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检索条件"主题词=Multi-Objective Genetic Algorithm"

共 724 条记录，以下是611-620 订阅

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Dynamic power minimization during combinational circuit testing as a traveling salesman problem

Dynamic power minimization during combinational circuit test...

引用

IEEE Congress on Evolutionary Computation

作者： Sokolov, A Sanyal, A Whitley, D Malaiya, Y Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

ISBN: (纸本)0780393635

Testing of VLSI circuits can cause generation of excessive heat which can damage the chips under test. In the random testing environment, high-performance CMOS circuits consume significant dynamic power during testing because of enhanced switching activity in the internal nodes. Our work focuses on the fact that power minimization is a Traveling Salesman Problem (TSP). We explore application of local search and genetic algorithms to test set reordering and perform a quantitative comparison to previously used deterministic techniques. We also consider reduction of the original test set as a dual-objective optimization problem, where switching activity and fault coverage are the two objective functions.

关键词： combinational circuit testing test vector automatic test pattern generator (ATPG) fault coverage traveling salesman problem (TSP) genetic algorithm application weight-biased edge crossover multi-objective genetic algorithm

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Schemes research and application of close-to-wheel drive system based on slider-crank mechanism 13

Schemes research and application of close-to-wheel drive sys...

引用

13th IEEE Vehicle Power and Propulsion Conference (VPPC)

作者： Li, Yan Zhu, Jianfei Gu, Cheng Chen, Xinbo Wang, Wei Wang, Yefeng Tongji Univ Sch Mech Engn Shanghai Peoples R China Tongji Univ Sch Automot Engn Shanghai Peoples R China

ISBN: (纸本)9781509035281

Normal in-wheel drive system with large unsprung mass has negative effects on the ride comfort and wheel ground adhesion. Therefore, three new kinds of close-to-wheel drive concepts were proposed: the motor suspended on car frame, the motor suspended on knuckle and two-stage suspension. Dynamic differential equation with the three concepts were deduced and their three degree-of-freedom(DOF) vibration models of 1/4 suspension were established in MATLAB software respectively. In order to analyze the three concepts' effects of ride comfort and handling stability compared with in-wheel drive system, the multi-objective genetic algorithms was applied to optimize the added stiffness and damping parameters of different concepts based on two objectives of Root-Mean-Square of body acceleration and wheel dynamic load.

关键词： Close-to-wheel drive two-stage suspension multi-objective genetic algorithm ride comfort handling stability

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Evolutionary feature selection for emotion recognition in multilingual speech analysis

Evolutionary feature selection for emotion recognition in mu...

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IEEE Congress on Evolutionary Computation (CEC)

作者： Brester, Christina Semenkin, Eugene Kovalev, Igor Zelenkov, Pavel Sidorov, Maxim Siberian State Aerosp Univ Inst Comp Sci & Telecommun Krasnoyarsk Russia Univ Ulm Inst Commun Engn Ulm Germany

ISBN: (纸本)9781479974924

In the case when conventional feature selection methods do not demonstrate sufficient performance, alternative algorithmic schemes might be applied. In this paper we propose an evolutionary feature selection technique based on the two-criteria optimization model. To diminish the drawbacks of genetic algorithms, which are used as optimizers, we design a parallel multi-criteria heuristic procedure based on an island model. The effectiveness of the proposed approach was investigated on the Speech-based Emotion Recognition Problem, which reflects one of the crucial aspects in the sphere of human-machine communications. A number of multilingual corpora (German, English and Japanese) were engaged in the experiments. According to the results obtained, a high level of emotion recognition was achieved (up to a 11.15% relative improvement compared with the best F-score value on the full set of attributes).

关键词： feature selection multi-objective genetic algorithm island model emotion recognition

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A Novel MOGA-based Method of Flight Control Law Design for a Helicopter and Its Application

A Novel MOGA-based Method of Flight Control Law Design for a...

引用

7th International Symposium on Instrumentation and Control Technology

作者： Xing, Xiaojun Yuan, Dongli Yan, Jianguo NW Polytech Univ Sch Automat Xian 710072 Peoples R China

ISBN: (纸本)9780819473622

In order to design full-envelop flight control law for a certain helicopter, a novel method based on multi-objective genetic algorithm (MOGA) is put forward. In this method, the design of flight control law is viewed as a multi-objective optimization problem(MOP) where obtaining optimal performances in each designed flight envelop are treated as sub-objective and that in all designed flight envelop as objective, flight control law's parameters to be searched as decision variables, corresponding performance criteria as constraints. For the MOP, MOGA is used to get the optimal parameters of flight control law in all designed flight envelops. Finally, the novel method is applied to the flight control law's design for the helicopter's pitch motion, the simulation results show that the parameters are feasible and the performances are satisfactory, which further prove that the method is effective.

