Genetic programming 19th European Conference, EuroGP 2016, Porto, Portugal, March 30-April 1, 2016, Proceedings /
This book constitutes the refereed proceedings of the 19th European Conference on Genetic Programming, EuroGP 2016, held in Porto, Portugal, in March/April 2016 co-located with the Evo*2016 events: EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers presented together with 8 poster pa...
| Corporate Authors: | EuroGP (Conference) Porto, Portugal) |
|---|---|
| Other Authors: | EuroGP (Conference), Heywood, Malcolm I.,, McDermott, James (Computer scientist), Castelli, Mauro (Professor of Natural Computing),, Costa, Ernesto,, Sim, Kevin (Lecturer in computing science),, SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
Switzerland :
Springer,
2016.
|
| Physical Description: |
1 online resource (xii, 311 pages) : illustrations. |
| Series: |
Lecture notes in computer science ;
9594. LNCS sublibrary. Theoretical computer science and general issues. |
| Subjects: |
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| 245 | 1 | 0 | |a Genetic programming : |b 19th European Conference, EuroGP 2016, Porto, Portugal, March 30-April 1, 2016, Proceedings / |c Malcolm I. Heywood, James McDermott, Mauro Castelli, Ernesto Costa, Kevin Sim (eds.). |
| 246 | 3 | |a EuroGP 2016. | |
| 264 | 1 | |a Switzerland : |b Springer, |c 2016. | |
| 300 | |a 1 online resource (xii, 311 pages) : |b illustrations. | ||
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| 490 | 1 | |a Lecture notes in computer science, |x 0302-9743 ; |v 9594. | |
| 490 | 1 | |a LNCS sublibrary. SL 1, Theoretical computer science and general issues. | |
| 500 | |a International conference proceedings. | ||
| 500 | |a Includes author index. | ||
| 588 | 0 | |a Online resource; title from PDF title page (SpringerLink, viewed March 30, 2016). | |
| 520 | |a This book constitutes the refereed proceedings of the 19th European Conference on Genetic Programming, EuroGP 2016, held in Porto, Portugal, in March/April 2016 co-located with the Evo*2016 events: EvoCOP, EvoMUSART, and EvoApplications. The 11 revised full papers presented together with 8 poster papers were carefully reviewed and selected from 36 submissions. The wide range of topics in this volume reflects the current state of research in the field. Thus, we see topics as diverse as semantic methods, recursive programs, grammatical methods, coevolution, Cartesian GP, feature selection, metaheuristics, evolvability, and fitness predictors; and applications including image processing, one-class classification, SQL injection attacks, numerical modelling, streaming data classification, creation and optimisation of circuits, multi-class classification, scheduling in manufacturing and wireless networks. | ||
| 505 | 0 | |a Intro; Preface; Organization; Contents; Full Presentations; One-Class Classification for Anomaly Detection with Kernel Density Estimation and Genetic Programming; 1 Introduction; 2 Related Work; 3 Preliminaries; 3.1 Genetic Programming; 3.2 Kernel Density Estimation; 4 Proposed Approach; 4.1 Description of Method; 4.2 Generating Artificial Data; 5 Experiments; 5.1 Datasets; 5.2 Experimental Settings; 6 Results and Discussion; 7 Conclusion and Further Work; References; Evolutionary Approximation of Edge Detection Circuits; 1 Introduction; 2 Relevant Work; 2.1 Edge Detectors. | |
