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Intelligent computing approach to analyze the dynamics of wire coating with Oldroyd 8-constant fluid

NEURAL COMPUTING & APPLICATIONS 2019年第3期31卷 751-775页

作者： Munir, Annum Manzar, Muhammad Anwaar Khan, Najeeb Alam Raja, Muhummad Asif Zahoor Capital Univ Sci & Technol Dept Math Islamabad Pakistan Preston Univ Kohat Dept Math Islamabad Campus Kohat Pakistan Hamdard Univ Hamdard Inst Engn & Technol Islamabad Pakistan Univ Karachi Dept Math Sci Karachi 75270 Pakistan COMSATS Inst Informat Technol Dept Elect Engn Attock Pakistan

In the study, intelligent computing technique is developed for solving the nonlinear system for wire coating analysis with the bath of Oldroyd 8-constant fluid having pressure gradient using feedforward artificial neural networks (ANNs), evolutionary computing, active-set algorithm (ASA) and their hybrid. Original partial differential equations of wire coating process are converted to nonlinear ordinary differential equation (NL-ODEs) in dimensionless form using similarity transformation. Strength of ANNs is exploited to develop mathematical model of the transformed equations by defining an unsupervised error. Training of design variables of the network is carried out globally using evolutionary computing techniques based on genetic algorithms (GAs) hybrid with ASA for rapid local convergence. Design scheme is applied to analyze the dynamics of the problem for number of variants based on dilatant constant, the pseudoplastic constant, the pressure gradient, shear stress under the effect of viscosity parameter and varying the coating thickness of the polymer. Results of the proposed method are compared with standard numerical solver for NL-ODEs based of Adams method to establish its correctness. Reliability of the method is further validated through the results of statistics based on different performance measures for accuracy and computational complexity.

关键词： Wire coating analysis Fluid dynamics Nonlinear systems Artificial neural network Genetic algorithms active-set algorithm

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Applicability comparison of different algorithms for ambient signal based load model parameter identification

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 111卷 382-389页

作者： Wang, Ying Lu, Chao Zhang, Xinran Tsinghua Univ Dept Elect Engn State Key Lab Control & Simulat Power Syst & Gene Beijing Peoples R China Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China

The time-varying characteristic of the power load can be tracked with the ambient signal based load model parameter identification method proposed recently. Meanwhile, the small fluctuations of the ambient signal bring higher requirement for optimization algorithm as well. The interior-point algorithm (IPA) and the activeset algorithm (ASA) are two typical traditional nonlinear constrained optimization algorithms, while the differential evolution algorithm (DEA) is an excellent heuristic search algorithm. Besides, the grid search algorithm (GSA) is a violent search algorithm, which is also an effective method considering the fact that the real load model parameters are unknown in practical power system. Based on the review of the basic idea of the four algorithms, the applicability of the four algorithms is comparatively assessed for ambient signal based load model parameter identification. Their performance is compared using ambient data from both simulation and field phasor measurement unit (PMU) in China Southern Power Grid considering the identification accuracy, calculation time, and the robustness to measurement error and algorithm parameters. Some general conclusions are drawn from the analysis for several cases.

关键词： Ambient signal based load model parameter identification active-set algorithm Differential evolution algorithm Grid search algorithm Interior-point algorithm

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Bio-inspired computational heuristics for Sisko fluid flow and heat transfer models

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APPLIED SOFT COMPUTING 2018年 71卷 622-648页

作者： Raja, Muhammad Asif Zahoor Mehmood, Ammara Rehman, Ateeq ur Khan, Asifullah Zameer, Aneela COMSATS Inst Informat Technol Dept Elect Engn Attock Pakistan Pakistan Inst Engn & Appl Sci Dept Elect Engn Islamabad Pakistan Preston Univ Kohat Dept Math Islamabad Campus Islamabad Pakistan Pakistan Inst Engn & Appl Sci Dept Comp & Informat Sci Islamabad Pakistan

A novel approach of integrated meta-heuristic computing is designed for Sisko fluid dynamics (SFD) system using artificial neural networks (ANN) based differential equation models being optimized with exploration capabilities of Genetic algorithms (GAs) and efficient convergence of active -set algorithm (ASA) for different scenarios based on variation of magnetic interaction parameter, stretching parameter, generalized Prandtl and Biot numbers. Governing partial differential equations (PDEs) of SFD system are converted into coupled nonlinear ordinary differential equations (ODEs) through similarity variables and then ANN based models are constructed for the transformed problem. These networks are trained globally using GAs with fine tuning by ASA for speedy optimization. Accurate and consistent convergence of this scheme is established by comparison of results with standard Adams numerical approach and further validated through statistical performance indices. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Artificial neural networks Integrated computing Genetic algorithms active-set algorithm Sisko fluid dynamics

