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Smart prediction of liquefaction-induced lateral spreading

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Journal of Rock Mechanics and Geotechnical eng.neering 2024年第6期16卷 2310-2325页

作者： Muhammad Nouman Amjad Raja Tarek Abdoun Waleed El-Sekelly New York university(NYU)Abu Dhabi Abu Dhabi129188United Arab Emirates university of Management and Technology Lahore54372Pakistan Department of Civil and Environmental eng. Rensselaer Polytechnic Institute(RPI)1108th StreetJEC 4049TroyNY12180USA Department of Structural eng.neering Mansoura UniversityMansoura35516Egypt

The prediction of liquefaction-induced lateral spreading/displacement(Dh)is a challeng.ng task for civil/geotechnical *** this study,a new approach is proposed to predict Dh using gene expression programming(GEP).Based on statistical reasoning,individual models were developed for two topographies:free-face and gently sloping *** with a comp.rison with conventional approaches for predicting the Dh,four additional regression-based soft comp.ting models,*** process regression(GPR),relevance vector machine(RVM),sequential minimal optimization regression(SMOR),and M5-tree,were developed and comp.red with the GEP *** results indicate that the GEP models predict Dh with less bias,as evidenced by the root mean square error(RMSE)and mean absolute error(MAE)for training(i.e.1.092 and 0.815;and 0.643 and 0.526)and for testing(i.e.0.89 and 0.705;and 0.773 and 0.573)in free-face and gently sloping ground topographies,*** overall performance for the free-face topology was ranked as follows:GEP>RVM>M5-tree>GPR>SMOR,with a total score of 40,32,24,15,and 10,*** the gently sloping condition,the performance was ranked as follows:GEP>RVM>GPR>M5-tree>SMOR with a total score of 40,32,21,19,and 8,***,the results of the sensitivity analysis showed that for both free-face and gently sloping ground,the liquefiable layer thickness(T_(15))was the major parameter with percentage deterioration(%D)value of 99.15 and 90.72,respectively.

关键词： Lateral spreading Intelligent modeling Gene expression programming(GEP) Closed-form solution Feature importance

A trust region-CG algorithm for deblurring problem in atmospheric image reconstruction

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sci.nce China Mathematics 2002年第6期45卷 731-740页

作者：王彦飞袁亚湘张洪超 Stt. Key Lab. of sci. and eng. comp. Inst. Compl. Math. Sci./Eng. Comp. Acad. of Math. and System Sciences Beijing 100080 China

In this paper we solve large scale ill-posed problems, particularly the image restoration problem in atmospheric imaging sci.nces, by a trust region-CG algorithm. Image restoration involves the removal or minimization of degradation (blur, clutter, noise, etc.) in an image using a priori knowledge about the degradation phenomena. Our basic technique is the so-called trust region method, while the subproblem is solved by the truncated conjugate gradient method, which has been well developed for well-posed *** trust region method, due to its robustness in global convergence, seems to be a promising way to deal with ill-posed problems.

关键词： image reconstruction, ill-posed problems, truncated CG, trust region.

Robot soccer simulation comp.tition platform based on multi-agent

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 203-206页

作者：洪炳熔高全胜褚海涛 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

Presents the robot soccer software simulation platform to be firstly used at FIRA Robot World Cup China 2001, introduces the system’s purpose and design plan; discusses the system core server configuration and working principle; describes the operating method and how to develop comp.tition strategy, and refers to the teams to take part in FIRA Robot World Cup China 2001 and investigators who are interested in the distributed multi agent system.

关键词： multi agent system simulation comp.tition server client.

Pass-ball trainning based on genetic reinforcement learning

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 279-282页

作者：褚海涛洪炳熔 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

Introduces a mixture genetic algorithm and reinforcement learning comp.tation model used for independent agent learning in continuous, distributive, open environment, which takes full advantage of the reactive and robust of reinforcement learning algorithm and the property that genetic algorithm is suitable to the problem with high dimension,large collectivity, comp.ex environment, and concludes that through proper training, the result verifies that this method is available in the comp.ex multi agent environment.

关键词： reinforcement genetic multi agent genetic reinforcement learning

Design of robot soccer simulator

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 256-260页

作者：高全胜洪炳熔褚海涛 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

Robot soccer game is an interesting emerging domain for multiple cooperative robotic system. This paper discusses the detailed design of a simulator, and describes the architecture of soccer server and client in detail. This simulator is sufficiently flexible and robust for the users to develop strategies for a simulated comp.tition and to test algorithms of intelligent robotics.

关键词： robotic soccer simulator client server

Robot soccer action selection based on Qlearning

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 212-214页

作者：刘新宇洪炳熔 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

This paper researches robot soccer action selection based on Q learning .The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations ... 详细信息

关键词： robot soccer action selection Q learning neural network

Layered learning of soccer robot based on artificial neural network

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 276-278页

作者：韩学东洪炳熔 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

Discusses the application of artificial neural network for MIROSOT, introduces a layered model of BP network of soccer robot for learning basic behavior and cooperative behavior, and concludes from experimental result... 详细信息

关键词： artificial neural network (ANN) MIROSOT layered learning soccer robot

Genetic algorithm-fuzzy based dynamic motion planning approach for a mobile robot

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 228-232页

作者：王月海洪炳熔 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

Presents the mobile robots dynamic motion planning problem with a task to find an obstacle free route that requires minimum travel time from the start point to the destination point in a changing environment, due to the obstacle’s moving. An Genetic Algorithm fuzzy (GA Fuzzy) based optimal approach proposed to find any obstacle free path and the GA used to select the optimal one, points out that using this learned knowledge off line, a mobile robot can navigate to its goal point when it faces new scenario on line. Concludes with the optimal rule base given and the simulation results showing its effectiveness.

关键词： GA fuzzy approach dynamic motion planning mobile robot optimal

Multi-agent coordination strategy estimation method based on control domain

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Journal of Harbin Institute of Technology(New Series) 2001年第3期8卷 249-252页

作者：曙光洪炳熔 dept. of comp. sci. and eng. Harbin Inst. of Technol. Harbin 150001 China

For estimation group comp.tition and multiagent coordination strategy, this paper introduces a notion based on multiagent group. According to the control domain, it analyzes the multiagent strategy during comp.tition in the macroscopic. It has been adopted in robot soccer and result enunciates that our method does not depend on comp.tition result. It can objectively quantitatively estimate coordination strategy.

关键词： multiagent coordination control domain color histogram