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Electric mobility in public transport--driving towards cleaner air / / editors, Krzysztof Krawiec, Sylwester Markusik, Grzegorz Sierpinski
| Electric mobility in public transport--driving towards cleaner air / / editors, Krzysztof Krawiec, Sylwester Markusik, Grzegorz Sierpinski |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (viii, 216 pages) : illustrations (some color) |
| Disciplina | 388.3493 |
| Collana | Lecture notes in intelligent transportation and infrastructure |
| Soggetto topico |
Transportation - Technological innovations
Transportation and state Buses, Electric Vehicles elèctrics Transport públic Autobusos Política de transports Seguretat informàtica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-67431-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483687103321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Genetic Programming [[electronic resource] ] : 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers / / edited by Miguel Nicolau, Krzysztof Krawiec, Malcolm I. Heywood, Mauro Castelli, Pablo García-Sánchez, Juan J. Merelo, Victor Manuel Rivas Santos, Kevin Sim
| Genetic Programming [[electronic resource] ] : 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers / / edited by Miguel Nicolau, Krzysztof Krawiec, Malcolm I. Heywood, Mauro Castelli, Pablo García-Sánchez, Juan J. Merelo, Victor Manuel Rivas Santos, Kevin Sim |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (XII, 247 p. 78 illus.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science Artificial intelligence Application software Theory of Computation Artificial Intelligence Computer and Information Systems Applications |
| ISBN | 3-662-44303-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Table of Contents -- Oral Presentations -- Higher Order Functions for Kernel Regression -- 1 Introduction -- 2 Kernel Regression -- 3 Higher Order Functions -- 4 Method -- 4.1 Wrapper Approach to the Evolution of Distance Measures -- 4.2 Experiment Design -- 5 Results Analysis -- 6 Conclusion and Future Work -- References -- Flash: A GP-GPU Ensemble Learning System for Handling Large Datasets -- 1 Introduction -- 2 Related Work: Accelerating GP with GPUs -- 3 The Core GP Learner -- 3.1 Mean Squared Error and Pearson Correlation on GPUs -- 3.2 Individual Level Parallelism -- 4 Flash - The GP-GPU Ensemble Learning System -- 4.1 GP Instances -- 4.2 Generating a Fused Model -- 5 Experimental Setup -- 5.1 Million Song Dataset Year Prediction Challenge -- 5.2 Ensemble Configurations -- 6 Results -- 6.1 Prediction Error Analysis -- 6.2 Prediction Error vs. GP Instances -- 6.3 Runtime Analysis -- 7 Conclusions and Future Work -- References -- Learning Dynamical Systems Using Standard Symbolic Regression -- 1 Introduction -- 2 Background -- 2.1 Genetic Programming and Symbolic Regression -- 2.2 Differential Equations and First-Order Approximation -- 3 Proposed Approach -- 4 Case Study -- 5 Experimental Results -- 5.1 Noise-Free Data -- 5.2 Absolute Noise -- 5.3 Noise 5% -- 5.4 Noise 10% -- 6 Results Discussion -- 7 Conclusions and Future Works -- References -- Semantic Crossover Based on the Partial Derivative Error -- 1 Introduction -- 2 Semantic Crossover Based on Partial Derivative Error -- 2.1 Backpropagation -- 2.2 Selecting the Crossing Points -- 3 Results -- 4 Conclusions -- References -- A Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems -- 1 Introduction -- 2 Related Work -- 3 Formulation of Multi-dimensional GP -- 4 Algorithm -- 5 Experimental Analysis -- 5.1 Data Sets.