关键词： multi-objective genetic algorithm Helicopter Flight control law

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multi-objective GA for Path Planning of Robot Manipulators Based on Dual Quaternion

Multi-Objective GA for Path Planning of Robot Manipulators B...

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5th IEEE Latin American Conference on Computational Intelligence (LA-CCI)

作者： Cea-Montufar, C. E. Merchan-Cruz, E. A. Ramirez-Gordillo, J. Vergara-Hernandez, E. Cerro-Ramirez, M. A. Inst Politecn Nacl Hidalgo Unidad Profes Interdisciplinaria Ingn Campus Hidalgo San Agustin Hgo Mexico Inst Politecn Nacl ESIME Unidad Azcapotzalco Secc Estudios Posgrad & Invest Mexico City DF Mexico

ISBN: (纸本)9781538646267

This paper presents a path planning strategy for robotic manipulators based on genetic algorithms and dual quaternions, designing a multi-objective function that allow trajectories be planned in an obstacle-free space and singularity-free kinematic restrictions for robotic manipulators as an optimization problem satisfying position and orientation conditions.

关键词： path planning dual quaternion multi-objective genetic algorithm robot manipulator

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Iris recognition based on zigzag collarette region and asymmetrical support vector machines

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4th International Conference on Image Analysis and Recognition

作者： Roy, Kaushik Bhattacharya, Prabir Concordia Univ Concordia Inst Informat Syst Engn Montreal PQ H3G 1M8 Canada

ISBN: (纸本)9783540742586

This paper presents an iris recognition technique based on the zigzag collarette region for segmentation and asymmetrical support vector machine to classify the iris pattern. The deterministic feature sequence extracted from the iris images using the 1D log-Gabor filters is applied to train the support vector machine (SVM). We use the multi-objective genetic algorithm (MOGA) to optimize the features and also to increase the overall recognition accuracy based on the matching performance of the tuned SVM. The traditional SVM is modified to an asymmetrical SVM to treat the cases of the False Accept and the False Reject differently and also to handle the unbalanced data of a specific class with respect to the other classes. The proposed technique is computationally effective with recognition rates of 97.70 % and 95.60% on the ICE (Iris Challenge Evaluation) and the WVU (West Virginia University) iris datasets respectively.

关键词： biometrics asymmetrical support vector machine multi-objective genetic algorithm zigzag collarette region

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Estimation of Dynamic Passenger Car Unit by multi objective Optimization Technique 8

Estimation of Dynamic Passenger Car Unit by Multi Objective ...

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8th IEEE International Conference on Cloud Computing, Data Science and Engineering (Confluence) / Global Technology, Innovation and Enterpreneurship Summit

作者： Biswas, Sabyasachi Singh, Somya Malik, Nihal Bisen, Atul, V Amity Univ Dept Civil Engn Amity Sch Engn & Technol Noida India

ISBN: (纸本)9781538617199

Capacity of an intersection is one of the most significant term to assess the efficiency of the urban road network. In order to bring a heterogeneous traffic stream into a homogeneous one consisting of passenger cars only, the concept of Passenger Car Unit (PCU) factor was introduced. From the past decades several methods were proposed by different researchers across the world to estimate the passenger car unit (PCU) in order to convert the heterogeneous traffic into homogeneous traffic. Among all the existing methods, headway ratio method was used frequently for estimating the PCU values at signalised intersections. Though, headway method have some limitation regarding the non-lane discipline behaviour under the highly mix traffic condition. Most of these proposed methods were found to be based on the homogeneous traffic condition. However, different vehicles categories were found to travel in the same traffic stream while in India, traffic condition is found to be highly heterogeneous in nature. Therefore, the proposed methods cannot be implemented directly under highly heterogamous traffic condition. Still, in India, researchers are using static PCU values which can biased the final outcomes of the study. PCU value can vary with the variation in the traffic conditions (i.e. roadway feature, vehicular characteristics and many more). Therefore, there is a need to use the dynamic passenger car unit (DPCU) instead of static one. Present study proposing a new technique for estimating DPCU at signalized intersections based on multi-objective genetic algorithm (MOGA) technique. One of the objective function of this method is to minimize the variance of the saturation flow. Additionally, second objective is to maximize the overall saturation flow in terns of PCU/h. Another aim of the study is to examine the effect of each vehicle types on the PCU value due to their different static and dynamic characteristics which ultimately affect the PCU value.

关键词： Signalized Intersection multi-objective genetic algorithm Optimization Headway

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ARTIFICIAL NEURAL NETWORK MODELS: DATA SELECTION AND ONLINE ADAPTATION

ARTIFICIAL NEURAL NETWORK MODELS: DATA SELECTION AND ONLINE ...

