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Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings /
The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems.
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Berlin, Heidelberg : Springer Berlin Heidelberg,
2000
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| Subjects: | Computer science., Computer communication systems., Algorithms., Artificial intelligence., Image processing., Complexity, Computational., Computer Science., Artificial Intelligence (incl. Robotics)., Algorithm Analysis and Problem Complexity., Computer Communication Networks., Image Processing and Computer Vision., Complexity., |
| Online Access: | http://dx.doi.org/10.1007/3-540-45561-2 |
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Computer science. Computer communication systems. Algorithms. Artificial intelligence. Image processing. Complexity, Computational. Computer Science. Artificial Intelligence (incl. Robotics). Algorithm Analysis and Problem Complexity. Computer Communication Networks. Image Processing and Computer Vision. Complexity. Computer science. Computer communication systems. Algorithms. Artificial intelligence. Image processing. Complexity, Computational. Computer Science. Artificial Intelligence (incl. Robotics). Algorithm Analysis and Problem Complexity. Computer Communication Networks. Image Processing and Computer Vision. Complexity. |
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Computer science. Computer communication systems. Algorithms. Artificial intelligence. Image processing. Complexity, Computational. Computer Science. Artificial Intelligence (incl. Robotics). Algorithm Analysis and Problem Complexity. Computer Communication Networks. Image Processing and Computer Vision. Complexity. Computer science. Computer communication systems. Algorithms. Artificial intelligence. Image processing. Complexity, Computational. Computer Science. Artificial Intelligence (incl. Robotics). Algorithm Analysis and Problem Complexity. Computer Communication Networks. Image Processing and Computer Vision. Complexity. Cagnoni, Stefano. editor. SpringerLink (Online service) Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / |
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The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems. |
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Computer science. Computer communication systems. Algorithms. Artificial intelligence. Image processing. Complexity, Computational. Computer Science. Artificial Intelligence (incl. Robotics). Algorithm Analysis and Problem Complexity. Computer Communication Networks. Image Processing and Computer Vision. Complexity. |
| author |
Cagnoni, Stefano. editor. SpringerLink (Online service) |
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Cagnoni, Stefano. editor. SpringerLink (Online service) |
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Cagnoni, Stefano. editor. |
| title |
Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / |
| title_short |
Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / |
| title_full |
Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / |
| title_fullStr |
Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / |
| title_full_unstemmed |
Real-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / |
| title_sort |
real-world applications of evolutionary computing [electronic resource] : evoworkshops 2000: evoiasp, evoscondi, evotel, evostim, evorob, and evoflight edinburgh, scotland, uk, april 17, 2000 proceedings / |
| publisher |
Berlin, Heidelberg : Springer Berlin Heidelberg, |
| publishDate |
2000 |
| url |
http://dx.doi.org/10.1007/3-540-45561-2 |
| work_keys_str_mv |
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| _version_ |
1756266420528742400 |
| spelling |