5.2 Experiments with GP Classifiers -- 5.3 Comparison with Various Classifiers -- 6 Conclusions and Future Directions -- References -- Generalisation Enhancement via Input Space Transformation: A GP Approach -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Trees Return Multiple Outputs -- 3.2 FitnessMeasure -- 4 Experiments and Analysis -- 4.1 Experimental Settings -- 4.2 Results -- 5 Conclusions -- References -- On Diversity, Teaming, and Hierarchical Policies: Observations from the Keepaway Soccer Task -- 1 Introduction -- 2 Related Work -- 3 Hierarchical Symbiotic Policy Search -- 3.1 Symbiont -- 3.2 Variation Operators -- 3.3 Selection Operator -- 3.4 Constructing Hierarchical Policies -- 3.5 Fitness and Diversity -- 4 Results -- 5 Conclusion -- References -- Genetically Improved CUDA C++ Software -- 1 Introduction -- 2 Source Code: StereoCamera -- 3 Example Stereo Pairs from Microsoft's I2I Database -- 4 Pre- and Post- Evolution Tuning and Post Evolution Minimisation of Code Changes -- 5 Alternative Implementations -- 5.1 Avoiding Reusing Threads: XHALO -- 5.2 Parallel of Discrepancy Offsets: DPER -- 6 Parameters Accessible to Evolution -- 6.1 Fixed Configuration Parameters -- 7 Evolvable Code -- 7.1 Initial Population -- 7.2 Weights -- 7.3 Mutation -- 7.4 Crossover -- 7.5 Fitness -- 7.6 Selection -- 8 Results -- 8.1 GP Better Than Random Search -- 9 Evolved Tesla K20c CUDA Code -- 10 Conclusions -- References -- Measuring Mutation Operators' Exploration-Exploitation Behaviour and Long-Term Biases -- 1 Introduction -- 1.1 Reader's Guide -- 2 Related Work -- 3 Statistics on Markov Chains -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Measuring Exploration-Exploitation Behaviour -- 4.3 Exploration-Exploitation Behaviour and Search Space Coverage -- 4.4 Exploration-Exploitation Behaviour and Performance. 4.5 Stationary Distributions -- 5 Conclusions -- 5.1 Limitations -- 5.2 Future Work -- References -- Exploring the Search Space of Hardware / Software Embedded Systems by Means of GP -- 1 Introduction -- 2 Previous Work -- 2.1 Hardware -- 2.2 Software -- 3 Proposed Extensions -- 3.1 Evolvable Hardware Topology Related Changes -- 3.2 Input Modules -- 3.3 Problem Encoding and Search Method -- 4 Experimental Results -- 4.1 Newton-Raphson Division -- 4.2 Finding the Maximum -- 4.3 Parity -- 5 Conclusions -- References -- Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming -- 1 Introduction -- 1.1 Goals -- 1.2 Organisation -- 2 Methodology -- 2.1 Branch and Bound Algorithm for OAS -- 3 Computational Results -- 3.1 Datasets -- 3.2 Results -- 4 Conclusions -- References -- Using Genetic Improvement and Code Transplants to Specialise a C++ Program to a Problem Class -- 1 Introduction -- 2 Genetic Improvement with Multi-donor Transplantation and Specialisation -- 3 Experimental Setup -- 4 Results -- 4.1 Transplanting from MiniSAT-best09 -- 4.2 Transplanting from MiniSAT-bestCIT -- 4.3 Transplanting from MiniSAT-best09 and MiniSAT-bestCIT -- 4.4 Combining Results -- 5 Summary of Related Work -- 6 Conclusions -- References -- ESAGP - A Semantic GP Framework Based on Alignment in the Error Space -- 1 Introduction -- 2 Alignment in the Error Space -- 3 One Step Error Space Alignment GP: ESAGP-1 -- 4 Two Steps Error Space Alignment GP: ESAGP-2 -- 5 Experimental Study -- 6 Conclusions and Future Work -- References -- Building a Stage 1 Computer Aided Detector for Breast Cancer Using Genetic Programming -- 1 Introduction -- 2 Mammography -- 2.1 Computer-Aided Detection of Mammographic Abnormalities -- 2.2 Feature Extraction -- 2.3 Related Work -- 3 Workflow -- 3.1 Separation -- 3.2 Suppression of the Background. 