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检索条件"主题词=evolutionary computation"

共 14926 条记录，以下是4891-4900 订阅

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Multi-species Generation Strategy-Based Vegetation Evolution

Multi-species Generation Strategy-Based Vegetation Evolution

引用

IEEE Congress on evolutionary computation (CEC) as part of the IEEE World Congress on computational Intelligence (IEEE WCCI)

作者： Yu, Jun Takagi, Hideyuki Niigata Univ Inst Sci & Technol Niigata Japan Kyushu Univ Fac Design Fukuoka Japan

ISBN: (纸本)9781728169293

We propose a multi-species generation strategy to increase the diversity of seed individuals produced in the maturity operation of vegetation evolution (VEGE). Since the breeding patterns of real plants can be roughly divided into sexual reproduction and asexual one, the proposed strategy additionally introduces two different methods to simulate these two patterns. As our preliminary attempt of the simulation, a mature individual is splattered randomly in the neighbor local area of its parent individual with Gaussian distribution probability to simulate asexual reproduction, while a mature individual is generated by crossing randomly selected two different parent individuals to simulate sexual reproduction. Our proposed strategy consists of these two new reproduction methods and that of our original VEGE, and each mature individual in every generation randomly selects one of these three methods to generate seed individuals, which is analogous to different plant species using different mechanisms to breed. To evaluate the performance of our proposed strategy, we compare VEGE and (VEGE + the proposed generation strategy) on 28 benchmark functions of three different dimensions from the CEC 2013 test suit with 30 independent trial runs. The experimental results have confirmed that the proposed strategy can increase the diversity of seed individuals, accelerate the convergence of VEGE significantly, and become effective according to the increase of dimensions.

关键词： evolutionary computation Vegetation Evolution Multi-species Generation Strategy Optimization

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A Fundamental Study on Coded Aperture Design for Depth from Projector Defocus based on evolutionary Multi-Objective Optimization 7

A Fundamental Study on Coded Aperture Design for Depth from ...

引用

International Conference on Intelligent Networking and Collaborative Systems (INCoS)

作者： Mido, Yudai Horita, Yuki Nakai, Kentaro Megano, Taishi Ono, Satoshi Kawasaki, Hiroshi Kagoshima Univ Grad Sch Sci & Engn Dept Informat Sci & Biomed Engn Kagoshima Japan

ISBN: (纸本)9781467376952

It is a reasonable idea to solve a problem whose property has not been clarified yet using evolutionary multi-objective optimization (EMO) because EMO does not require domain specific knowledge and analysis for obtained pareto solution set may reveal relationships between design variables and objective functions. This paper focuses on designing a coded aperture (CA), one of the hot topics in computer photography;CA is used in a camera or a projector for deblurring, constructing all-focus image, depth estimation and so on. Since little knowledge has been accumulated for designing CA, this paper proposes a CA design method using EMO. Experiments on designing projector aperture have shown relationships between the performance of depth estimation, aperture ratio, and noise robustness.

关键词： evolutionary computation coded aperture depth from defocus multi-objective optimization

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EXIT-Based evolutionary Optimization of Continuous Phase Modulation Waveforms

EXIT-Based Evolutionary Optimization of Continuous Phase Mod...

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International Symposium on Wireless Communication Systems (ISWCS)

作者： Dantona, V. Lankl, B. Munich Univ Bundeswehr Inst Commun Engn Neubiberg Germany

ISBN: (纸本)9781538629130

The joint optimization of partial response continuous phase modulation (CPM) parameters is addressed. For fixed modulation order and memory length, the modulation index, the symbol rate and the phase pulse shape are considered as degrees of freedom. In particular, we drop the restriction of "classical" phase pulses and we allow for custom shapes, which are parametrized through Bezier curves. In order to deal with the many variables involved, an evolutionary algorithm is employed for numerical optimization. The optimization metric is related to the extrinsic information transfer (EXIT), under the assumption that CPM is serially concatenated with an outer convolutional encoder, as it is the case for several practical systems. The presence of high adjacent channel interference (ACI) is explicitly accounted for in the optimization process. We show that the proposed optimization strategy can effectively exploit the power-bandwidth trade-off. Nevertheless, only moderate improvements are achievable in comparison to state-of-the-art serially concatenated systems.

