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Comparative research of optimization algorithms for parameters calibration of watershed hydrological model

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2016年第3期16卷 653-669页

作者： Huo, Jiuyuan Liu, Liqun Zhang, Yaonan Lanzhou Jiaotong Univ Sch Elect & Informat Engn Lanzhou 730070 Gansu Peoples R China Gansu Agr Univ Coll Informat Sci & Technol Lanzhou Gansu Peoples R China Chinese Acad Sci Cold & Arid Reg Environm & Engn Res Inst Lanzhou Gansu Peoples R China Gansu Data Engn & Technol Res Ctr Resources & Env Lanzhou Gansu Peoples R China

Parameter optimization and calibration of the hydrological model has been one of the important research fields in hydrological forecasting. This paper is written to address the inherent defects that traditional parameter optimization of Xinanjiang hydrological model with a single objective entails. These methods cannot fully exploit hydrological characteristics information from hydrological observation. We selected the Nash Sutcliffe coefficient, which is known to be biased for high flows and the logarithmic form of the Nash Sutcliffe coefficient that emphasize low-flow values as the objective functions. Then, we adopted the multi-objective optimization algorithms, such as the Nondominated Sorted Genetic algorithm-II (NSGAII) and the Third Evolution Step of Generalized Differential Evolution (GDE3), and the single-objective optimization algorithm, Simulated Annealing (sa). These algorithms were applied in Heihe River Basin to calibrate parameters of the Xinanjiang hydrological model for long-term prediction of river discharges. Through the evaluation of the Pareto optimal parameter set derived from multi-objective optimization algorithms and the optimal solution obtained from the single objective algorithm, the results showed that the multi-objective optimization algorithms, in particular the NSGA-II algorithm, perform best to locate the Pareto optimal solutions in the parameter search space. They can also obtain better results with respect to the model parameters calibrated by the single objective algorithm. The major contribution of this work is the comparative application research of single-objective optimization with the multi-objective optimization algorithms for the parameters optimization of the Xinanjiang model in the Heihe River basin.

关键词： Hydrological model parameter calibration multi-objective optimization algorithm Xinanjiang model NSGAII algorithm GDE3 algorithm sa algorithm

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A fuzzy DEMATEL - Fuzzy Binary Logistic Regression approach to evaluate and prioritize risks and simulated annealing optimization algorithm (an empirical study in energy projects)

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INTERNATIONAL JOURNAL OF MANAGING PROJECTS IN BUSINESS 2020年第5期13卷 1025-1050页

作者： Hashemi, Reyhane Kamranrad, Reza Bagheri, Farnoosh Emami, Iman Univ Sci & Culture Tehran Iran Semnan Univ Dept Ind Engn Semnan Iran Nardis Co Dept Change Management Tehran Iran

Purpose The aim of this paper is to predict and minimize the risks of oil, gas and petrochemical projects. Besides, reducing the likelihood of occurrence and minimizing risks impact on the projects to reduce the probable costs and improve the economic situation is another purpose of this paper. Design/methodology/approach This paper provides a fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) - a technique that assist to solve decision-making problems - and IP (Impact & Probability) table methods to identify and analyze critical risks in energy projects, and then fuzzy Binary Logistic Regression (BLR) in order to predict the probability of each level of risk for more efficient risk management in projects. Furthermore, in this paper, the fuzzy BLR (FBLR) is optimized such that the probability of a high level of risk for the implementation of the project has been minimized using meta-heuristic algorithm. Findings The results from the point of view of experts show that combination of fuzzy DEMATEL with FBLR approach as well as using sa algorithm, in order to optimize the high level of risks, can provide a smart approach to managing risks with more success. Practical implications The application of the proposed method is illustrated via a real data set from energy projects. Originality/value We propose combined fuzzy DEMATEL and FBLR methods to predict and optimize the risks of the energy projects, which is the innovation of this paper.

关键词： Fuzzy DEMATEL Fuzzy Binary Logistic Regression Impact-Probability table Critical risk sa algorithm Optimization

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Application of Genetic algorithm in modeling of Shortest Path problem

Application of Genetic Algorithm in modeling of Shortest Pat...

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Chinese Automation Congress (CAC)

作者： Yang, Zhihui Xia, Huiwen Su, Fuwen Zhao, Jiayu Feng, Fan Wuhan Univ Technol Sch Automat Wuhan Peoples R China Wuhan Univ Technol Sch Comp Sci & Technol Wuhan Peoples R China

ISBN: (纸本)9781728176871

For a long time, people have been looking for the best way to solve problems to improve work efficiency. Shortest path as a figure with a classical problem in the study of network technology in computer science, communications, and operations research, geographic information science and other fields has a very wide range of applications, for solving the problem is not only has important theoretical significance, but also has important practical value, the problem solving algorithm design and improving the research has important significance [1-3]. This paper introduces several commonly used algorithms to solve the shortest path problem, analyses their advantages and disadvantages. Then Genetic algorithm is introduced and the results is compared with Simulated Annealing algorithm. The results of comparison shows that the Genetic algorithm is much better than Simulated Annealing algorithm in this problem. In many existing literatures, the author only elaborates a certain method or solves a specific problem through a certain method, which to a large extent makes the advantages of the method described in the literature unable to be fully displayed. In this paper, a great improvement has been made in this aspect. This Simulated Annealing algorithm is introduced while the Genetic algorithm is described. Simulation results show that Genetic algorithm is more effective than Simulated Annealing algorithm in path planning and result optimization in solving the shortest path problem.

