based on Geneti...

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4th International Conference on Manufacturing Science and Engineering (ICMSE 2013)

作者： Chang Chunyuan Northeast Forestry Univ Harbin Peoples R China

ISBN: (纸本)9783037856932

The spread of forest fire is a complex adaptive system. The spread could be seen as the result of fire agents' continuous learning, adaptation and co-ordination. This paper founded an Agent-based model for forest fire spread, modeled the generating of fire spread rules based on Genetic algorithms. Created the spread rules with effect of wind and topography independently for forest fire, designed the fitness function, and took the genetic operation on the rules, which created new rules. Implemented the adaptive algorithm on Repast S, and used it in the Agent-based model of forest fire spread. The result of model's running indicated the adaptive algorithm could improve the adaptive ability of fire agent.

关键词： adaptive algorithm Forest fire spread Genetic algorithm Rule generation

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