標(biāo)題: Titlebook: Genetic Programming Theory and Practice VIII; Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva Book 2011 Springer Science+Business Media [打印本頁] 作者: Fuctionary 時(shí)間: 2025-3-21 19:32
書目名稱Genetic Programming Theory and Practice VIII影響因子(影響力)
書目名稱Genetic Programming Theory and Practice VIII影響因子(影響力)學(xué)科排名
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書目名稱Genetic Programming Theory and Practice VIII網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Genetic Programming Theory and Practice VIII被引頻次
書目名稱Genetic Programming Theory and Practice VIII被引頻次學(xué)科排名
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書目名稱Genetic Programming Theory and Practice VIII年度引用學(xué)科排名
書目名稱Genetic Programming Theory and Practice VIII讀者反饋
書目名稱Genetic Programming Theory and Practice VIII讀者反饋學(xué)科排名
作者: 不規(guī)則的跳動(dòng) 時(shí)間: 2025-3-21 23:59 作者: Ossification 時(shí)間: 2025-3-22 03:38 作者: 浮雕寶石 時(shí)間: 2025-3-22 04:34 作者: Gorilla 時(shí)間: 2025-3-22 10:37
Symbolic Density Models of One-in-a-Billion Statistical Tails via Importance Sampling and Genetic P to analyze the tradeoff between high-sigma yields and circuit performance. The flow is validated on two modern industrial problems: a bitcell circuit on a 45nm TSMC process, and a sense amp circuit on a 28nm TSMC process.作者: GILD 時(shí)間: 2025-3-22 13:07 作者: GILD 時(shí)間: 2025-3-22 18:18 作者: Obliterate 時(shí)間: 2025-3-22 21:59
Das Aufbereiten von Textausgabenety of different problems, and see that SMCGP is able to solve tasks that require scalability and plasticity. We demonstrate how SMCGP is able to produce results that would be impossible for conventional, static Genetic Programming techniques.作者: arthrodesis 時(shí)間: 2025-3-23 01:50
Finch: A System for Evolving Java (Bytecode),eral. This is in contrast to existing work that uses restricted subsets of the Java bytecode instruction set as a representation language for individuals in genetic programming. The ability to evolve Java programs will hopefully lead to a valuable new tool in the software engineer’s toolkit.作者: HEAVY 時(shí)間: 2025-3-23 06:10
A Survey of Self Modifying Cartesian Genetic Programming,ety of different problems, and see that SMCGP is able to solve tasks that require scalability and plasticity. We demonstrate how SMCGP is able to produce results that would be impossible for conventional, static Genetic Programming techniques.作者: 食草 時(shí)間: 2025-3-23 11:28 作者: 誤傳 時(shí)間: 2025-3-23 14:29 作者: 大包裹 時(shí)間: 2025-3-23 21:44
https://doi.org/10.1007/978-1-4419-7747-2Genetic Programming; Genetic Programming Applications; Genetic Programming Theory; Symbolic regression; 作者: 保留 時(shí)間: 2025-3-23 22:42
Rick Riolo,Trent McConaghy,Ekaterina VladislavlevaPresents large-scale, real-world applications of GP.Addresses a variety of problem domains that respond to GP solutions.Written by leading researchers and practitioners in the field.Includes supplemen作者: infantile 時(shí)間: 2025-3-24 06:01
,Prüfung statistischer Hypothesen (Tests),h evolution of expressions using these definitions takes place. We have recently developed a system, dubbed FINCH (.ertile Darw.ian Byte.ode .arvester), to evolutionarily improve actual, . software, which was . for the purpose of serving as a GP representation in particular, nor for evolution in gen作者: opprobrious 時(shí)間: 2025-3-24 08:50 作者: Inordinate 時(shí)間: 2025-3-24 12:09 作者: theta-waves 時(shí)間: 2025-3-24 16:40
https://doi.org/10.1007/978-3-531-92042-9requires independent training cases and can only use voting as a cooperation mechanism. This paper compares AdaBoost to Orthogonal Evolution of Teams (OET), an approach for generating ensembles that allows for a much wider range of problems and cooperation mechanisms. The set of test problems includ作者: crescendo 時(shí)間: 2025-3-24 21:34
Das Aufbereiten von Textausgaben in such a way to guarantee that the mean program size will either keep a particular value (e.g., its initial value) or will follow a schedule chosen by the user. The mathematical derivation of the technique as well as its numerical and empirical corroboration are presented.作者: ordain 時(shí)間: 2025-3-25 01:43
Das Aufbereiten von Textausgabenon to the usual computational functions found in CGP, SMCGP includes functions that can modify the evolved program at run time. This means that programs can be iterated to produce an infinite sequence of phenotypes from a single evolved genotype. Here, we discuss the results of using SMCGP on a vari作者: 序曲 時(shí)間: 2025-3-25 03:43
Das Aufbereiten von Textausgaben per se. The techniques explored produce a symbolic regression engine which has absolutely no bloat, which allows total user control of the search space and output formulas, which is faster, and more accurate than the engines produced in our previous papers using Genetic Programming. The genome is a作者: Charade 時(shí)間: 2025-3-25 08:24 作者: 玉米棒子 時(shí)間: 2025-3-25 13:16
,Prüfung der Variablen auf Normalverteilung,hardware and software takes place. Many software algorithms need rethinking to expose all the possible concurrency, increase locality and have built-in fault tolerance. Evolutionary algorithms are naturally parallel and should as such have an edge in exploiting these hardware features..In this paper作者: 無法解釋 時(shí)間: 2025-3-25 16:52
https://doi.org/10.1007/978-3-8349-3575-5’ tails is critical. The problem is of importance to cutting-edge industrial integrated circuit design, such as designing SRAM memory components (bitcells, sense amps) where each component has extremely low probability of failure. A naive approach is infeasible because it would require billions of M作者: V切開 時(shí)間: 2025-3-25 21:19 作者: chandel 時(shí)間: 2025-3-26 01:50 作者: 合并 時(shí)間: 2025-3-26 06:12