关键词： shortest path problem GA algorithm sa algorithm material allocation and delivery

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Optimized Implementation of Discrete Wavelet Transform with Area Efficiency

Optimized Implementation of Discrete Wavelet Transform with ...

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IEEE International Multi Conference on Automation, Computing, Control, Communication and Compressed Sensing (iMac4s)

作者： John, sani Jose, Manu Viswajyothi Coll Engn & Technol Vazhakkulam ECE Dept Muvattupuzha Kerala India

ISBN: (纸本)9781467350907;9781467350891

The objective of this paper is to illustrate a comparative study on the performance of DWT with the multiplier reducing algorithms. The optimization techniques were based on the identification of algorithms, which could exploit the FPGA features. Discrete Wavelet Transform (DWT) is one of the most used techniques for image compression and is applied in a large category of applications for multi resolution analysis of signals. DWT can provide significant compression ratios without great loss of visual quality than the previous techniques such as the Discrete Cosine Transform (DCT) and the Discrete Fourier Transform (DFT). This work provides an analysis between the conventional VLSI implementation techniques as against an area efficient realization approach. This is expected to provide a reduction in hardware complexity and also an increase in computational speed. The reduction in the resource utilization improves the system performance by means of reduction in power consumption as well as the reduction in delay.

关键词： DA algorithm DWT sa algorithm

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Simulated Annealing for Constructing Binary Covering Arrays of Variable Strength

Simulated Annealing for Constructing Binary Covering Arrays ...

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2010 IEEE World Congress on Computational Intelligence

作者： Torres-Jimenez, Jose Rodriguez-Tello, Eduardo CINVESTAV Tamaulipas Informat Technol Lab Victoria Tamps 87130 Mexico

ISBN: (纸本)9781424481262

This paper presents new upper bounds for binary covering arrays of variable strength constructed by using a new Simulated Annealing (sa) algorithm. This algorithm incorporates several distinguished features including an efficient heuristic to generate good quality initial solutions, a compound neighborhood function which combines two carefully designed neighborhoods and a fine-tuned cooling schedule. Its performance is investigated through extensive experimentation over well known benchmarks and compared with other state-of-the-art algorithms, showing that the proposed sa algorithm is able to outperform them.

关键词： sa algorithm binary covering array fine-tuned cooling schedule neighborhood function simulated annealing simulated annealing variable strength

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UAV path planning based on K-means algorithm and simulated annealing algorithm 37

UAV path planning based on K-means algorithm and simulated a...

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37th Chinese Control Conference (CCC)

作者： Yue, Xiu Zhang, Wei Univ Shanghai Sci & Technol Minist Educ Shanghai Key Lab Modem Opt Syst Shanghai 200093 Peoples R China Univ Shanghai Sci & Technol Minist Educ Engn Res Ctr Opt Instrument & Syst Shanghai 200093 Peoples R China

ISBN: (纸本)9789881563958

This paper proposed a new method for unmanned aerial vehicle (UAV) path planning based on K-means algorithm and simulated annealing (sa) algorithm, which solves the problem for multi-UAVs with multi-mission under complicated constraints. Firstly, the model is established for the no-fly zone, the target zone and the valid zone for cruise within it in the mission area. Then, the decomposition technique decomposes the valid area into multiple sub-target points reasonably. Secondly, the K-means algorithm is used to cluster the target points of UAV cruise, which solves the problem for UAV cruise range and scheduling issues. Combining the sa algorithm for the similar sub-target route planning, this technique increases the coverage of the UAVs in the sub-target area of cruise valid area. Finally, taking the real data of UAVs in earthquake relief as an example, the effectiveness and robustness of the proposed method is validated by simulation experiments.

关键词： UAV model area decomposition technique K-means algorithm sa algorithm

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Time Optimal Trajectory Planning Based on Simulated Annealing algorithm for a Train Uncoupling Robot 29

Time Optimal Trajectory Planning Based on Simulated Annealin...

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第29届中国控制与决策会议

作者： Yao Jianjun Sun Cheng Zhang Le Xiao Chenguang Yang Ming Zhang Shiqi College of Mechanical and Electrical Engineering Harbin Engineering University

ISBN: (纸本)9781509046584

A train uncoupling robot with four degrees-of-freedom has been developed to replace humans in the uncoupling task in a marshalling field for designating freight cars to different *** can avoid picking the wrong hook,improve work efficiency and reduce the workload of *** planning can ensure that the robot moves to target position smoothly and *** Annealing(sa) algorithm based on penalty function is proposed to get the optimal time of trajectory planning in this *** optimal trajectories of robot joints are obtained under the constraints of maximum speed,maximum acceleration and maximum jerk *** can be seen from the simulation curves that the robot can move smoothly and there is no impact phenomenon.