引用

作者： HAMID REZA KHOSRAVANI UNIVERSIDADE DO ALGARVE

学位级别：博士

Energy consumption has been increasing steadily due to globalization and industrialization. Studies have shown that buildings have the biggest proportion in energy consumption; for example in European Union countries, energy consumption in buildings represents around 40% of the total energy consumption. Hence this PhD was intended towards managing the energy consumed by Heating, Ventilating and Air Conditioning (HVAC) systems in buildings benefiting from Model Predictive Control (MPC) technique. To achieve this goal, artificial intelligence models such as neural networks and Support Vector Machines (SVM) have been proposed because of their high potential capabilities of performing accurate nonlinear mappings between inputs and outputs in real environments which are not noise-free. In this PhD, Radial Basis Function Neural Networks (RBFNN) as a promising class of Artificial Neural Networks (ANN) were considered to model a sequence of time series processes where the RBFNN models were built using multi objective genetic algorithm (MOGA) as a design platform. Regarding the design of such models, two main challenges were tackled; data selection and model adaptation. Since RBFNNs are data driven models, the performance of such models relies, to a good extent, on selecting proper data throughout the design phase, covering the whole input-output range in which they will be employed. The convex hull algorithms can be applied as methods for data selection; however the use of conventional implementations of these methods in high dimensions, due to their high complexity, is not feasible. As the first phase of this PhD, a new randomized approximation convex hull algorithm called ApproxHull was proposed for high dimensions so that it can be used in an acceptable execution time, and with low memory requirements. Simulation results showed that applying ApproxHull as a filter data selection method (i. e., unsupervised data selection method) could improve the performance of the class

关键词： Neural Networks multi-objective genetic algorithm Data Selection Online Adaptation

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A system-of-systems meta-architecting approach for seru production system design 15

A system-of-systems meta-architecting approach for seru prod...

引用

IEEE 15th International Conference of System of Systems Engineering (SoSE)

作者： Vanfossan, Samuel Dagli, Cihan H. Kwasa, Benjamin Missouri Univ Sci & Technol Engn Management & Syst Engn Rolla MO 65409 USA

ISBN: (纸本)9781728180502

Sponsored by expedient technologic innovation, consumers frequently expect manufacturer offerings to exhibit extensive product variety and regular product advancement. These expectations have rendered many traditional production practices less applicable. Chiefly impacted is the notion of mass-produced, low-variety artifacts via massive assembly lines. These operations have difficulty meeting the high-customization, short-lifecycle requirements imposed by contemporary demand. Many industries and organizations have begun the transformation from these rigid assembly mechanisms to a more versatile, cellular production strategy known as seru production. To facilitate this transition, methods are needed to aid manufacturers in appropriately selecting and arranging seru system components, a critical step in seru system design. Herein, a generalized model is proposed utilizing a system-of-systems architecting approach to determine the component assembly best suiting the needs of the manufacturing entity. Candidate architectures are generated and evaluated using a multi-objective genetic algorithm from which a preferred alternative is selected through a fuzzy inference system. Directing this genetic algorithm, domain-independent objectives are presented, maintaining applications to most seru production design scenarios. The proposed method is then applied to a camera production example, culminating in the identification of a well-performing architecture. The presented method should find increased use as organizations further adopt this flexible production methodology.

关键词： Seru production system meta-architecture generation multi-objective genetic algorithm fuzzy inference system system-of-systems architecting

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MOEA-Based Fuzzy Control for Seismically Excited Structures

MOEA-Based Fuzzy Control for Seismically Excited Structures

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4th International Symposium on Intelligence Computation and Applications

作者： Ning, Xiang-liang Tan, Ping Zhou, Fu-lin Harbin Inst Technol Shenzhen Grad Sch Shenzhen 518055 Peoples R China Guangdong Key Lab Earthquake Engn & Appl Tech Guangzhou 510405 Guangdong Peoples R China

ISBN: (纸本)9783642049613

To guarantee the safety and functionality of structures simultaneously at different levels of seismic loadings, this paper proposes a multi-objective switching fuzzy control (MOSFC) strategy. MOSFC functions as a trigger with two control states considered. When the structure is at the state of linear, the main objection of control is the peak acceleration. On the other hand, once the nonlinear appears, the control of peak inter-storey drift is the main objection. multi-objective genetic algorithm, NSGA-II, is employed for optimizing the fuzzy control rules. A scaled model of a six-storey building with two MR dampers installed at the two bottom floors is simulated here. Linear and Nonlinear numerical simulations demonstrate the effectiveness and robustness.

关键词： multi-objective genetic algorithm fuzzy control robustness

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