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IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Yang, Ze Liu, Jing Wu, Kai Xidian Univ Sch Artificial Intelligence Xian Shaanxi Peoples R China

ISBN: (纸本)9781728121536

Fuzzy cognitive maps (FCMs) are generally applied to model and analyze complex dynamical systems. However, the accuracy of population-based FCM learning algorithms is relatively low. Boosting is an effective method to improve the accuracy of any learning algorithm. To this end, we combine FCMs with boosting, termed as boosting fuzzy cognitive maps (BFCMs). The BFCM is an extension of FCMs and has a better performance on fast numerical reasoning than FCMs. In this paper, a real-coded genetic algorithm, which is a popular population-based learning algorithm, is improved on mutation operator and applied to learn the BFCM models, termed as RCGA-BFCM. In the experiments, RCGA-BFCM is applied to learn the BFCM from synthetic data with varying sizes and densities. The experimental results show that RCGA-BFCM can learn BFCMs with high accuracy from synthetic data. In addition, the performance of RCGA-BFCM is validated on the benchmark datasets DREAM3 and DREAM4. The experimental results show that RCGA-BFCM outperforms other learning algorithms obviously, which illustrates that RCGA-BFCM can reconstruct gene regulatory networks (GRNs) effectively.

关键词： fuzzy cognitive maps boosting real-coded genetic algorithm

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Optimization of Cold-Formed Steel Portal Frame Topography Using real-coded genetic algorithm

Optimization of Cold-Formed Steel Portal Frame Topography Us...

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12th East Asia-Pacific Conference on Structural Engineering and Construction (EASEC)

作者： Phan, D. T. Lim, J. B. P. Ming, C. S. Y. Tanyimboh, T. Issa, H. Sha, W. Queens Univ Belfast Sch Planning Architecture & Civil Engn Belfast BT7 1NN Antrim North Ireland Univ Strathclyde Dept Civil Engn Glasgow G1 1XQ Lanark Scotland Nottingham Trent Univ Sch Architecture Design & Built Environm Nottingham England

Cold-formed steel portal frames are a popular form of construction for single-storey buildings of spans of up to 30 m. Such buildings typically use cold-formed steel channel-sections for the columns and rafters, with joints formed through back-to-back gusset plates bolted to the webs of the channel-sections. For such buildings, for frames of a given topography (where the span, height, pitch and frame spacing are all known) the choice of the cold-formed steel channel-section that results in either the minimum weight or minimum cost for the building can be determined easily for a given cold-formed steel manufacturer. This is because a typical cold-formed steel manufacturer would typically only have a finite number of discrete sections in their catalogue, and so in conjunction with frame analysis and design member checks, all the different permutations of sections can be considered. However, it is well-known that the minimum weight or minimum cost of a frame will not necessarily yield the most economical solution of the whole of building. In this paper, a study is conducted to investigate effects of frame topography on either the frame weight or cost per meter length of building. Thereafter, an optimization technique that uses a real-coded genetic algorithm is applied to search for the optimum topography of steel portal frame for a building. The advantage of using a real-coded genetic algorithm is that a high precision optimum solution can be achieved easily when the optimization process works in the continuous search space. The result of a parametric study that investigates the effect of typical wind zones in Australia on the optimum parameters of building geometry is presented.

关键词： Cold-formed portal frames topography optimization real-coded genetic algorithm

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Optimal Control Solving of Polymer Flooding Based on real-coded genetic algorithm

Optimal Control Solving of Polymer Flooding Based on Real-co...

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8th World Congress on Intelligent Control and Automation (WCICA)

作者： Lei, Yang Li, Shurong Zhang, Xiaodong China Univ Petr Coll Informat & Control Engn Dongying Shandong Peoples R China

ISBN: (纸本)9781424467129

This paper researches the optimization of injection strategies of polymer flooding in oil recovery. An optimal control problem (OCP) of a distributed parameter system (DPS) is established, in which the functional of performance index is profit maximum and the governing equations are the fluid equations in porous media. The control variables are chosen as the polymer concentrations and the switching time of a slug. The constraint conditions include boundary constraints and other inequality constraints. The method based on real-coded genetic algorithm (RGA) is presented for numerically solving the OCP. Finally, an example of the OCP for polymer flooding is exposed and the results show the effectiveness of the RGA method.

关键词： Optimal control Polymer flooding real-coded genetic algorithm

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Time-domain reconstruction of a two-dimensional dielectric cylinder by using real-coded genetic algorithm

Time-domain reconstruction of a two-dimensional dielectric c...