关键词： Optimization evolutionary computation Receivers Demodulation Decoding Phase modulation

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The performance of polyploid evolutionary algorithms is improved both by having many chromosomes and by having many copies of each chromosome on symbolic regression problems

The performance of polyploid evolutionary algorithms is impr...

引用

IEEE Congress on evolutionary computation

作者： Cavill, R Smith, S Tyrrell, A Univ York Dept Elect York YO10 5DD N Yorkshire England

ISBN: (纸本)0780393635

This paper presents important new findings for a new method for evolving individual programs with multiple chromosomes. Previous results have shown that evolving individuals with multiple chromosomes produced improved results over evolving individuals with a single chromosome. The multiple chromosomes are organised along two axes;there are a number of different chromosomes and a number of copies of each chromosome. This paper investigates the effects which these two axes have on the performance of the algorithm;whether the improvement in performance comes from just one of these features or whether it is a combination of them both.

关键词： biology cellular biophysics evolutionary computation regression analysis multiple chromosomes polyploid evolutionary algorithm symbolic regression problem

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Short-term Electric Load Forecasting Using computational Intelligence Methods

Short-term Electric Load Forecasting Using Computational Int...

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IEEE International Conference on Fuzzy Systems (FUZZ)

作者： Jurado, Sergio Peralta, Juan Nebot, Angela Mugica, Francisco Cortez, Paulo Sensing & Control Syst Arago 208-210 Barcelona 08011 Spain Univ Autonoma Barcelona E-08193 Bellaterra Spain Tech Univ Catalonia E-08034 Barcelona Spain Univ Minho Cent Algoritmi Guimaraes Portugal

ISBN: (纸本)9781479900206

Accurate time series forecasting is a key issue to support individual and organizational decision making. In this paper, we introduce several methods for short-term electric load forecasting. All the presented methods stem from computational intelligence techniques: Random Forest, Nonlinear Autoregressive Neural Networks, evolutionary Support Vector Machines and Fuzzy Inductive Reasoning. The performance of the suggested methods is experimentally justified with several experiments carried out, using a set of three time series from electricity consumption in the real-world domain, on different forecasting horizons.

关键词： Artificial Neural Networks evolutionary computation Support Vector Machines Random Forest Time Series Forecast

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On the Effect of Population Size and Selection Mechanism from the Viewpoint of Collaboration between Exploration and Exploitation

On the Effect of Population Size and Selection Mechanism fro...

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IEEE 2nd Workshop on Memetic Computing (MC)

作者： Lin, Jih-Yiing Chen, Ying-ping Natl Chiao Tung Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9781467358910

The synergy between exploration and exploitation has been a prominent issue in optimization. Optimization algorithms are generally required to have their parameters tuned to achieve successful exploration-exploitation synergies. Nonetheless, while many algorithms have achieved remarkable success in a wide range of applications, the key to successful exploration-exploitation synergies still remains obscure because conclusions drawn from empirical results or theoretical derivations are usually algorithm specific and/or problem dependent. In our previous studies, a theoretical model based on the concept of local search zones was proposed to provide an alternative perspective depicting the synergy between global search and local search in memetic algorithms. In the present work, we adopt the concept of local search zones to interpret and discuss the effect of population size and selection mechanism, two common design concerns in evolutionary algorithms, on the synergy between exploration and exploitation. In addition to providing interpretations to the effect of population size and selection mechanism on different problem types, this investigation also suggests that with proper mapping, the concept of local search zones is also applicable to delineate the behavior of optimization algorithms with different mechanisms.

关键词： Population size selection mechanism discrete Lipschitz class quasi-basin class global search local search evolutionary computation

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EFFECTIVE ALLELE PRESERVATION BY OFFSPRING SELECTION: AN EMPIRICAL STUDY FOR THE TSP

EFFECTIVE ALLELE PRESERVATION BY OFFSPRING SELECTION: AN EMP...

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20th European Modeling and Simulation Symposium

作者： Affenzeller, Michael Wagner, Stefan Winkler, Stephan Upper Austrian Univ Appl Sci Sch Informat Commun & Media Heurist & Evolutionary Algorithms Lab A-4232 Hagenberg Austria

ISBN: (纸本)9788890372407

The basic selection ideas of the different representatives of evolutionary algorithms are sometimes quite diverse. The selection concept of genetic algorithms (GAs) and genetic programming (GP) is basically realized by the selection of above-average parents for reproduction whereas evolution strategies (ES) use the fitness of newly evolved offspring as the basis for selection (survival of the fittest due to birth surplus). This contribution considers aspects of population genetics and Evolution Strategies in order to propose an enhanced and generic selection model for Genetic Algorithms which is able to preserve the alleles which are part of a high quality solution. Some selected aspects of these enhanced techniques are discussed exemplarily on the basis of travelling salesman benchmark (TSP) benchmark problem instances.