3.3 Segmentation -- 3.4 Textural Features -- 4 Experimental Setup -- 4.1 GP Setup -- 5 Results -- 6 Conclusions and Future Work -- References -- NEAT, There's No Bloat -- 1 Introduction -- 2 Bloat -- 2.1 Causes of Bloat and Bloat Control Methods -- 2.2 The Secret Behind Operator Equalization -- 3 NeuroEvolution of Augmenting Topologies -- 3.1 NEAT Features -- 3.2 NEAT, GP and Bloat -- 4 Experiments -- 4.1 Discussion -- 5 Concluding Remarks and Future Work -- References -- Posters -- The Best Things Don't Always Come in Small Packages: Constant Creation in Grammatical Evolution -- 1 Introduction -- 2 Background -- 3 Experiments -- 3.1 Problem Suite and Evolutionary Parameters -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Asynchronous Evolution by Reference-Based Evaluation: Tertiary Parent Selection and Its Archive -- 1 Introduction -- 2 Tierra-Based Asynchronous Genetic Programming -- 2.1 Overview -- 2.2 Algorithm -- 3 Asynchronous Reference-Based Evaluation -- 3.1 Concept -- 3.2 Algorithm -- 4 Experiment -- 4.1 Settings -- 4.2 Results -- 5 Conclusion -- References -- Behavioral Search Drivers for Genetic Programing -- 1 Introduction -- 2 Background -- 3 Motivation -- 4 Behavioral Evaluation of Programs in GP -- 5 TheExperiment -- 6 Related Work -- 7 Conclusion -- References -- Cartesian Genetic Programming: Why No Bloat? -- 1 Introduction -- 2 Cartesian Genetic Programming -- 3 Bloat and CGP -- 3.1 Neutral Genetic Drift -- 3.2 Length Bias -- 4 Experiments -- 4.1 Regular CGP -- 4.2 No Neutral Genetic Drift -- 4.3 Recurrent CGP -- 4.4 Neutral Search -- 5 Results -- 5.1 Regular CGP -- 5.2 No Neutral Genetic Drift -- 5.3 Recurrent CGP -- 5.4 Neutral Search -- 6 Discussion -- 7 Conclusion -- References -- On Evolution of Multi-category Pattern Classifiers Suitable for Embedded Systems -- 1 Introduction. 2 Cartesian Genetic Programming -- 2.1 Representation -- 2.2 Search Algorithm -- 3 Evolutionary Design of Classifiers -- 4 Experimental Setup -- 5 Experimental Results -- 5.1 Evaluation of the Evolved Classifiers -- 6 Conclusion -- References -- Author Index. |
| Record Nr. | UNISA-996202528503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Genetic Programming : 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers / / edited by Miguel Nicolau, Krzysztof Krawiec, Malcolm I. Heywood, Mauro Castelli, Pablo García-Sánchez, Juan J. Merelo, Victor Manuel Rivas Santos, Kevin Sim
| Genetic Programming : 17th European Conference, EuroGP 2014, Granada, Spain, April 23-25, 2014, Revised Selected Papers / / edited by Miguel Nicolau, Krzysztof Krawiec, Malcolm I. Heywood, Mauro Castelli, Pablo García-Sánchez, Juan J. Merelo, Victor Manuel Rivas Santos, Kevin Sim |
| Edizione | [1st ed. 2014.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014 |
| Descrizione fisica | 1 online resource (XII, 247 p. 78 illus.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science Artificial intelligence Application software Theory of Computation Artificial Intelligence Computer and Information Systems Applications |
| ISBN | 3-662-44303-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Table of Contents -- Oral Presentations -- Higher Order Functions for Kernel Regression -- 1 Introduction -- 2 Kernel Regression -- 3 Higher Order Functions -- 4 Method -- 4.1 Wrapper Approach to the Evolution of Distance Measures -- 4.2 Experiment Design -- 5 Results Analysis -- 6 Conclusion and Future Work -- References -- Flash: A GP-GPU Ensemble Learning System for Handling Large Datasets -- 1 Introduction -- 2 Related Work: Accelerating GP with GPUs -- 3 The Core GP Learner -- 3.1 Mean Squared Error and Pearson Correlation on GPUs -- 3.2 Individual Level Parallelism -- 4 Flash - The GP-GPU Ensemble Learning System -- 4.1 GP Instances -- 4.2 Generating a Fused Model -- 5 Experimental Setup -- 5.1 Million Song Dataset Year Prediction Challenge -- 5.2 Ensemble Configurations -- 6 Results -- 6.1 Prediction Error Analysis -- 6.2 Prediction Error vs. GP Instances -- 6.3 Runtime Analysis -- 7 Conclusions and Future Work -- References -- Learning Dynamical Systems Using Standard Symbolic Regression -- 1 Introduction -- 2 Background -- 2.1 Genetic Programming and Symbolic Regression -- 2.2 Differential Equations and First-Order Approximation -- 3 Proposed Approach -- 4 Case Study -- 5 Experimental Results -- 5.1 Noise-Free Data -- 5.2 Absolute Noise -- 5.3 Noise 5% -- 5.4 Noise 10% -- 6 Results Discussion -- 7 Conclusions and Future Works -- References -- Semantic Crossover Based on the Partial Derivative Error -- 1 Introduction -- 2 Semantic Crossover Based on Partial Derivative Error -- 2.1 Backpropagation -- 2.2 Selecting the Crossing Points -- 3 Results -- 4 Conclusions -- References -- A Multi-dimensional Genetic Programming Approach for Multi-class Classification Problems -- 1 Introduction -- 2 Related Work -- 3 Formulation of Multi-dimensional GP -- 4 Algorithm -- 5 Experimental Analysis -- 5.1 Data Sets.