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Asia-Pacific Conference on Environmental Electromagnetics

作者： Tan Qiongliang Zhu Feng Zhang Saiqiao Liu Lina SW Jiaotong Univ Coll Elect Engn Chengdu 610031 Peoples R China

ISBN: (纸本)1424401836

Time-domain reconstruction of a two-dimensional dielectric cylinder by using real-coded genetic algorithm is presented in this paper. Scattering from the dielectric cylinder is solved by using finite-difference, time-domain method (FDTD). The dielectric cylinder is represented by a set of geometrical and constitutive parameters. The electromagnetic inverse scattering problem is to retrieve these parameters given the measured. time-domain scattered electric fields on finite receivers. Its cast into an optimization. problem by defining the objective function as the relative error between the measured and simulated time-domain scattered electric fields on finite receivers. The optimization problem is then solved by using the real-coded genetic algorithm. Good agreement is observed between true profiles and numerically reconstructed ones.

关键词： FDTD real-coded genetic algorithm electromagnetic inverse scattering

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A Study on real-coded genetic algorithm for Process Optimization Using Ranking Selection, Direction-Based Crossover and Dynamic Mutation

A Study on Real-Coded Genetic Algorithm for Process Optimiza...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Chuang, Yao-Chen Chen, Chyi-Tsong Feng Chia Univ Dept Chem Engn Taichung 40724 Taiwan

ISBN: (纸本)9781424478354

In this paper, a novel and efficient real-coded genetic algorithm (RCGA) for process optimization is developed. The proposed RCGA is equipped with Ranking Selection (RS), Direction-Based Crossover (DBX) and Dynamic Random Mutation (DRM) operators. The RS operator is used to eliminate the bad solutions and reproduce good solutions, making the whole population to achieve a better average fitness. The DBX operator uses relative fitness information to direct the crossover toward a direction that significantly improves the objective fitness. The DRM operator prevents the premature convergence of RCGA and at the same time increases the precision of the searched solution. The effectiveness and application of the proposed RCGA are demonstrated through a variety of single-objective optimization benchmark problems. For comparative study, other existing RCGAs with different evolution operators are also performed to the same problem set. Extensive experiment results reveal that the proposed RCGA provides a significantly faster convergence speed and much better search performance than comparative methods.

关键词： component real-coded genetic algorithm direction-based crossover dynamic mutation constrained optimization process optimization

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A New Optimization Model for MLP Hyperparameter Tuning: Modeling and Resolution by real-coded genetic algorithm

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NEURAL PROCESSING LETTERS 2024年第2期56卷 105-105页

作者： El-Hassani, Fatima Zahrae Amri, Meryem Joudar, Nour-Eddine Haddouch, Khalid Sidi Mohamed Ben Abdellah Univ ENSA Engn Syst & Applicat Lab Fes Morocco Sidi Mohamed Ben Abdellah Univ Fac Sci & Technol Fez Dept Math Modelling & Math Struct Lab Fes Morocco

This paper introduces an efficient real-coded genetic algorithm (RCGA) evolved for constrained real-parameter optimization. This novel RCGA incorporates three specially crafted evolutionary operators: Tournament Selection (RS) with elitism, Simulated Binary Crossover (SBX), and Polynomial Mutation (PM). The application of this RCGA is directed toward optimizing the MLPRGA+5 model. This model is designed to configure Multilayer Perceptron neural networks by optimizing both their architecture and associated hyperparameters, including learning rates, activation functions, and regularization hyperparameters. The objective function employed is the widely recognized learning loss function, commonly used for training neural networks. The integration of this objective function is supported by the introduction of new variables representing MLP hyperparameter values. Additionally, a set of constraints is thoughtfully designed to align with the structure of the Multilayer Perceptron (MLP) and its corresponding hyperparameters. The practicality and effectiveness of the MLPRGA+5 approach are demonstrated through extensive experimentation applied to four datasets from the UCI machine learning repository. The results highlight the remarkable performance of MLPRGA+5, characterized by both complexity reduction and accuracy improvement.

关键词： real-coded genetic algorithm Hyperparameter Constrained optimization Multi-layer perceptron

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Optimization of Cold-Formed Steel Portal Frame Topography Using real-coded genetic algorithm

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Procedia Engineering 2011年 14卷 724-733页

作者： D.T. Phan J.B.P. Lim C.S.Y. Ming T. Tanyimboh H. Issa W. Sha School of Planning Architecture and Civil Engineering Queen's University Belfast UK Department of Civil Engineering University of Strathclyde Glasgow UK School of Architecture Design and Built Environment Nottingham Trent University UK

Cold-formed steel portal frames are a popular form of construction for single-storey buildings of spans of up to 30 m. Such buildings typically use cold-formed steel channel-sections for the columns and rafters, with joints formed through back-to-back gusset plates bolted to the webs of the channel-sections. For such buildings, for frames of a given topography (where the span, height, pitch and frame spacing are all known) the choice of the cold-formed steel channel-section that results in either the minimum weight or minimum cost for the building can be determined easily for a given cold-formed steel manufacturer. This is because a typical cold-formed steel manufacturer would typically only have a finite number of discrete sections in their catalogue, and so in conjunction with frame analysis and design member checks, all the different permutations of sections can be considered. However, it is well-known that the minimum weight or minimum cost of a frame will not necessarily yield the most economical solution of the whole of building. In this paper, a study is conducted to investigate effects of frame topography on either the frame weight or cost per meter length of building. Thereafter, an optimization technique that uses a real-coded genetic algorithm is applied to search for the optimum topography of steel portal frame for a building. The advantage of using a realcoded genetic algorithm is that a high precision optimum solution can be achieved easily when the optimization process works in the continuous search space. The result of a parametric study that investigates the effect of typical wind zones in Australia on the optimum parameters of building geometry is presented.