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Efficient methods for solving the Stokes problem with slip boundary conditions

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MATHEMATICS AND COMPUTERS IN SIMULATION 2018年 145卷 114-124页

作者： Kucera, Radek Haslinger, Jaroslav Satek, Vaclav Jarosova, Marta VSB TU Ostrava 17 Listopadu 15-2172 Ostrava 70833 Czech Republic

The paper deals with the Stokes flow with the threshold slip boundary conditions. A finite element approximation of the problem leads to the minimization of a non-differentiable energy functional subject to two linear equality constraints: the impermeability condition on the slip part of the boundary and the incompressibility of the fluid. Eliminating the velocity components, one gets the smooth dual functional in terms of three Lagrange multipliers. The first Lagrange multiplier regularizes the problem. Its components are subject to simple bounds. The other two Lagrange multipliers treat the impermeability and the incompressibility conditions. The last Lagrange multiplier represents the pressure in the whole domain. The solution to the dual problem is computed by an active set strategy and a path-following variant of the interior-point method. Numerical experiments illustrate computational efficiency. (C) 2016 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved.

关键词： Stokes problem Slip boundary condition active-set algorithm Interior-point method

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Reconsidering Constraint Release for active-set Evolution Strategies 17

Reconsidering Constraint Release for Active-Set Evolution St...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Arnold, Dirk V. Dalhousie Univ Fac Comp Sci Halifax NS B3H 4R2 Canada

ISBN: (纸本)9781450349208

We consider the problem of solving constrained numerical optimization problems where the objective function is a black box, but the constraint functions are known explicitly. A recently proposed active-set approach implemented in an evolution strategy that interleaves the evolution of the active set with the search for better candidate solutions is able to solve unimodal problems from a commonly used test function set with relatively small numbers of objective function evaluations. We observe that the algorithm may under some conditions exhibit long phases of stagnation and propose a novel policy for considering constraints for release from the active set. The algorithm using the revised policy is seen to be able to avoid the stagnation observed in runs of the original strategy.

关键词： Stochastic black-box optimization constraint handling evolution strategy active-set algorithm

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Design of bio-inspired computational intelligence technique for solving steady thin film flow of Johnson-Segalman fluid on vertical cylinder for drainage problems

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JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS 2016年 60卷 59-75页

作者： Raja, Muhammad Asif Zahoor Shah, Fiaz Hussain Khan, Abdul Ahad Khan, Najeeb Alam COMSATS Inst Informat Technol Dept Elect Engn Attock Campus Attock 43600 Punjab Pakistan Univ Karachi Dept Math Sci Karachi 75270 Pakistan

In the present study, bio-inspired computing technique is designed for solving governing mathematical relation for steady thin film flow of Johnson-Segalman fluid on vertical cylinder for drainage problems using Artificial Neural Networks (ANNs), genetic algorithms (GAs) and active-set algorithm (ASA). The strength of ANN modeling is exploited for the transformed equation of drainage problem which is derived from original partial differential equation using similarity transform. Training of design parameter of ANNs is carried out with evolutionary computing approach based on GAs hybrid with ASA for rapid local convergence. Design scheme is evaluated for number of cases of all four scenarios of drainage problem based on variations in Stokes number, Weissenberg number, ratio of viscosities, and slip parameters. Comparison of the results is made with Adams numerical method for each case in order to validate the accuracy of the proposed scheme. Results of statistical analysis in terms of performance measures based on mean, standard deviation, mean absolute deviation, root mean square error and Nash-Sutcliffe efficiency as well as their global variations further established the worth of the given scheme for each variant of drainage problem. (C) 2015 Taiwan Institute of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

关键词： Thin film flow Non-Newtonian fluids Computational fluid dynamics Artificial Neural Networks Genetic algorithms active-set algorithm

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active set algorithm for mathematical programs with linear complementarity constraints

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APPLIED MATHEMATICS AND COMPUTATION 2011年第21期217卷 8291-8302页

作者： Yin, Hongxia Ding, Fei Zhang, Jianzhong Minnesota State Univ Mankato Dept Math & Stat Mankato MN 56001 USA Chinese Acad Sci Grad Univ CAS Res Ctr Fict Econ & Data Sci Beijing 100080 Peoples R China GuangDong Dev Bank Dept Risk Management Guangzhou 510080 Guangdong Peoples R China Chinese Univ Hong Kong Dept Syst Engn & Engn Management Hong Kong Hong Kong Peoples R China

