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检索条件"主题词=artificial immune algorithm"

共 158 条记录，以下是121-130 订阅

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An Application of Charging Management for Mobile Robot Transportation in Laboratory Environments

An Application of Charging Management for Mobile Robot Trans...

引用

IEEE International Instrumentation and Measurement Technology Conference (I2MTC)

作者： Liu, Hui Stoll, Norbert Junginger, Steffen Thurow, Kerstin Univ Rostock Inst Automat D-18055 Rostock Germany

ISBN: (纸本)9781467346214

In life science laboratories, mobile robots are adopted to do transportation tasks among distributed automated islands or rooms. To use those mobile robots effectively, a number of technology issues have to be considered, such as path planning of transportation and charging, localization, communication, etc. In this paper an application of charging management for mobile robot transportation is presented. In this application: (a) to localize the mobile robots accurately and fast in life science environments, a method using ceiling landmarks is adopted;(b) to measure the power status from all running robots, a power module for the server and client sides is designed;(c) to let mobile robots go charging automatically, an automated charging station is utilized;and (d) to select the best installing positions for the charging stations, an intelligent method based on the artificial immune algorithm (AIA) is proposed, which considers both of the distances among the expected working positions and their distribution of transportation tasks. A real case shows that the presented application is effective for mobile robot charging management in life science environments.

关键词： charging station laboratory transportation artificial immune algorithm life science engineering

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Identification and speed control of ultrasonic motors based on modified immune algorithm and Elman neural networks

Identification and speed control of ultrasonic motors based ...

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5th International Conference on Rough Sets and Current Trends in Computing

作者： Zhang, Qiao Xu, Xu Liang, Yanchun Jilin Univ Coll Comp Sci & Technol Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China Jilin Univ Coll Math Changchun 130012 Peoples R China

ISBN: (纸本)3540476938

An improved artificial immune algorithm with a dynamic threshold is presented in this paper. Numerical experiments show that compared with the genetic algorithm and the originally real-valued coding artificial immune algorithm, the improved algorithm possesses high speed of convergence and good performance of preventing the premature convergence. The proposed algorithm is employed to train the network structure, weights, initial inputs of the context units and self-feedback coefficient of the modified Elman network. A novel identifier and controller are constructed successively based on the proposed algorithm. A simulated dynamic system of the ultrasonic motor (USM) is considered as an example of a highly nonlinear system. The novel identifier and controller are applied to perform the speed identification and control of the ultrasonic motors. Numerical results show that both the identifier and controller based on the proposed algorithm possesses not only high convergent precision but also robustness to the external noise.

关键词： dynamic threshold artificial immune algorithm Elman network ultrasonic motor system identification control

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A New Approach to Solve the Mission Assignment Problem for Cooperative UCAVs Using immune Particle Swarm Optimizations

A New Approach to Solve the Mission Assignment Problem for C...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Wang, Guodong Li, Ming Deng, Zhidong Yang, Bo Yao, Wentao Aviat Ind Corp China Shenyang Aircraft Design & Res Inst Shenyang 110035 Peoples R China Tsinghua Univ Dept Comp Sci Tsinghua Natl Lab Informat Sci & Technol Beijing 100084 Peoples R China

ISBN: (纸本)9781467313988

This paper first builds a mathematical model for the mission assignment problem (MAP) of cooperative multiple uninhabited combat aerial vehicles (UCAVs). To address challenges posed by the specific MAP problem, we propose a new immune particle swarm optimization (NIPSO) approach through incorporating immunity memory, diversity clone, and immune selection in artificial immune algorithm into standard PSO. The simulation results achieved on a typical scenario show that our NIPSO approach for multiple UCAVs is capable of substantially speeding up convergence and has stronger ability to find the global optimum than that of classical PSO. The MAP solution for cooperative UCAVs is significantly improved.

关键词： Uninhabited Combat Aerial Vehicles (UCAV) mission assignment problem artificial immune algorithm Particle Swarm Optimization (PSO)

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Fault Diagnosis of Marine Diesel Engine by Means of immune-Rough Sets and RBF Neural Network

Fault Diagnosis of Marine Diesel Engine by Means of Immune-R...