5.2 Experiments with GP Classifiers -- 5.3 Comparison with Various Classifiers -- 6 Conclusions and Future Directions -- References -- Generalisation Enhancement via Input Space Transformation: A GP Approach -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Trees Return Multiple Outputs -- 3.2 FitnessMeasure -- 4 Experiments and Analysis -- 4.1 Experimental Settings -- 4.2 Results -- 5 Conclusions -- References -- On Diversity, Teaming, and Hierarchical Policies: Observations from the Keepaway Soccer Task -- 1 Introduction -- 2 Related Work -- 3 Hierarchical Symbiotic Policy Search -- 3.1 Symbiont -- 3.2 Variation Operators -- 3.3 Selection Operator -- 3.4 Constructing Hierarchical Policies -- 3.5 Fitness and Diversity -- 4 Results -- 5 Conclusion -- References -- Genetically Improved CUDA C++ Software -- 1 Introduction -- 2 Source Code: StereoCamera -- 3 Example Stereo Pairs from Microsoft's I2I Database -- 4 Pre- and Post- Evolution Tuning and Post Evolution Minimisation of Code Changes -- 5 Alternative Implementations -- 5.1 Avoiding Reusing Threads: XHALO -- 5.2 Parallel of Discrepancy Offsets: DPER -- 6 Parameters Accessible to Evolution -- 6.1 Fixed Configuration Parameters -- 7 Evolvable Code -- 7.1 Initial Population -- 7.2 Weights -- 7.3 Mutation -- 7.4 Crossover -- 7.5 Fitness -- 7.6 Selection -- 8 Results -- 8.1 GP Better Than Random Search -- 9 Evolved Tesla K20c CUDA Code -- 10 Conclusions -- References -- Measuring Mutation Operators' Exploration-Exploitation Behaviour and Long-Term Biases -- 1 Introduction -- 1.1 Reader's Guide -- 2 Related Work -- 3 Statistics on Markov Chains -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Measuring Exploration-Exploitation Behaviour -- 4.3 Exploration-Exploitation Behaviour and Search Space Coverage -- 4.4 Exploration-Exploitation Behaviour and Performance. 4.5 Stationary Distributions -- 5 Conclusions -- 5.1 Limitations -- 5.2 Future Work -- References -- Exploring the Search Space of Hardware / Software Embedded Systems by Means of GP -- 1 Introduction -- 2 Previous Work -- 2.1 Hardware -- 2.2 Software -- 3 Proposed Extensions -- 3.1 Evolvable Hardware Topology Related Changes -- 3.2 Input Modules -- 3.3 Problem Encoding and Search Method -- 4 Experimental Results -- 4.1 Newton-Raphson Division -- 4.2 Finding the Maximum -- 4.3 Parity -- 5 Conclusions -- References -- Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming -- 1 Introduction -- 1.1 Goals -- 1.2 Organisation -- 2 Methodology -- 2.1 Branch and Bound Algorithm for OAS -- 3 Computational Results -- 3.1 Datasets -- 3.2 Results -- 4 Conclusions -- References -- Using Genetic Improvement and Code Transplants to Specialise a C++ Program to a Problem Class -- 1 Introduction -- 2 Genetic Improvement with Multi-donor Transplantation and Specialisation -- 3 Experimental Setup -- 4 Results -- 4.1 Transplanting from MiniSAT-best09 -- 4.2 Transplanting from MiniSAT-bestCIT -- 4.3 Transplanting from MiniSAT-best09 and MiniSAT-bestCIT -- 4.4 Combining Results -- 5 Summary of Related Work -- 6 Conclusions -- References -- ESAGP - A Semantic GP Framework Based on Alignment in the Error Space -- 1 Introduction -- 2 Alignment in the Error Space -- 3 One Step Error Space Alignment GP: ESAGP-1 -- 4 Two Steps Error Space Alignment GP: ESAGP-2 -- 5 Experimental Study -- 6 Conclusions and Future Work -- References -- Building a Stage 1 Computer Aided Detector for Breast Cancer Using Genetic Programming -- 1 Introduction -- 2 Mammography -- 2.1 Computer-Aided Detection of Mammographic Abnormalities -- 2.2 Feature Extraction -- 2.3 Related Work -- 3 Workflow -- 3.1 Separation -- 3.2 Suppression of the Background. 