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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

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Analysing Fuzzy Based Approach for Extractive Text Summarization

Analysing Fuzzy Based Approach for Extractive Text Summariza...

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Intelligent Computing and control systems (ICCS), international conference on

作者： Aakanksha Sharaff Amit Siddharth Khaire Dimple Sharma National Institute of Technology Raipur Raipur India

ISBN: (数字)9781538681138

ISBN: (纸本)9781538681145

In today's era of information, there is gigantic amount of data available from various sources. Not only does the enormous volumes pose problems, searching of required information becomes a very difficult task. It is the need of the hour to have smaller but significant representation of large, bulky pieces of information in order to obtain the desired details. Text summarization is the process of condensing text documents into shorter and accurate representation conveying the meaning of the text precisely. It has found applications in numerous fields. In this paper, a process for extractive text summarization using fuzzy logic has been discussed meticulously. It takes various properties into account for identifying the most significant sentences for the formation of summary from a given text. The model proposed in this paper has been tested on BBC News Summary dataset and the results have been compared using the ROUGE measures. The obtained results indicate that the proposed model shows enhanced performance with improved f-measure values.

关键词： Fuzzy logic Feature extraction Indexing Mathematical model conferences control systems Computational modeling

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A modeling Method for Command and control Supemetworks Based on Hyperedge Generation Strategies 22

A Modeling Method for Command and Control Supemetworks Based...

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22nd IEEE international conference on Computer Supported Cooperative Work in Design, CSCWD 2018

作者： Gao, Xiue Yu, Haoyang Wang, Yunming Chen, Bo Information and Engineering College Dalian University Computer Science and Technology College Dalian University of Technology Dalian China Communication and Network Laboratory Dalian University Dalian China

ISBN: (纸本)9781538614822

In the current command and control (C2) supernetwork model it is difficult to quantify and describe the complex relationships in C2 networks accurately. This paper presents a new modeling method for C2 supernetworks based on hypergraph theory. Firstly, a C2 supernetwork model with three layers and five networks is built. Secondly, the generation strategies for five types of hyperedges are given. Finally, we verify the feasibility and effectiveness of both the model and the method using a simulation of an air defense C2 network. The simulation results confirm that the model can reflect the complex relationships and characteristics present in a C2 network. © 2018 IEEE.

关键词： complex networks

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problems in models of opening networks resources and methods for calculating system performance and reliability 18

Problems in models of opening networks resources and methods...

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18th international conference on control, Automation and systems, ICCAS 2018

作者： Gulnara, Bektemyssova Ahmad, Abdul Rahim Bin Ismail, Roslan Computer Engineering and Telecommunications International Information Technologies University Almaty050040 Kazakhstan Department of Systems and Networking Universiti Tenaga Nasional Selangor43000 Malaysia

ISBN: (纸本)9788993215151

The purpose of this paper is to identify a problem in Grid resource discovery models that affect the overall performance of grid computing. Since, Grid resources are scattered in different geographical locations on heterogeneous platforms and within various administrative policies. Finding resources in grid computing is an actual and complex task. The paper identifies some problems in the Grid resource discovery models. In addition, deals with the application of the mathematical apparatus to calculate the reliability and performance of GRID systems and application of a permanent matrix for calculating the reliability of distributed computing systems based on GRID. © ICROS.

关键词： Grid computing

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Theory and simulation of a neuro-fuzzy controller for 20MW turbo generator control 7

Theory and simulation of a neuro-fuzzy controller for 20MW t...

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7th international conference on Renewable Energy Research and Applications (ICRERA)

作者： Kebe, Babacar Thiaw, Lamine Ba, Oumar Univ Cheikh Anta Diop Dakar Ecole Super Polytech Dakar Dakar Senegal

ISBN: (纸本)9781538659823

This document focuses on the development of a learning tools for the dynamic model of a steam turbine 20MW capacity type able to accommodate the different variations of the machine's operating parameters. Considering all the advantages and disadvantages of the optimization methods that we have studied (genetic algorithm and neural networks), the neuro-fuzzy option was remarkable in view of the results obtained in the modeling of the systems. The ANFIS model (Adaptive Neuro-Fuzzy Inference System), known for its performance in the learning domain of complex non-linear systems, is chosen for a better approximation of functions fir modeling. The active power depending of the high pressure steam flow inlet turbine and the low pressure steam flow extraction as well as the voltage across the generator depending of the power factor and the active power shall be controlled from 2 ANFIS models mounted in parallel, their outputs acting respectively on the control of the HP (High Pressure) steam inlet valve opening for the variation of the HP steam flow inlet and the rotor excitation current for the variation of the voltage across the alternator. The dynamic model thus obtained from the adjustment of the parameters of the membership functions describes the behavior of the turbine to stabilize its operating point in the face of any disturbance.