KOHA-OAI-TEST:1930862018-07-30T23:17:51ZReal-World Applications of Evolutionary Computing [electronic resource] : EvoWorkshops 2000: EvoIASP, EvoSCONDI, EvoTel, EvoSTIM, EvoRob, and EvoFlight Edinburgh, Scotland, UK, April 17, 2000 Proceedings / Cagnoni, Stefano. editor. SpringerLink (Online service) textBerlin, Heidelberg : Springer Berlin Heidelberg,2000.engThe increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems.EvoIASP Talks -- Special Purpose Image Convolution with Evolvable Hardware -- Stereoscopic Vision for a Humanoid Robot Using Genetic Programming -- A Faster Genetic Clustering Algorithm -- Scene Interpretation using Semantic Nets and Evolutionary Computation -- Evolutionary Wavelet Bases in Signal Spaces -- EvoIASP Posters -- Finding Golf Courses: The Ultra High Tech Approach -- Sound Localization for a Humanoid Robot by Means of Genetic Programming -- On the Scalability of Genetic Algorithms to Very Large-Scale Feature Selection -- Combining Evolutionary, Connectionist, and Fuzzy Classification Algorithms for Shape Analysis -- Experimental Determination of Drosophila Embryonic Coordinates by Genetic Algorithms, the Simplex Method, and Their Hybrid -- EvoSCONDI Papers -- A Genetic Algorithm with Local Search for Solving Job Problems -- Distributed Learning Control of Traffic Signals -- Time Series Prediction by Growing Lateral Delay Neural Networks -- Trajectory Controller Network and Its Design Automation through Evolutionary Computing -- Evolutionary Computation and Nonlinear Programming in Multi-model-robust Control Design -- Benchmarking Cost-Assignment Schemes for Multi-objective Evolutionary Algorithms -- Automatic Synthesis of Both the Topology and Parameters for a Controller for a Three-Lag Plant with a Five-Second Delay Using Genetic Programming -- Automatic Design of Multivariable QFT Control System via Evolutionary Computation -- Development of Power Transformer Thermal Models for Oil Temperature Prediction -- EvoTel Talks -- Automatic Validation of Protocol Interfaces Described in VHDL -- Evolutive Modeling of TCP/IP Network Traffic for Intrusion Detection -- Multimodal Performance Profiles on the Adaptive Distributed Database Management Problem -- Protocol Construction Using Genetic Search Techniques -- EvoTel Posters -- Prediction of Power Requirements for High-Speed Circuits -- A Communication Architecture for Multi-Agent Learning Systems -- EvoSTIM Papers -- An Ambulance Crew Rostering System -- A Systematic Investigation of GA Performance on Jobshop Scheduling Problems -- An Ant Algorithm with a New Pheromone Evaluation Rule for Total Tardiness Problems -- A New Genetic Representation and Common Cluster Crossover for Job Shop Scheduling Problems -- Optimising an Evolutionary Algorithm for Scheduling -- EvoRob Papers -- On-line Evolution of Control for a Four-Legged Robot Using Genetic Programming -- Optimized Collision Free Robot Move Statement Generation by the Evolutionary Software GLEAM -- Self-Adaptive Mutation in ZCS Controllers -- Using a Hybrid Evolutionary-A* Approach for Learning Reactive Behaviours -- EvoFlight Papers -- Supervised Evolutionary Methods in Aerodynamic Design Optimisation -- An Evolutionary Algorithm for Large Scale Set Covering Problems with Application to Airline Crew Scheduling -- Design, Implementation, and Application of a Tool for Optimal Aircraft Positioning.The increasingly active eld of Evolutionary Computation (EC) provides val- ble tools, inspired by the theory of natural selection and genetic inheritance, to problem solving, machine learning, and optimization in many real-world app- cations. Despite some early intuitions about EC, that can be dated back to the - vention of computers, and a better formal de nition of EC, made in the 1960s, the quest for real-world applications of EC only began in the late 1980s. The dramatic increase in computer performances in the last decade of the 20th c- tury gave rise to a positive feedback process: EC techniques became more and more applicable, stimulating the growth of interest in their study, and allowing, in turn, new powerful EC paradigms to be devised. In parallel with new theoretical results, the number of elds to which EC is being applied is increasing day by day, along with the complexity of applications and application domains. In particular, industrially relevant elds, such as signal and image processing, computer vision, pattern recognition, industrial control, telecommunication, scheduling and timetabling, and aerospace engineering are employing EC techniques to solve complex real-world problems.Computer science.Computer communication systems.Algorithms.Artificial intelligence.Image processing.Complexity, Computational.Computer Science.Artificial Intelligence (incl. Robotics).Algorithm Analysis and Problem Complexity.Computer Communication Networks.Image Processing and Computer Vision.Complexity.Springer eBookshttp://dx.doi.org/10.1007/3-540-45561-2URN:ISBN:9783540455615 |