关键词： Cold-formed portal frames topography optimization real-coded genetic algorithm

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Multiobjective geometry optimization of microchannel heat exchanger using real-coded genetic algorithm

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APPLIED THERMAL ENGINEERING 2022年 202卷 1页

作者： Garcia, John Carlo S. Tanaka, Hiroki Giannetti, Niccolo Sei, Yuichi Saito, Kiyoshi Houfuku, Mamoru Takafuji, Ryoichi Waseda Univ Dept Appl Mech & Aerosp Engn Tokyo 1698555 Japan Univ Philippines Dept Mech Engn Quezon City 1101 Philippines Waseda Univ Waseda Inst Adv Study Tokyo 1698050 Japan Waseda Univ Interdisciplinary Inst Thermal Convers Engn & Mat Tokyo 1698555 Japan Univ Electrocommun Dept Informat Tokyo 1828585 Japan Hitachi Johnson Controls Air Conditioning Inc 500 TomidaOhira Machi Tochigi City Tochigi 3294404 Japan

In this paper, a multiobjective optimization of the structure of a flat-tubed microchannel heat exchanger is performed to reduce its volume and fan power at a specified capacity. Design variables include tube height, tube width, tube length, fin height, and fin pitch. A weight-based, real-coded genetic algorithm is implemented to optimize the design variables within their specified range of dimensions. To further improve the numerical simulations of the microchannel heat exchanger performance, correlations for the air-side Nusselt number, friction factor, and fin efficiency are developed and validated. In the optimization, the Pareto optimal fronts are obtained by varying weights of the two conflicting objectives. A reference microchannel heat exchanger operating at different capacities is optimized. Results show that the volume and fan power of the reference microchannel heat exchanger can be reduced by up to 45% and 51% respectively, depending on the weighting factor selected. The optimization approach of this study provides the optimal solutions at the given domain of geometric parameter dimensions.

关键词： Microchannel heat exchanger Optimization real-coded genetic algorithm

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A study on improving the convergence of the real-coded genetic algorithm for electromagnetic inverse scattering of multiple perfectly conducting cylinders

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IEICE TRANSACTIONS ON ELECTRONICS 2002年第7期E85C卷 1460-1471页

作者： Qing, AY Lee, CK Natl Univ Singapore Temasek Labs Singapore 119260 Singapore VS Elect Pte Ltd Singapore 569876 Singapore Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

A study on improving the performance of the real-coded genetic algorithm for electromagnetic inverse scattering of two-dimensional perfectly conducting cylinders is presented. Three schemes, namely, the penalty function approach, the closed cubic B-splines local shape function approach and the adaptive hybrid algorithm approach are proposed to deal with the problem. These schemes can be used separately or be combined to improve the performance. Numerical examples validate the schemes.

关键词： real-coded genetic algorithm penalty function closed cubic B-splines adaptive hybrid algorithm

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A Proposal of genetic Operations for BSIM Parameter Extraction Using real-coded genetic algorithm

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2011年第8期15卷 1131-1138页

作者： Nishiba, Ai Kawanaka, Hiroharu Takase, Haruhiko Tsuruoka, Shinji Mie Univ Grad Sch Engn 1577 Kurima Machiya Tsu Mie 5148507 Japan Mie Univ Grad Sch Reg Innovat Studies Tsu Mie 5148507 Japan

This paper discusses genetic operations and their effects on evolution of GA in BSIM parameter extraction problems. Generally, real-coded genetic algorithm (RCGA) using Simplex Crossover (SPX) is often employed to extract BSIM parameter sets. BSIM parameters, however, have recommended operating ranges. There are regarded as constraints, thus all extracted parameters have to be satisfied them. In many cases, when the number of parameters becomes large, the conventional methods generate a lot of infeasible solutions because SPX makes offspring on the simplex plane expanded by epsilon parameter. This makes search efficiency of GA reduce drastically. Because of these factors, we propose genetic operations considering the constraints to prevent reduction of search efficiency of GA. In this paper, some experiments using actual static characteristic curves of MOS-FET were conducted to validate the proposed method. This paper also discussed the effectiveness of the proposed method.

关键词： BSIM parameter extraction problem real-coded genetic algorithm simplex crossover genetic operations constraints

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