关键词： Neuro-fuzzy networks generator learning linguistic value ANFIS membership function fuzzy logic

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Surrogate-Assisted Particle Swarm Optimization using Space Reduction and Global Search

Surrogate-Assisted Particle Swarm Optimization using Space R...

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international conference on High Performance Computing & Simulation (HPCS)

作者： Peng Zhang Shuyou Zhang Guodong Yi Lemiao Qiu State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China

ISBN: (数字)9781728144849

ISBN: (纸本)9781728144856

Evolutionary algorithms (EAs) are powerful tools for solving complex engineering applications problems, however, the function evaluations of the real-world problems are often time-consuming, which hinders the application of EAs to solve these problems. To address this challenge, surrogate-assisted EAs (SAEAs) have been widely studied over the past decades. Model management can help obtain solutions under limited computational budget to accelerate the convergence of the optimization process. In this paper, we propose a SAEA based on social learning particle swarm optimization (SL-PSO), a space reduction strategy and a global model search strategy are developed to search for the best and most uncertain solutions. In the proposed algorithm, the space reduction strategy is used to search for the optimal solution based on the surrogates and the global model search strategy is used to search for the most uncertain solution. The evolutionary search using the space strategy switches to the global search once on further improvement can be observed, and vice versa. Experimental results comparing the proposed algorithm with other two algorithms on several benchmark problems that the proposed algorithm is able to achieve better or competitive solutions.

关键词： Search problems Computational modeling Particle swarm optimization Optimization Sociology Statistics Fluids

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Optimal control of automotive multivariable dynamical systems 1

引用

14th international conference on Dynamical systems: Theory and Applications, DSTA 2017

作者： Jackiewicz, Jacek Faculty of Mathematics Physics & Technical Sciences Kazimierz Wielki University Chodkiewicza 30 Bydgoszcz85-064 Poland

ISBN: (数字)9783319965987

ISBN: (纸本)9783319965970

Two distinctive features of challenging control engineering problems are commonly taken into consideration in design of dynamical, mechatronics systems, namely operation ranges, of such systems with nonlinear effects, which are not always near to equilibrium states, as well as a fairly high level of uncertainties of their physical description with which controllers have to cope despite a lack of knowledge on the all system parameters although physical modeling allows to identify their particular nonlinear effects. It should be noted that usage of nonlinear physical modeling in real-time control systems can be computationally very demanding. Hence, it seems to be suitable to use robust control methods based on linearized models with adaptive updating algorithms. However, usually strong nonlinearities can reduce the effectiveness of control methods, and thus of adaptive control algorithms. The controller gains can be often updated by using the estimated parameters. In this contribution the adaptive control systems for automotive applications, which are based on indirect (or self-tuning) controller strategies are discussed. The modeling issue of indirect optimal controller strategies is illustrated by the application example. © Springer international Publishing AG, part of Springer Nature 2018.

关键词： Adaptive control systems

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Reinforcement Learning with Explainability for Traffic Signal control

Reinforcement Learning with Explainability for Traffic Signa...

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international conference on Intelligent Transportation

作者： Stefano Giovanni Rizzo Giovanna Vantini Sanjay Chawla Qatar Computing Research Institute (QCRI) Doha Qatar

ISBN: (纸本)9781538670255

Deep reinforcement learning has recently provided promising results on the traffic light control optimization problem, by training neural network agents to select the traffic light phase. These agents learn complex models by optimizing a simple objective, such as the average traffic speed, but are considered opaque when it comes to explaining their decisions. Nevertheless, explanations are required in transferring this technology in the real world, especially in complex scenarios with nontrivial phases, such as in the case of signalized roundabouts with entry and circulatory traffic lights. In this paper, after training a Policy Gradient agent on a signalized roundabout with 11 phases and real traffic data, we analyze the relation between the agent phase preferences and the actual traffic, and we assess the agent capability of reacting to the current detectors state. Then, we estimate the effect of the road detectors state on the agent selected phases, through the SHAP model-agnostic technique, using Shapley values recovered from a linear explanation model. The results show that it is possible to extract meaningful explanations on the decision taken by a complex policy, in relation to both the traffic volumes and the lanes occupancy.