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2nd International Conference on Information and Computing Science

作者： Zhang Xu Sun Jian-bo Dalian Jiaotong Univ Sch Mech Engn Dalian Peoples R China Dalian Maritime Univ Marine Engn Coll Dalian Peoples R China

ISBN: (纸本)9780769536347

A new hybrid intelligent model of rough sets and RBF neural networks for fault diagnosis is proposed. Meanwhile, a novel attribute reduction approach of rough set based on artificial immune algorithm is proposed, that can find several different minimal feature set of decision table through clonal selection, mutation and antibody suppressing strategy, then provide more selection for fault diagnosis. The diagnosis of large marine diesel engine showed that the model can reduce the cost of diagnosis and increase the efficiency of diagnosis. There will be well application prospect in practice.

关键词： rough set attribute reduction artificial immune algorithm RBF neural network fault diagnosis

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An implement approach for optimized variant design based on product gene

An implement approach for optimized variant design based on ...

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7th International Conference on Machine Learning and Cybernetics

作者： Zhao, Xiu-Yan Zhao, Ting-Ting Wei, Xiao-Peng Dalian Univ Technol Liaoning Key Lab Intelligent Informat Proc Dalian 116622 Peoples R China

ISBN: (纸本)9781424420957

Product optimization in product design is a very essential and time-consuming process especially at the variant design stage. A research project is introduced aiming to develop quickly a variant design system capable of competition and owning market shares. According to it, a new variant design idea, with a logical product structure model, is put forward based on product gene (PG). The product gene model (PGM) and its sequential gene manipulation are established, which described an optimization model of products. Adapting to the optimization model of products, an improved artificial immune algorithm (IAIA) is adopted based on basic artificial immune algotithm (BAIA). The numerical results demonstrate the high performance of the suggested methods for structural optimization with a certain constraints. It is found that the better results are obtained in variant design.

关键词： variant design product gene product optimization model artificial immune algorithm

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Application of Improved immune algorithm in Logistics Distribution Center Location 2

Application of Improved Immune Algorithm in Logistics Distri...

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2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)

作者： Ping, Huan Song, Chuyi Wang, Nan Jiang, Jingqing Inner Mongolia Univ Nationalities Coll Math Tong Liao 028000 Peoples R China

ISBN: (纸本)9781538620304

Logistics distribution center location problem is a hot topic nowadays. We choose a medium-sized city group to study in this paper. The improved artificial immune algorithm based on similarity vector distance selection is used for the logistics distribution center location problem. The algorithm uses the threshold value to restrict concentration calculation of two antibodies from two aspects which are the structure and the fitness. It can effectively improve the convergence speed and solve the problem.

关键词： logistics distribution center similarity vector distance artificial immune algorithm

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Towards a Multiobjective Framework for Evaluating Network Security under Exploit Attacks

Towards a Multiobjective Framework for Evaluating Network Se...

引用

IEEE International Conference on Communications (ICC)

作者： Dai, Fangfang Zheng, Kangfeng Luo, Shoushan Wu, Bin Beijing Univ Posts & Telecommun Informat Secur Ctr Beijing 100876 Peoples R China

ISBN: (纸本)9781467364324

Exploit attacks have been one of the major threats to computer network systems, the damage of which has been extensively studied and numerous countermeasures have been proposed to defend against them. In this work, we propose a multiobjective optimization framework to facilitate evaluation of network security under exploit attacks. Our approach explores a promising avenue of integrating attack graph methodology to evaluate network security. In particular, we innovatively utilize attack graph based security metrics to model exploit attacks and dynamically measure security risk under these attacks. Then a multiobjective problem is formulated to maximize network exploitability and security impact under feasible exploit compositions. Furthermore, an artificial immune algorithm is employed to solve the formulated problem. We conduct a series of simulation experiments on hypothetical network models to testify the performance of proposed mechanism. Simulation results show that our approach can innovatively solve the security evaluation problem under multiple decision variables with feasibility and effectiveness.