3.3 Segmentation -- 3.4 Textural Features -- 4 Experimental Setup -- 4.1 GP Setup -- 5 Results -- 6 Conclusions and Future Work -- References -- NEAT, There's No Bloat -- 1 Introduction -- 2 Bloat -- 2.1 Causes of Bloat and Bloat Control Methods -- 2.2 The Secret Behind Operator Equalization -- 3 NeuroEvolution of Augmenting Topologies -- 3.1 NEAT Features -- 3.2 NEAT, GP and Bloat -- 4 Experiments -- 4.1 Discussion -- 5 Concluding Remarks and Future Work -- References -- Posters -- The Best Things Don't Always Come in Small Packages: Constant Creation in Grammatical Evolution -- 1 Introduction -- 2 Background -- 3 Experiments -- 3.1 Problem Suite and Evolutionary Parameters -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Asynchronous Evolution by Reference-Based Evaluation: Tertiary Parent Selection and Its Archive -- 1 Introduction -- 2 Tierra-Based Asynchronous Genetic Programming -- 2.1 Overview -- 2.2 Algorithm -- 3 Asynchronous Reference-Based Evaluation -- 3.1 Concept -- 3.2 Algorithm -- 4 Experiment -- 4.1 Settings -- 4.2 Results -- 5 Conclusion -- References -- Behavioral Search Drivers for Genetic Programing -- 1 Introduction -- 2 Background -- 3 Motivation -- 4 Behavioral Evaluation of Programs in GP -- 5 TheExperiment -- 6 Related Work -- 7 Conclusion -- References -- Cartesian Genetic Programming: Why No Bloat? -- 1 Introduction -- 2 Cartesian Genetic Programming -- 3 Bloat and CGP -- 3.1 Neutral Genetic Drift -- 3.2 Length Bias -- 4 Experiments -- 4.1 Regular CGP -- 4.2 No Neutral Genetic Drift -- 4.3 Recurrent CGP -- 4.4 Neutral Search -- 5 Results -- 5.1 Regular CGP -- 5.2 No Neutral Genetic Drift -- 5.3 Recurrent CGP -- 5.4 Neutral Search -- 6 Discussion -- 7 Conclusion -- References -- On Evolution of Multi-category Pattern Classifiers Suitable for Embedded Systems -- 1 Introduction. 2 Cartesian Genetic Programming -- 2.1 Representation -- 2.2 Search Algorithm -- 3 Evolutionary Design of Classifiers -- 4 Experimental Setup -- 5 Experimental Results -- 5.1 Evaluation of the Evolved Classifiers -- 6 Conclusion -- References -- Author Index. |
| Record Nr. | UNINA-9910484703203321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2014 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Genetic Programming [[electronic resource] ] : 16th European Conference, EuroGP 2013, Vienna, Austria, April 3-5, 2013, Proceedings / / edited by Krzysztof Krawiec, Alberto Moraglio, Ting Hu, A. Sima Etaner-Uyar, Bin Hu
| Genetic Programming [[electronic resource] ] : 16th European Conference, EuroGP 2013, Vienna, Austria, April 3-5, 2013, Proceedings / / edited by Krzysztof Krawiec, Alberto Moraglio, Ting Hu, A. Sima Etaner-Uyar, Bin Hu |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XII, 277 p. 99 illus.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science Artificial intelligence Application software Theory of Computation Artificial Intelligence Computer and Information Systems Applications |
| ISBN | 3-642-37207-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adaptive Distance Metrics for Nearest Neighbour Classification Based on Genetic Programming.- Controlling Bloat through Parsimonious Elitist Replacement and Spatial Structure.- Generation of VNS Components with Grammatical Evolution for Vehicle Routing.- Understanding Expansion Order and Phenotypic Connectivity in πGE.- PhenoGP: Combining Programs to Avoid Code Disruption.- Reducing Wasted Evaluations in Cartesian Genetic Programming.- Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data.- Automated Design of Probability Distributions as Mutation Operators for Evolutionary Programming Using Genetic Programming.- Robustness and Evolvability of Recombination in Linear Genetic Programming.- On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming Methodology.- Discovering Subgroups by Means of Genetic Programming.- Program Optimisation with Dependency Injection.- Searching for Novel Classifiers.- Learning Reusable Initial Solutions for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming.- Automated Problem Decomposition for the Boolean Domain with Genetic Programming.- A Multi-objective Optimization Energy Approach to Predict the Ligand Conformation in a Docking Process.