关键词： Detectors Learning (artificial intelligence) Machine learning Optimization Neural networks Training Computational modeling

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Dynamics and control of adaptive airbags for UAV impact protection

Dynamics and control of adaptive airbags for UAV impact prot...

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international conference on Noise and Vibration Engineering (ISMA) / international conference on Uncertainty in Structural Dynamics (USD)

作者： Wolejsza, Z. Holnicki-Szulc, J. Graczykowski, C. Hinc, K. Faraj, R. Kowalski, T. Mikulowski, G. Kazmierczak, K. Wiszowaty, R. Pawlowski, P. Polish Acad Sci Dept Intelligent Technol Inst Fundamental Technol Res Ul A Pawinskiego 5b PL-02106 Warsaw Poland Adaptronica Sp Zoo Ul Szpitalna 32 PL-05092 Lomianki Poland

ISBN: (纸本)9789073802995

Small drones with total mass of a few kilograms are becoming more and more popular in many applications increasing the probability of occurrence of emergency situations caused by an equipment failure or a human error. In case of a fall from a high altitude very often it is possible to use parachute rescue systems, which however require relatively long time for deployment and development of braking forces. The touchdown velocity may be large enough to exceed limit accelerations for UAV equipment. The paper presents the concept of deployable airbag systems, in particular with adaptive flow control, which provides a possible solution to the above-mentioned problems. The paper discusses the overall control and adaptation strategy. Simplified methods for mathematical modeling are proposed and formulated for an example on a cylindrical airbag. The conceptual part is concluded with the presentation of the methodology of experimental verification and results of initial tests of the integrated airbag system.

关键词： Adaptive control systems

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Closed-loop Optimal control of Tethered Robot during Nonplanar Orbital Transfer 8

Closed-loop Optimal Control of Tethered Robot during Nonplan...

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8th IEEE Annual international conference on Cyber Technology in Automation, control, and Intelligent systems (IEEE-CYBER)

作者： Sun, Liang Chen, Ming Zhao, Guowei Xu, Wei Beihang Univ Beijing 100191 Peoples R China

ISBN: (纸本)9781538670576

Typical Tethered Space Robot (TSR) composed of main satellite, operation robot and joined tether has an important prospect in active debris capture and removal applications. Targeting the safe, stable and economical nonplanar orbital transfer mission, the dynamic modeling and tracking control algorithm problems during the towing process have been studied in this paper, providing a theoretical basis for the tether towing deorbit technical verification and engineering. On the basis of optimal feedback control theory, the control problem during nonplanar orbital transfer mission of TSR is studied. For eliminating the effect of mismatch of system model and external disturbance, an optimal feedback controller in closed-loop form is proposed. The established optimal feedback controller is essentially composed of multiple computations by an open-loop optimal controller. Based on the state feedback matrix collected at the sampling interval, taking advantage of fast convergence speed and high precision characteristics inherited from Gauss-Pseudospectral method, the finite horizon open-loop optimal control problem at each sampling interval is discretized and solved. And the first part of each control sequence generated by the controller is imposed on the controlled model. Finally, the effectiveness of the proposed scheme is demonstrated via numerical case studies.

关键词： component Tethered Space Robot Closed-loop Optimal control Gauss-Pseudospectral Method Nonplanar Orbital Transfer

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Solution of Kinematics Problem of 5-DOF Manipulator Emitter for Non-Destructive Defectoscopy

Solution of Kinematics Problem of 5-DOF Manipulator Emitter ...

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international conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Murzakaev, Rustam T. Poliakov, Anatoliy N. Artemev, Vadim V. Perm Natl Res Polytech Univ Dept Informat Technol & Automated Syst Perm Russia

ISBN: (纸本)9781538643075

This article describes the positioning system of defectoscopic equipment for non-destructive examination of complex shaped parts made of polymer composite materials. The purpose of the system and features of the investigated objects are described. The rationale for the development of the system and the range of problems it solves are presented. The solution of the kinematics problem for a 5-DOF manipulator is considered. The original algorithms for solving the kinematics problem are demonstrated. Methods for resolving collisions for a manipulator system are described. The results obtained in the course of experiments and studies are presented. The study was supported by the RSF grant 16-19-00155 "The robotic system of multi-angle microfocus radiography for aircraft parts and assemblies made of polymer composite materials with complex impact."

关键词： Inverse kinematics modeling and control 5-DOF manipulator non-destructive defectoscopy

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