关键词： artificial immune algorithm attack graph exploit attack network security evaluation

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A game theory based intelligent QoS static traffic grooming scheme

A game theory based intelligent QoS static traffic grooming ...

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Conference on Network Architectures, Management, and Applications IV, Pts 1 & 2

作者： Wang, Xingwei Zhao, Zhijie An, Guangyong Huang, Min Northeastern Univ Coll Informat Sci & Engn Shenyang 110004 Peoples R China Korea Univ Sch Business Int Business Dept Seoul 130061 South Korea

ISBN: (纸本)081946449X

Supporting QoS (Quality of Service) and improving bandwidth utilization are necessary in IP/DWDM optical Internet. In this paper, with the introduction of game theory and layered graph, a static traffic grooming scheme is proposed based on artificial immune algorithm to minimize network resource occupancy and maximize comprehensive QoS satisfaction degree, achieving Nash equilibrium between network provider utility and user utility. Simulation results have shown that the proposed scheme is both feasible and effective.

关键词： IP/DWDM optical Internet traffic grooming QoS gaming artificial immune algorithm

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CPS Compliant Adaptive immune Based Load Frequency Control With Varying Wind Penetrations

CPS Compliant Adaptive Immune Based Load Frequency Control W...

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IEEE Power-and-Energy-Society Innovative Smart Grid Technologies Conference (ISGT)

作者： Rimal, Arjan N. Belkacemi, Rabie Tennessee Technol Univ Energy Syst Res Ctr Cookeville TN 38505 USA

ISBN: (纸本)9781509051670

As total inertia of a power system decreases with an increase in wind penetration, it cannot fully recover the frequency following a load perturbation. Control performance standards (CPS) deteriorate due to an increased variability in Area Control Error (ACE). Throughout a day, the operating conditions in a power system changes. As, the fixed gain controllers are only designed for nominal operating conditions, they cannot perform effectively over a long period of time. An adaptive immune based controller is designed in this paper for a two-area power system model which can comply with North American Reliability Council (NERC) CPS criteria and highly reduce the mechanical oscillations in the system. The immune response is compared with the high gain response, low gain response and the optimal gain response calculated through Genetic algorithm (GA) to prove its effectiveness in a system.

关键词： artificial immune algorithm Automatic generation control Control performance standards Frequency regulation Wind energy conversion

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Self-Organizing Polynomial Neural Network for Forecasting Chaotic Time Series: Comparison Results

Self-Organizing Polynomial Neural Network for Forecasting Ch...

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International Conference on Computer Science and Education (CSE 2011)

作者： Wu, Jui-Yu Lunghwa Univ Sci & Technol Dept Business Adm Tao Yuan Taiwan

ISBN: (纸本)9783642224171

While lacking previous knowledge, general users often have difficulty in using nonlinear statistical time series methods (e.g., bilinear model, threshold autoregressive model, smoothing transition autoregressive model, autoregressive conditional heteroscedastic model and generalized autoregressive conditional heteroscedastic model) and spectral analytical approaches. Moreover, standard back-propagation neural networks (BPNNs) using the steepest descent algorithm have the disadvantage that they converge to local optima. To overcome the above limitations, this work develops a self-organizing polynomial neural network (SOPNN) based on the group method of data handling (GMDH) algorithm, which is a statistical learning network. The proposed SOPNN scheme can create an optimal network topology by using an evolutionary process and is easily to be used. Performance of the proposed SOPNN scheme is also measured by using the Mackey-Glass chaotic time series problem. Additionally, numerical results of the proposed SOPNN scheme are compared with those of conventional BPNN, cerebellar model articulation controller NN (CMAC NN), advanced simulated annealing-based BPNN (ASA-BPNN) and artificial immune algorithm-based BPNN (AIA-BPNN). Experimental results indicate that the optimum training and test capabilities of the proposed SOPNN are superior to those of a conventional BPNN. Furthermore, the generalization capability and computational CPU time of the proposed SOPNN scheme are competitive for those of CMAC NN, AIA-BPNN and ASA-BPNN.

关键词： group method of data handling cerebellar model articulation controller back-propagation neural network artificial immune algorithm chaotic time series

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