- Semantic Bias in Program Coevolution.- A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokinetics -- A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification.- Global Top-Scoring Pair Decision Tree for Gene Expression Data Analysis.- Asynchronous Evaluation Based Genetic Programming: Comparison of Asynchronous and Synchronous Evaluation and Its Analysis.- How Early and with How Little Data? Using Genetic Programming to Evolve Endurance Classifiers for MLC NAND Flash Memory.- Examining the Diversity Property of Semantic Similarity Based Crossover. Controlling Bloat through Parsimonious Elitist Replacement and Spatial Structure.- Generation of VNS Components with Grammatical Evolution for Vehicle Routing.- Understanding Expansion Order and Phenotypic Connectivity in πGE.- PhenoGP: Combining Programs to Avoid Code Disruption.- Reducing Wasted Evaluations in Cartesian Genetic Programming.- Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data.- Automated Design of Probability Distributions as Mutation Operators for Evolutionary Programming Using Genetic Programming.- Robustness and Evolvability of Recombination in Linear Genetic Programming.- On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming Methodology.- Discovering Subgroups by Means of Genetic Programming.- Program Optimisation with Dependency Injection.- Searching for Novel Classifiers.- Learning Reusable Initial Solutions for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming.- Automated Problem Decomposition for the Boolean Domain with Genetic Programming.- A Multi-objective Optimization Energy Approach to Predict the Ligand Conformation in a Docking Process.- Semantic Bias in Program Coevolution.- A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokinetics -- A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification.- Global Top-Scoring Pair Decision Tree for Gene Expression Data Analysis.- Asynchronous Evaluation Based Genetic Programming: Comparison of Asynchronous and Synchronous Evaluation and Its Analysis.- How Early and with How Little Data? Using Genetic Programming to Evolve Endurance Classifiers for MLC NAND Flash Memory.- Examining the Diversity Property of Semantic Similarity Based Crossover. |
| Record Nr. | UNISA-996465581303316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Genetic Programming : 16th European Conference, EuroGP 2013, Vienna, Austria, April 3-5, 2013, Proceedings / / edited by Krzysztof Krawiec, Alberto Moraglio, Ting Hu, A. Sima Etaner-Uyar, Bin Hu
| Genetic Programming : 16th European Conference, EuroGP 2013, Vienna, Austria, April 3-5, 2013, Proceedings / / edited by Krzysztof Krawiec, Alberto Moraglio, Ting Hu, A. Sima Etaner-Uyar, Bin Hu |
| Edizione | [1st ed. 2013.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 |
| Descrizione fisica | 1 online resource (XII, 277 p. 99 illus.) |
| Disciplina | 006.31 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Algorithms
Computer science Artificial intelligence Application software Theory of Computation Artificial Intelligence Computer and Information Systems Applications |
| ISBN | 3-642-37207-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Adaptive Distance Metrics for Nearest Neighbour Classification Based on Genetic Programming.- Controlling Bloat through Parsimonious Elitist Replacement and Spatial Structure.- Generation of VNS Components with Grammatical Evolution for Vehicle Routing.- Understanding Expansion Order and Phenotypic Connectivity in πGE.- PhenoGP: Combining Programs to Avoid Code Disruption.- Reducing Wasted Evaluations in Cartesian Genetic Programming.- Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data.- Automated Design of Probability Distributions as Mutation Operators for Evolutionary Programming Using Genetic Programming.- Robustness and Evolvability of Recombination in Linear Genetic Programming.- On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming Methodology.