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检索条件"主题词=Cartesian Genetic Programming"

共 248 条记录，以下是31-40 订阅

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Two New Mutation Techniques for cartesian genetic programming 11th

Two New Mutation Techniques for Cartesian Genetic Programmin...

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11th International Joint Conference on Computational Intelligence (IJCCI)

作者： Kalkreuth, Roman TU Dortmund Univ Dept Comp Sci Otto Hahn Str 14 Dortmund Germany

ISBN: (纸本)9789897583841

cartesian genetic programming is often used with a point mutation as the sole genetic operator. In this paper, we propose two phenotypic mutation techniques and take a step towards advanced phenotypic mutations in cartesian genetic programming The functionality of the proposed mutations is inspired by biological evolution which mutates DNA sequences by inserting and deleting nucleotides. Experiments with boolean functions problem show a better search performance when the proposed mutations are used. The results of our experiments indicate that the proposed mutations are beneficial for the use of cartesian genetic programming.

关键词： cartesian genetic programming Mutation Phenotype

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Approximation of Digital Circuits Using cartesian genetic programming

Approximation of Digital Circuits Using Cartesian Genetic Pr...

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International Conference on Communication and Electronics Systems (ICCES)

作者： Babu, Kagana Sarath Balaji, N. Univ Coll Engn Vizianagaram Dept ECE Vizianagaram India

ISBN: (纸本)9781509010660

Digital circuits can be approximated in which the exact functionality can be relaxed. Approximate circuits are constructed such that the logic given by the user is not implemented completely and hence their functionality can be traded for area, delay and power consumption. An evolutionary approach like cartesian genetic programming (CGP) is used in this paper to make automatic design process of digital circuits. The quality of approximate circuits can be improved along with the reduction of evolution time by using a heuristic population seeding method which is embedded into CGP. In particular, digital circuits like full adder, 2 bit multiplier and 2 bit adder are addressed in this paper. Experimental results are given where random seeding mechanism is compared with heuristic seeding methods.

关键词： Approximate circuits cartesian genetic programming Digital circuits Evolutionary approach Heuristic population Seeding

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C³PO: Cipher Construction with cartesian genetic programming 19

C<SUP>3</SUP>PO: Cipher Construction with Cartesian genetic ...

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genetic and Evolutionary Computation Conference (GECCO)

作者： Picek, Stjepan Knezevic, Karlo Jakobovic, Domagoj Derek, Ante Delft Univ Technol Delft Netherlands Univ Zagreb Fac Elect Engn & Comp Zagreb Croatia

ISBN: (纸本)9781450367486

In this paper, we ask a question whether evolutionary algorithms can evolve cryptographic algorithms when no precise design criteria are given. Our strategy utilizes cartesian genetic programming in the bi-level optimization setting with multiple populations trying to evolve a cryptographic algorithm and break it. To challenge our design paradigm, we consider a number of scenarios with varying criteria on the system and its security. We are able to obtain interesting results in several scenarios where the attacker is not able to understand the text with more than a random chance. Interestingly, our system is able to develop various versions of one-time pads, which are the only systems that ensure perfect secrecy. Although our system is far from practical, we consider it interesting since it gives good results that are also human-readable.

关键词： Cryptography cartesian genetic programming Block ciphers Bi-level optimization

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Designing Combinational Circuits Using a Multi-objective cartesian genetic programming with Adaptive Population Size 5th

Designing Combinational Circuits Using a Multi-objective Car...

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5th International Conference on Machine Learning, Optimization, and Data Science (LOD)

作者： Lima, Leandro S. Bernardino, Heder S. Barbosa, Helio J. C. Univ Fed Juiz de Fora UFJF Juiz De Fora MG Brazil Lab Nacl Comp Cient LNCC Petropolis RJ Brazil

ISBN: (纸本)9783030375997;9783030375980

This paper proposes a multiobjective cartesian genetic programming with an adaptive population size to design approximate digital circuits via evolutionary algorithms, analyzing the trade-off between the most often used objectives: error, area, power dissipation, and delay. Combinational digital circuits such as adders, multipliers, and arithmetic logic units (ALUs) with up to 16 inputs and 370 logic gates are considered in the computational experiments. The proposed method was able to produce approximate circuits with good operational characteristics when compared with other methods from the literature.

关键词： Combinational circuits Multi-objective optimization cartesian genetic programming

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Evolution of Neural Networks using cartesian genetic programming

Evolution of Neural Networks using Cartesian Genetic Program...

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2010 IEEE World Congress on Computational Intelligence

作者： Khan, Maryam Mahsal Khan, Gul Muhammad Miller, Julian F. NWFP Univ Engn & Technol Dept Comp Syst Engn Peshawar Pakistan NWFP Univ Engn & Technol Dept Elect Engn Peshawar Pakistan Univ York Dept ELEC Intelligent Syst Grp York N Yorkshire England

ISBN: (纸本)9781424481262

A novel Neuroevolutionary technique based on cartesian genetic programming is proposed (CGPANN). ANNs are encoded and evolved using a representation adapted from the CGP. We have tested the new approach on the single pole balancing problem. Results show that CGPANN evolves solutions faster and of higher quality than the most powerful algorithms of Neuroevolution in the literature.

关键词： cartesian genetic programming genetic algorithms neural nets neural network evolution neuroevolutionary technique single pole balancing problem

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Adaptive Sampling of Biomedical Images with cartesian genetic programming 18th

Adaptive Sampling of Biomedical Images with Cartesian Geneti...

