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Record Nr. |
UNINA9910695350903321 |
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Autore |
Knecht William |
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Titolo |
Pilot willingness to take off into marginal weather [[electronic resource] ] : final report / / William Knecht |
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Pubbl/distr/stampa |
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Washington, DC : , : Office of Aerospace Medicine, Federal Aviation Administration |
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Ft. Belvior, VA : , : Available through the Defense Technical Information Center |
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Springfield, VA : , : National Technical Information Service, , 2005 |
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Descrizione fisica |
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i, 9, 1, 3 pages : digital, PDF file |
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Soggetti |
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Meteorology in aeronautics |
Air pilots - Psychology |
Logistic regression analysis - Data processing |
Risk assessment |
Statistics. |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Title from title screen (viewed on Oct. 10, 2006). |
"August 2005." |
"DOT/FAA/AM-05/15." |
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Nota di bibliografia |
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Includes bibliographic references (page 7). |
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Nota di contenuto |
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Pt. 2, Antecedent overfitting with forward stepwise logistic regression |
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2. |
Record Nr. |
UNINA9910984694803321 |
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Autore |
Singh Hemant |
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Titolo |
Evolutionary Multi-Criterion Optimization : 13th International Conference, EMO 2025, Canberra, ACT, Australia, March 4–7, 2025, Proceedings, Part I / / edited by Hemant Singh, Tapabrata Ray, Joshua Knowles, Xiaodong Li, Juergen Branke, Bing Wang, Akira Oyama |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (498 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 15512 |
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Altri autori (Persone) |
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RayTapabrata |
KnowlesJoshua |
LiXiaodong |
BrankeJuergen |
WangBing |
OyamaAkira |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- Algorithm design. -- Towards an Efficient Innovation Path Seeking Algorithm Using Directed Domination. -- An MaOEA/Local Search Hybrid Based on a Fast, Stochastic BFGS Using Achievement Scalarizing Search Directions. -- Selective evaluations for expediting multi-objective bilevel optimization. -- MOAISDX: A New Multi-objective Artificial Immune System based on Decomposition. -- PAES-25: Local Search, Archiving and Multi/Many-objective PseudoBoolean Functions. -- Weights-Guided Random Bit Climber for Binary Many-objective Optimization. -- Bilevel Optimization-based Decomposition for Solving Single and Multi objective Optimization Problems. -- A Study on Optimistic & Pessimistic Pareto-fronts in Multi objective Bilevel Optimization via ?-Perturbation. -- Cumulative Step Size Adaptation for Adaptive SEMO in Integer Space. -- Adaptive Normal-Boundary Intersection Directions for Evolutionary Many objective Optimization |
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with Complex Pareto Fronts. -- Encodings for Multi-Objective Free-Form Coverage Path Planning. -- VBEA: Voting-Based Evolutionary Algorithm for Multi-Objective Planning. -- Enhancing NSGA-II with a Knee Point for Constrained Multi-objective Optimization. -- Benchmarking. -- Single and Multi-Objective Optimization Benchmark Problems Focusing on Human-Powered Aircraft Design. -- An Extension of the Welded Beam Problem that Includes Multiple Interactng Design Concepts. -- Extended Results on Analytical Hypervolume Indicator Calculation of Linear and Quadratic Pareto Fronts. -- MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOH profiler. -- Applications. -- Multi-Objective Sequential Decision Making for Holistic Supply Chain Optimization. -- Interactive evolutionary re optimization for ground fish survey planning. -- A Multi-Objective Competitive Co-Evolutionary Framework with Progressive Shrinking for Wargame Scenarios. -- -- Impact of Environmental Changes on Optimized Robotics Collective Motion for Multi-Objective Coverage Tasks. |
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Sommario/riassunto |
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This two-volume set LNCS 15512-15513 constitutes the proceedings of the 13th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2025, held in Canberra, ACT, Australia, in March 2025. The 38 full papers and 2 extended abstracts presented in this book were carefully reviewed and selected from 63 submissions. The papers are divided into the following topical sections: Part I : Algorithm design; Benchmarking; Applications. Part II : Algorithm analysis; Surrogates and machine learning; Multi-criteria decision support. |
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