| 000 | 05582nam a22006255i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-31153-1 | ||
| 003 | DE-He213 | ||
| 005 | 20240423125706.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 160324s2016 sz | s |||| 0|eng d | ||
| 020 |
_a9783319311531 _9978-3-319-31153-1 |
||
| 024 | 7 |
_a10.1007/978-3-319-31153-1 _2doi |
|
| 050 | 4 | _aQA76.9.A43 | |
| 072 | 7 |
_aUMB _2bicssc |
|
| 072 | 7 |
_aCOM051300 _2bisacsh |
|
| 072 | 7 |
_aUMB _2thema |
|
| 082 | 0 | 4 |
_a518.1 _223 |
| 245 | 1 | 0 |
_aApplications of Evolutionary Computation _h[electronic resource] : _b19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part II / _cedited by Giovanni Squillero, Paolo Burelli. |
| 250 | _a1st ed. 2016. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
| 300 |
_aXXVI, 329 p. 94 illus. _bonline resource. |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
||
| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aTheoretical Computer Science and General Issues, _x2512-2029 ; _v9598 |
|
| 505 | 0 | _aEvoNUM: Local Fitness Meta-Models with Nearest Neighbor Regression -- Validating the Grid Diversity Operator: an Infusion Technique for Diversity Maintenance in Population-Based Optimisation Algorithms -- Benchmarking Languages for Evolutionary Algorithms -- On the Closest Averaged Hausdorff Archive for a Circularly Convex Pareto Front -- Evolving Smoothing Kernels for Global Optimization -- EvoPAR: Implementing Parallel Differential Evolution on Spark -- ECJ+HADOOP: An Easy Way to Deploy Massive Runs of Evolutionary Algorithm -- Addressing High Dimensional Multi-Objective Optimization Problems by Coevolutionary Islands with Overlapping Search Spaces -- Compilable Phenotypes: Accelerating the Evaluation of Individuals in Grammatical Evolution -- GPU Accelerated Molecular Docking Simulation with Genetic Algorithms -- EvoRISK: Challenging Anti-virus Through Evolutionary Malware Obfuscation -- EvoROBOT: Leveraging Online Racing and Population Cloning in Evolutionary Multirobot Systems -- Multi-Agent Behavior-Based Policy Transfer -- On-line Evolution of Foraging Behaviour in a Population of Real Robots -- Hybrid Control for a Real Swarm Robotics System in an Intruder Detection Task -- EvoSTOC: Direct Memory Schemes for Population-Based Incremental Learning in Cyclically Changing Environments -- Simheuristics for the Multiobjective Nondeterministic Firefighter Problem in a Time-Constrained Setting -- Benchmarking Dynamic Three-Dimensional Bin Packing Problems Using Discrete-Event Simulation -- Genetic Programming Algorithms for Dynamic Environments -- A Memory-Based NSGA-II Algorithm for Dynamic Multi-Objective Optimization Problems -- Hybrid Dynamic Resampling Algorithms for Evolutionary Multi-objective Optimization of Invariant-Noise Problems. . | |
| 520 | _aThe two volumes LNCS 9597 and 9598 constitute the refereed conference proceedings of the 19th European Conference on the Applications of Evolutionary Computation, EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART. The 57 revised full papers presented together with 17 poster papers were carefully reviewed and selected from 115 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments). | ||
| 650 | 0 | _aAlgorithms. | |
| 650 | 0 | _aArtificial intelligence. | |
| 650 | 0 | _aApplication software. | |
| 650 | 0 | _aPattern recognition systems. | |
| 650 | 0 | _aData mining. | |
| 650 | 0 |
_aComputer science _xMathematics. |
|
| 650 | 1 | 4 | _aAlgorithms. |
| 650 | 2 | 4 | _aArtificial Intelligence. |
| 650 | 2 | 4 | _aComputer and Information Systems Applications. |
| 650 | 2 | 4 | _aAutomated Pattern Recognition. |
| 650 | 2 | 4 | _aData Mining and Knowledge Discovery. |
| 650 | 2 | 4 | _aMathematics of Computing. |
| 700 | 1 |
_aSquillero, Giovanni. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
| 700 | 1 |
_aBurelli, Paolo. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319311524 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319311548 |
| 830 | 0 |
_aTheoretical Computer Science and General Issues, _x2512-2029 ; _v9598 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-319-31153-1 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 912 | _aZDB-2-LNC | ||
| 942 | _cSPRINGER | ||
| 999 |
_c180700 _d180700 |
||