关键词： Train Uncoupling Robot Trajectory Planning Time Optimal sa algorithm

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Wireless positioning method based on dynamic objective function under mixed LOS/NLOS conditions 5

Wireless positioning method based on dynamic objective funct...

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5th IEEE Conference on Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS)

作者： Guo Qing Ke Wei Tang Wanchun Nanjing Normal Univ Sch Phys Sci & Technol Jiangsu Key Lab Optoelect Technol Nanjing 210023 Jiangsu Peoples R China Jiangsu Ctr Collaborat Innovat Geog Informat Reso Nanjing 210023 Jiangsu Peoples R China

ISBN: (纸本)9781538637555

The current wireless positioning technology faces with the influence of the mixed line of sight(LOS) and non-LOS(NLOS) environment. The measurement error will become larger under NLOS environment and then result in a significant reduction of accuracy and instability of positioning results. Therefore, the research of wireless location under the LOS/ NLOS environment has become research hotspots. In this paper, a dynamic positioning method based on the received signal strength(RSS) is proposed to solve this current hot issue. This method firstly adopts mixed Gauss model to describe the LOS and NLOS propagation effects, respectively, which can avoid the LOS/ NLOS identifying problem. At the same time, the simulated annealing (sa) algorithm is exploited to overcome the local optimal solution problem. Simulation results show that our method can achieve good positioning performance under mixed LOS/NLOS environment.

关键词： LOS NLOS mixed Gauss model sa algorithm

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Solving Container Loading Problem With Simulated Annealing algorithm 15

Solving Container Loading Problem With Simulated Annealing A...

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15th IEEE International Symposium on Computational Intelligence and Informatics

作者： Can, Okan sahingoz, Ozgur Koray Turkish Air Force Acad Dept Comp Engn Istanbul Turkey

ISBN: (纸本)9781479953370

In the economic world, transportation is very important and decreasing transportation cost is a challenging issue. To decrease this cost, increasing the efficiency of loading containers is very important, and this problem mainly named as Container Loading Problem(CLP). There are many researches about CLP with different type of approaches. In the literature, solutions are generally lined up as Heuristic and Meta-Heuristic approaches. Simulated annealing (sa) algorithm is a meta-heuristic approach. The most important advantage of sa is avoiding from local optimums. In this paper, a single CLP is solved by using simulated annealing algorithm. Proposed system algorithm and experimental results are presented. These results showed that sa is an acceptable solution approach for CLP type problems.

关键词： goods distribution loading simulated annealing transportation CLP sa algorithm container loading problem metaheuristic approach simulated annealing algorithm transportation cost Containers Heuristic algorithms Loading Organizations Simulated annealing Stability analysis Transportation

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A Hybrid Dung Beetle Optimization algorithm with Simulated Annealing for the Numerical Modeling of Asymmetric Wave Equations

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Applied Geophysics 2024年第3期21卷 513-527,618页

作者： Wei Xu-ruo Bai Wen-lei Liu Lu Li You-ming Wang Zhi-yang College of Information Science and Technology Beijing University of Chemical TechnologyBeijingPRC Key Laboratory of Petroleum Resources Research Institute of Geology and GeophysicsChinese Academy of SciencesBeijingPRC University of Chinese Academy of Sciences BeijingChina Aramco Research Center-Beijing Aramco AsiaBeijingChina

In the generalized continuum mechanics(GCM)theory framework,asymmetric wave equations encompass the characteristic scale parameters of the medium,accounting for microstructure *** study integrates two theoretical branches of the GCM,the modified couple stress theory(M-CST)and the one-parameter second-strain-gradient theory,to form a novel asymmetric wave equation in a unified *** modeling of the asymmetric wave equation in a unified framework accurately describes subsurface structures with vital implications for subsequent seismic wave inversion and imaging ***,employing finite-difference(FD)methods for numerical modeling may introduce numerical dispersion,adversely affecting the accuracy of numerical *** design of an optimal FD operator is crucial for enhancing the accuracy of numerical modeling and emphasizing the scale ***,this study devises a hybrid scheme called the dung beetle optimization(DBO)algorithm with a simulated annealing(sa)algorithm,denoted as the sa-based hybrid DBO(SDBO)*** FD operator optimization method under the SDBO algorithm was developed and applied to the numerical modeling of asymmetric wave equations in a unified *** the DBO and sa algorithms mitigates the risk of convergence to a local *** numerical dispersion outcomes underscore that the proposed SDBO algorithm yields FD operators with precision errors constrained to 0.5‱while encompassing a broader spectrum *** result confirms the efficacy of the SDBO ***,the numerical modeling results demonstrate that the new FD method based on the SDBO algorithm effectively suppresses numerical dispersion and enhances the accuracy of elastic wave numerical modeling,thereby accentuating scale *** result is significant for extracting wavefield perturbations induced by complex microstructures in the medium and the analysis of scale effects.

关键词： Finite-difference Asymmetric wave equation Numerical modeling DBO algorithm sa algorithm

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