| 505 | 8 | |a 2.2 Evolutionary Computing in Edge Detector Design2.3 Approximate Computing in Image Processing; 2.4 Evolutionary Circuit Design; 3 Adopting CGP for Circuit Approximation; 3.1 Cartesian Genetic Programming; 3.2 Resources-Oriented Approximation; 4 Experimental Results; 4.1 Evolutionary Approximation of Adders; 4.2 Approximation of Sobel Edge Detector; 4.3 Approximation of Evolved Edge Operator; 5 Conclusions; References; On the Impact of Class Imbalance in GP Streaming Classification with Label Budgets; 1 Introduction; 2 Related Work; 3 Methodology; 3.1 Anytime Operation; 3.2 Archiving Policy. | |
| 505 | 8 | |a 3.3 Sampling Policy4 Experimental Methodology; 4.1 Datasets; 4.2 Class-Wise Detection Rate; 4.3 Parameters; 5 Results; 5.1 Single Generation Performance; 5.2 Multi-generation Performance; 5.3 Overall Detection Rates; 6 Conclusion; References; Genetic Programming for Region Detection, Feature Extraction, Feature Construction and Classification in Image Data; 1 Introduction; 2 Background; 2.1 Related Work; 3 The Proposed Method; 3.1 GP Program Representation; 3.2 Outline of the HoG Function; 3.3 The Fitness Function; 4 Experiment Design; 4.1 Datasets; 4.2 Training and Test Sets. | |
| 505 | 8 | |a 4.3 Baseline Methods4.4 Generating SURF Keypoints; 4.5 Evolutionary Parameters; 5 Results and Discussion; 5.1 Compared to the 2TGP Approach; 5.2 Compared to the Baselines; 6 Further Analysis; 6.1 Example Program 1; 6.2 Example Program 2; 6.3 Example Program 3; 7 Conclusions; References; Surrogate Fitness via Factorization of Interaction Matrix; 1 Introduction; 2 Background; 3 Factorization of Interaction Matrix; 4 The SFIMX Algorithm; 5 Related Work; 6 Experimental Verification; 7 Conclusions and Future Work; References. | |
| 505 | 8 | |a Scheduling in Heterogeneous Networks Using Grammar-Based Genetic Programming1 Introduction; 2 Problem Definition; 3 Previous Work; 4 Simulation Environment; 4.1 Generating Inputs; 4.2 Calculating Fitness; 5 Experiments; 6 Results and Discussion; 6.1 Terminal Utilisation; 6.2 Subframe Utilisation; 6.3 Benchmarking; 7 Future Work and Conclusions; References; On the Analysis of Simple Genetic Programming for Evolving Boolean Functions; 1 Introduction; 2 Preliminaries; 3 Analysis for Complete Training Sets; 3.1 Analysis for ANDn with Complete Training Sets. | |
| 546 | |a English. | ||
| 650 | 0 | |a Genetic programming (Computer science) |v Congresses. | |
| 650 | 6 | |a Programmation génétique (Informatique) |v Congrès. | |
| 650 | 7 | |a User interface design & usability. |2 bicssc. | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc. | |
| 650 | 7 | |a Information technology: general issues. |2 bicssc. | |
| 650 | 7 | |a Discrete mathematics. |2 bicssc. | |
| 650 | 7 | |a Algorithms & data structures. |2 bicssc. | |
| 650 | 7 | |a Computers |x Machine Theory. |2 bisacsh. | |
| 650 | 7 | |a Computers |x Intelligence (AI) & Semantics. |2 bisacsh. | |
| 650 | 7 | |a Computers |x Data Processing. |2 bisacsh. | |
| 650 | 7 | |a Computers |x Programming |x Algorithms. |2 bisacsh. | |
| 650 | 7 | |a Genetic programming (Computer science) |2 fast. | |
| 655 | 7 | |a Conference papers and proceedings. |2 fast. | |
| 655 | 7 | |a Conference papers and proceedings. |2 lcgft. | |
| 700 | 1 | |a Heywood, Malcolm I., |e editor. | |
| 700 | 1 | |a McDermott, James |c (Computer scientist) |1 https://id.oclc.org/worldcat/entity/E39PCjH4xXcqQdrx88QF8WMWrC, |e editor. | |
| 700 | 1 | |a Castelli, Mauro |c (Professor of Natural Computing), |e editor. | |
| 700 | 1 | |a Costa, Ernesto, |e editor. | |
| 700 | 1 | |a Sim, Kevin |c (Lecturer in computing science), |e editor. | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 776 | |z 3-319-30667-7. | ||
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