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18th International Conference on Parallel Problem Solving from Nature (PPSN)

作者： Lavinas, Yuri Haut, Nathan Punch, William Banzhaf, Wolfgang Cussat-Blanc, Sylvain Univ Toulouse IRIT CNRS UMR5505 Toulouse France Michigan State Univ E Lansing MI 48824 USA

ISBN: (纸本)9783031700545;9783031700552

In this contribution we study how to effectively evolve programs tailored for biomedical image segmentation by using an Active Learning approach in cartesian genetic programming (CGP). Active Learning allows to dynamically select training data by identifying the most informative next image to add to the training set. We study how different metrics for selecting images under active learning impact the searchability of CGP. Our results show that datasets built during evolution with active learning improve the performance of cartesian GP substantially. In addition, we found that the choice of the particular metric used for selecting which images to add heavily impacts convergence speed. Our work shows that the right choice of the image selection metric positively impacts the effectiveness of the evolutionary algorithm.

关键词： cartesian genetic programming biomedical data data sampling active learning

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CGP4Matlab-A cartesian genetic programming MATLAB Toolbox for Audio and Image Processing 21st

CGP4Matlab-A Cartesian Genetic Programming MATLAB Toolbox fo...

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21st International Conference on the Applications of Evolutionary Computation (EvoApplications)

作者： Miragaia, Rolando Reis, Gustavo Fernandez, Francisco Inacio, Tiago Grilo, Carlos Polytech Inst Leiria Comp Sci & Commun Res Ctr Sch Technol & Management Leiria Portugal Univ Extremadura Badajoz Spain

ISBN: (纸本)9783319775388

This paper presents and describes CGP4Matlab, a powerful toolbox that allows to run cartesian genetic programming within MATLAB. This toolbox is particularly suited for signal processing and image processing problems. The implementation of CGP4Matlab, which can be freely downloaded, is described. Some encouraging results on the problem of pitch estimation of musical piano notes achieved using this toolbox are also presented. Pitch estimation of audio signals is a very hard problem with still no generic and robust solution found. Due to the highly flexibility of CGP4Matlab, we managed to apply a new cartesian genetic programming based approach to the problem of pitch estimation. The obtained results are comparable with the state of the art algorithms.

关键词： cartesian genetic programming MATLAB toolbox Pitch estimation

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Detection of Microcalcifications in Mammograms using Multi-chromosome cartesian genetic programming 10

Detection of Microcalcifications in Mammograms using Multi-c...

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12th Annual genetic and Evolutionary Computation Conference (GECCO)

作者： Miller, Julian F. Smith, Stephen L. Zhang, Yuan Univ York Dept Elect York YO10 5DD N Yorkshire England

ISBN: (纸本)9781450300735

Mammograms are high resolution x-rays of the breast that are widely used to screen for cancer in women. This paper describes the first stage of development of a novel representation of cartesian genetic programming as part of a computer aided diagnostic system. Specifically, this work is concerned with automated recognition of microcalcifications, one of the key structures used to identify cancer. Results are presented for the application of the proposed algorithm to a number of mammogram sections taken from the Lawrence Livermore National Laboratory database. These demonstrate the proposed representation is effective in locating microcalcifications and will provide a promising basis on which to conduct future work in discriminating between microcalcifications that are indicative of cancer and those that are not.

关键词： Mammography cartesian genetic programming genetic programming

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Hardware design of a model generator based on grammars and cartesian genetic programming for blood glucose prediction

Hardware design of a model generator based on grammars and c...

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genetic and Evolutionary Computation Conference (GECCO)

作者： Cano, Jorge Hidalgo, J. Ignacio Garnica, Oscar Lanchares, Juan Univ Complutense Madrid Madrid Spain

ISBN: (纸本)9798400701207

People with diabetes need to control their blood glucose levels to avoid dangerous situations such as getting into hypoglycemia or hyperglycemia, which can lead to long-term and short-term complications. One of the most important daily tasks of people with diabetes is to estimate or predict the glucose in a near future as a consequence of medication, eating, or insulin administration events. We present a parameterized hardware implementation of a blood glucose level predictor generator. The design was implemented over a Field Programmable Gate Array and uses as input variables a set of data from the person (blood glucose levels, carbohydrates, and insulin units). Our implementation produces personal devices the patient can use whenever new readings of the variable are available. Moreover, it could be combined with insulin pumps and continuous glucose monitoring systems to develop an artificial pancreas. For the model generation, we designed a novel technique based on grammars, cartesian genetic programming with an evolutionary strategy (1+lambda) and a fitness function based on the Clarke Error Grid Analysis. Preliminary results show that our hardware implementation achieved higher speeds and lower power consumption than its software counterparts while preserving or even improving the accuracy of the predictions.

关键词： cartesian genetic programming Grammar-based genetic programming Hardware accelerator Field programmable gate array Blood glucose prediction

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A New Subgraph Crossover for cartesian genetic programming 20th

A New Subgraph Crossover for Cartesian Genetic Programming

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20th European Conference on genetic programming (EuroGP)

作者： Kalkreuth, Roman Rudolph, Gunter Droschinsky, Andre TU Dortmund Univ Dept Comp Sci Dortmund Germany

ISBN: (纸本)9783319556963;9783319556956

While tree-based genetic programming is often used with crossover, cartesian genetic programming is mostly used only with mutation as genetic operator. In this paper, a new crossover technique is introduced which recombines subgraphs of two selected graphs. Experiments on symbolic regression, boolean functions and image operator design problems indicate that the use of the subgraph crossover improves the search performance of cartesian genetic programming. A preliminary comparison to a former proposed crossover technique indicates that the subgraph crossover performs better on our tested problems.

关键词： cartesian genetic programming Crossover Recombination

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