In the paper, an incomplete active set algorithm is given for mathematical programs with linear complementarity constraints (MPLCC). At each iteration, a finite number of inneriterations are contained for approximately solving the relaxed nonlinear optimization problem. If the feasible region of the MPLCC is bounded, under the uniform linear independence constraint qualification (LICQ), any cluster point of the sequence generated from the algorithm is a B-stationary point of the MPLCC. Preliminary numerical tests show that the algorithm is promising. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Mathematical programs with linear complementarity constraints active-set algorithm B-stationary Uniform LICQ Convergence

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A new optimized Stockwell transform applied on synthetic and real non-stationary signals

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DIGITAL SIGNAL PROCESSING 2015年 46卷 226-238页

作者： Moukadem, Ali Bouguila, Zied Abdeslam, Djaffar Ould Dieterlen, Alain Univ Haute Alsace MIPS Lab Mulhouse France

The aim of this paper is to improve the energy concentration of the Stockwell transform (S-transform) in the time-frequency domain. A modified S-transform is proposed with several parameters to control the width of a hybrid Gaussian window. A constrained optimization problem is proposed based on an energy concentration measure as objective function and inequalities constraints to define the bounds of the Gaussian window. An active-set algorithm is applied to resolve the optimization problem. The optimization of the energy concentration in the time-frequency plane can lead to more reliable applications for non-stationary signals. The simulation results show a significant improvement of the proposed methodology most notably in the presence of noise comparing with the standard S-transform and existing modified S-transform in the literature. Moreover, comparison with other known time-frequency transforms such as Short-time Fourier transform (STFT) and smoothed-pseudo Wigner-Ville distribution (SPWVD) is also performed and discussed. The proposed S-transform is tested also on real non-stationary signals through an example of split detection in heart sounds. (C) 2015 Elsevier Inc. All rights reserved.

关键词： Time-frequency Stockwell transform Energy concentration active-set algorithm Heart sounds

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REGULARIZED NONNEGATIVE MATRIX FACTORIZATION: GEOMETRICAL INTERPRETATION AND APPLICATION TO SPECTRAL UNMIXING

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2014年第2期24卷 233-247页

作者： Zdunek, Rafal Wroclaw Univ Technol Dept Elect PL-50370 Wroclaw Poland

Nonnegative Matrix Factorization (NMF) is an important tool in data spectral analysis. However, when a mixing matrix or sources are not sufficiently sparse, NMF of an observation matrix is not unique. Many numerical optimization algorithms, which assure fast convergence for specific problems, may easily get stuck into unfavorable local minima of an objective function, resulting in very low performance. In this paper, we discuss the Tikhonov regularized version of the Fast Combinatorial NonNegative Least Squares (FC-NNLS) algorithm (proposed by Benthem and Keenan in 2004), where the regularization parameter starts from a large value and decreases gradually with iterations. A geometrical analysis and justification of this approach are presented. The numerical experiments, carried out for various benchmarks of spectral signals, demonstrate that this kind of regularization, when applied to the FC-NNLS algorithm, is essential to obtain good performance.

关键词： blind source separation nonnegative matrix factorization active-set algorithm regularized NMF polytope approximation

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Solving a discrete multimodal transportation network design problem

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TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2014年 49卷 73-86页

作者： Zhang, Lihui Yang, Hai Wu, Di Wang, Dianhai Zhejiang Univ Inst Transportat Engn Hangzhou 310058 Zhejiang Peoples R China Hong Kong Univ Sci & Technol Dept Civil & Environm Engn Kowloon 999077 Hong Kong Peoples R China Univ Florida Dept Civil & Coastal Engn Gainesville FL 32611 USA

This paper investigates the multimodal network design problem (MMNDP) that optimizes the auto network expansion scheme and bus network design scheme in an integrated manner. The problem is formulated as a single-level mathematical program with complementarity constraints (MPCC). The decision variables, including the expanded capacity of auto links, the layout of bus routes, the fare levels and the route frequencies, are transformed into multiple sets of binary variables. The layout of transit routes is explicitly modeled using an alternative approach by introducing a set of complementarity constraints. The congestion interaction among different travel modes is captured by an asymmetric multimodal user equilibrium problem (MUE). An active-set algorithm is employed to deal with the MPCC, by sequentially solving a relaxed MMNDP and a scheme updating problem. Numerical tests on nine-node and Sioux Falls networks are performed to demonstrate the proposed model and algorithm. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Multimodal network design Road capacity expansion Bus route layout active-set algorithm Multimodal user equilibrium

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