- Discovering Subgroups by Means of Genetic Programming.- Program Optimisation with Dependency Injection.- Searching for Novel Classifiers.- Learning Reusable Initial Solutions for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming.- Automated Problem Decomposition for the Boolean Domain with Genetic Programming.- A Multi-objective Optimization Energy Approach to Predict the Ligand Conformation in a Docking Process.- Semantic Bias in Program Coevolution.- A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokinetics -- A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification.- Global Top-Scoring Pair Decision Tree for Gene Expression Data Analysis.- Asynchronous Evaluation Based Genetic Programming: Comparison of Asynchronous and Synchronous Evaluation and Its Analysis.- How Early and with How Little Data? Using Genetic Programming to Evolve Endurance Classifiers for MLC NAND Flash Memory.- Examining the Diversity Property of Semantic Similarity Based Crossover. Controlling Bloat through Parsimonious Elitist Replacement and Spatial Structure.- Generation of VNS Components with Grammatical Evolution for Vehicle Routing.- Understanding Expansion Order and Phenotypic Connectivity in πGE.- PhenoGP: Combining Programs to Avoid Code Disruption.- Reducing Wasted Evaluations in Cartesian Genetic Programming.- Balancing Learning and Overfitting in Genetic Programming with Interleaved Sampling of Training Data.- Automated Design of Probability Distributions as Mutation Operators for Evolutionary Programming Using Genetic Programming.- Robustness and Evolvability of Recombination in Linear Genetic Programming.- On the Evolvability of a Hybrid Ant Colony-Cartesian Genetic Programming Methodology.- Discovering Subgroups by Means of Genetic Programming.- Program Optimisation with Dependency Injection.- Searching for Novel Classifiers.- Learning Reusable Initial Solutions for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming.- Automated Problem Decomposition for the Boolean Domain with Genetic Programming.- A Multi-objective Optimization Energy Approach to Predict the Ligand Conformation in a Docking Process.- Semantic Bias in Program Coevolution.- A New Implementation of Geometric Semantic GP and Its Application to Problems in Pharmacokinetics -- A Grammar-Guided Genetic Programming Algorithm for Multi-Label Classification.- Global Top-Scoring Pair Decision Tree for Gene Expression Data Analysis.- Asynchronous Evaluation Based Genetic Programming: Comparison of Asynchronous and Synchronous Evaluation and Its Analysis.- How Early and with How Little Data? Using Genetic Programming to Evolve Endurance Classifiers for MLC NAND Flash Memory.- Examining the Diversity Property of Semantic Similarity Based Crossover. |
| Record Nr. | UNINA-9910483354903321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Genetic Programming : 15th European Conference, EuroGP 2012, Málaga, Spain, April 11-13, 2012, Proceedings / / edited by Alberto Moraglio, Sara Silva, Krzysztof Krawiec, Penousal Machado, Carlos Cotta
| Genetic Programming : 15th European Conference, EuroGP 2012, Málaga, Spain, April 11-13, 2012, Proceedings / / edited by Alberto Moraglio, Sara Silva, Krzysztof Krawiec, Penousal Machado, Carlos Cotta |
| Edizione | [1st ed. 2012.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
| Descrizione fisica | 1 online resource (XII, 279 p. 91 illus.) |
| Disciplina | 005.11 |
| Collana | Theoretical Computer Science and General Issues |
| Soggetto topico |
Computer programming
Computer science Algorithms Application software Artificial intelligence Bioinformatics Programming Techniques Theory of Computation Computer and Information Systems Applications Artificial Intelligence Computational and Systems Biology |
| ISBN | 3-642-29139-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465999303316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||