https://doi.org/10.1007/978-3-658-18039-3applications, a specialized genome representation is used in order to break the problem down into smaller instances and put them back together. Results showing the applicability of the approaches are presented.作者: Munificent 時(shí)間: 2025-3-26 08:44 作者: 表否定 時(shí)間: 2025-3-26 15:26
Das Aufbereiten von Textausgaben in such a way to guarantee that the mean program size will either keep a particular value (e.g., its initial value) or will follow a schedule chosen by the user. The mathematical derivation of the technique as well as its numerical and empirical corroboration are presented.作者: foliage 時(shí)間: 2025-3-26 18:34 作者: 褻瀆 時(shí)間: 2025-3-27 00:03
Covariant Tarpeian Method for Bloat Control in Genetic Programming, in such a way to guarantee that the mean program size will either keep a particular value (e.g., its initial value) or will follow a schedule chosen by the user. The mathematical derivation of the technique as well as its numerical and empirical corroboration are presented.作者: Adrenal-Glands 時(shí)間: 2025-3-27 03:10
Composition of Music and Financial Strategies via Genetic Programming,applications, a specialized genome representation is used in order to break the problem down into smaller instances and put them back together. Results showing the applicability of the approaches are presented.作者: 售穴 時(shí)間: 2025-3-27 08:40 作者: finale 時(shí)間: 2025-3-27 11:32 作者: Ringworm 時(shí)間: 2025-3-27 16:53 作者: 期滿 時(shí)間: 2025-3-27 21:12 作者: COKE 時(shí)間: 2025-3-27 22:29
Ensemble Classifiers: AdaBoost and Orthogonal Evolution of Teams,noise - suggesting that the hierarchical approach is less subject to over-fitting than voting techniques. The results also suggest that there are specific problems and features of problems that make thembetter suited for different training algorithms and different cooperation mechanisms.作者: Coordinate 時(shí)間: 2025-3-28 02:21
Age-Fitness Pareto Optimization,tion complexities and number of variables. Our results indicate that the multi-objective approach identifies the exact target solution more often than the age-layered population and standard population methods. The multi-objective method also performs better on higher complexity problems and higher 作者: 繼而發(fā)生 時(shí)間: 2025-3-28 08:36 作者: 先兆 時(shí)間: 2025-3-28 13:27
Genetic Programming Transforms in Linear Regression Situations, given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistica作者: AORTA 時(shí)間: 2025-3-28 14:44 作者: 易發(fā)怒 時(shí)間: 2025-3-28 20:59
Evolutionary Art Using Summed Multi-Objective Ranks, distribution measurements requires 3 features to be satisfactory simultaneously. Sum of ranks scoring typically results in images that score better on the majority of features, and are therefore arguably more visually pleasing. Although the ranked sum strategy was originally inspired by highly dime作者: 下船 時(shí)間: 2025-3-29 01:19 作者: irreducible 時(shí)間: 2025-3-29 06:56
https://doi.org/10.1007/978-3-531-93192-0ctions are such that users are likely to face either reward functions that are very expensive to evaluate or functions that are very deceptive. Addressing this might well imply that domain knowledge is explicitly used to decompose the task to avoid these challenges. This would augment the described 作者: 我還要背著他 時(shí)間: 2025-3-29 09:32
https://doi.org/10.1007/978-3-531-92042-9noise - suggesting that the hierarchical approach is less subject to over-fitting than voting techniques. The results also suggest that there are specific problems and features of problems that make thembetter suited for different training algorithms and different cooperation mechanisms.作者: Fantasy 時(shí)間: 2025-3-29 12:18 作者: parallelism 時(shí)間: 2025-3-29 16:14 作者: 彈藥 時(shí)間: 2025-3-29 19:48
https://doi.org/10.1007/978-3-8349-6541-7 given as well. The application benefits of the proposed approach are illustrated with a real industrial application in one of the broadest empirical modeling areas in manufacturing - robust inferential sensors. The chapter contributes to increasing the awareness of the potential of GP in statistica作者: BLOT 時(shí)間: 2025-3-30 03:10
Aufgaben zur Regressionsanalyse,tistical expert knowledge. We anticipate that biological expert knowledge, such as genetic regulatory or protein-protein interaction maps, will provide complementary information, and further improve the ability of CES to model the genetic architectures of common human disease. The goal of this study作者: 親密 時(shí)間: 2025-3-30 05:28 作者: Hemiplegia 時(shí)間: 2025-3-30 08:29 作者: PANG 時(shí)間: 2025-3-30 16:27
Towards Practical Autoconstructive Evolution: Self-Evolution of Problem-Solving Genetic Programming the provided operators or the default parameters will be ideal for all problems or all program representations, practitioners often devote considerable energy to experimentation with alternatives. Attempts to bring choices about operators and parameters under evolutionary control, through self-adap作者: Console 時(shí)間: 2025-3-30 18:10 作者: 飛行員 時(shí)間: 2025-3-30 23:41 作者: Nomogram 時(shí)間: 2025-3-31 04:10
Covariant Tarpeian Method for Bloat Control in Genetic Programming, in such a way to guarantee that the mean program size will either keep a particular value (e.g., its initial value) or will follow a schedule chosen by the user. The mathematical derivation of the technique as well as its numerical and empirical corroboration are presented.作者: comely 時(shí)間: 2025-3-31 06:46