关键词： softcomputing evolutionary computation selection self adaptation

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Distributed Learning Strategies for Interference Mitigation in Femtocell Networks

Distributed Learning Strategies for Interference Mitigation ...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Bennis, M. Guruacharya, S. Niyato, D. Univ Oulu Ctr Wireless Commun Oulu Finland Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore

ISBN: (纸本)9781424492688

In this paper, the strategic coexistence between macro and femtocell tiers is studied using tools from evolutionary game theory and reinforcement learning. In the first case, femto base stations (FBSs) exchange information through a central controller, and adapt their strategies based on their instantaneous payoffs and average payoffs of the femtocell population. A fictitious play formulation is also examined where FBSs maximize their payoffs given the empirical frequency of other femtocells' actions. In the second case, when information exchange among femtocells is no longer possible, each femtocell gradually learns by interacting with its local environment through trials-and-errors, and adapt its strategies. Variant of the evolutionary game approach (referred to as replication by imitation) is also investigated where femtocells probabilistically review their strategies and imitate other femtocells in the network. Finally, the overall performance of the network in terms of spectral efficiency and convergence is shown to be adamantly driven by the type of information available at femtocells.

关键词： FBS Femtocell networks Games Heuristic algorithms Interference Macrocell networks Signal to noise ratio Vectors central controller distributed learning strategies evolutionary computation evolutionary game theory femtobase stations femtocell networks femtocell population femtocell tiers femtocellular radio game theory interference mitigation interference suppression learning (artificial intelligence) telecommunication computing

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Glitch It If You Can: Parameter Search Strategies for Successful Fault Injection 1

引用

12th International Conference on Smart Card Research and Advanced Application (CARDIS)

作者： Carpi, Rafael Boix Picek, Stjepan Batina, Lejla Menarini, Federico Jakobovic, Domagoj Golub, Marin Riscure BV Delft Netherlands Radboud Univ Nijmegen NL-6525 ED Nijmegen Netherlands Fac Elect Engn & Comp Zagreb Croatia

ISBN: (数字)9783319083025

ISBN: (纸本)9783319083025;9783319083018

Fault analysis poses a serious threat to embedded security devices, especially smart cards. In particular, modeling faults and finding effective practical approaches that are also generic is considered to be of interest for smart card industry. In this work we propose a novel methodology to deal with a difficult question of choosing multiple parameters required for effective faults. To this aim, we investigate several algorithms and find a new promising direction using evolutionary computation. Our experimental results on some of the smart cards used today show the potential of this new approach. Our best algorithm is a tailored search strategy especially developed for the purpose of finding the best choice of parameters for glitching. With this approach we found some of off-the-shelf devices, although secured against this type of attacks, still vulnerable.

关键词： Fault analysis Glitches Smart cards Self-adaptive algorithms evolutionary computation

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Evaluation of Communities from Exploratory evolutionary Compression of Weighted Graphs

Evaluation of Communities from Exploratory Evolutionary Comp...

引用

IEEE Congress on evolutionary computation (IEEE CEC)

作者： Rutkowski, Emilia Sargant, James Houghten, Sheridan Brown, Joseph Alexander Brock Univ Dept Comp Sci St Catharines ON Canada Innopolis Univ AI Games Dev Lab Innopolis Russia

ISBN: (纸本)9781728183923

Contact networks are used as a representation for the modeling of illness transmission. In this study, we represent not only the links of the transmissions but also utilize a weighted graph to represent the probability of transfer. These graphs can be large and complex when taking into account the number of contacts used in tracing. Compression of the graph allows for the development of community detection as well as providing a simpler graph. By examining the contact networks developed by an evolutionary algorithm for compression, it is discovered that the choice of fitness function and the appropriate weighting of edges leads to a different compressed graph, finding different connected communities;this is also true when compared to the communities identified by the Louvain community detection algorithm. This demonstrates the importance of considering weighting in contact networks, and suggests that in the future an understanding of the community structure should be utilized by public health officials.

关键词： Image edge detection evolutionary computation Public healthcare Detection algorithms

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