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1. |
Record Nr. |
UNINA9910155081403321 |
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Autore |
Hoffs Gill |
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Titolo |
The lost story of the William and Mary : the cowardice of captain Stinson / / Gill Hoffs |
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Pubbl/distr/stampa |
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Barnsley, [England] : , : Pen & Sword History, , 2016 |
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©2016 |
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ISBN |
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1-4738-5827-5 |
1-4738-5826-7 |
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Descrizione fisica |
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1 online resource (147 pages) : illustrations |
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Disciplina |
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Soggetti |
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Shipwrecks - Bahamas |
Atlantic Ocean |
Arctic Ocean |
Bahamas |
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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 bibliografia |
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Includes bibliographical references. |
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Sommario/riassunto |
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The emigrant ship William and Mary departed from Liverpool with 208 British, Irish, and Dutch emigrants in early 1853. Captained by young American Timothy Stinson, the vessel was sailing for New Orleans when the ship wrecked in the Bahamas in mysterious circumstances. Instead of grounding the ship on a nearby shore or building rafts for the passengers, Stinson and the majority of his crew sneaked away in lifeboats - murdering at least two of the emigrants with a hatchet as they did so - and reported the ship sunk with all on board lost. But the passengers kept the ship afloat and two days later were rescued by heroic wreckers as the ship went down. Now, over 160 years on, the tale of the two murdered in Bahamian waters and the hundreds who escaped thanks to kindly wreckers can finally be told. Stinson is no longer getting away with murder. |
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2. |
Record Nr. |
UNINA9910874692003321 |
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Autore |
Li Changhe |
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Titolo |
Intelligent Optimization : Principles, Algorithms and Applications / / by Changhe Li, Shoufei Han, Sanyou Zeng, Shengxiang Yang |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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9789819732869 |
9789819732852 |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (369 pages) |
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Altri autori (Persone) |
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HanShoufei |
ZengSanyou |
YangShengxiang |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Algorithms |
Mathematical optimization |
Computational intelligence |
Artificial Intelligence |
Design and Analysis of Algorithms |
Continuous Optimization |
Computational 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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chapter 1 Introduction -- chapter 2 Fundamentals -- chapter 3 Canonical Optimization Algorithms -- chapter 4 Basics of Evolutionary Computation Algorithms -- chapter 5 Popular Evolutionary Computation Algorithms -- chapter 6 Parameter Control and Policy Control -- chapter 7 Exploitation versus Exploration -- chapter 8 Multi-modal Optimization -- chapter 9 Multi-objective Optimization -- chapter 10 Constrained Optimization -- chapter 11 Dynamic Optimization.-chapter 12 Robust Optimization.-Chapter 13 Large-scale Global Optimization.-Chapter 14 Expensive Optimization -- Chapter 15 Real-world Applications. |
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Sommario/riassunto |
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This textbook comprehensively explores the foundational principles, algorithms, and applications of intelligent optimization, making it an |
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ideal resource for both undergraduate and postgraduate artificial intelligence courses. It remains equally valuable for active researchers and individuals engaged in self-study. Serving as a significant reference, it delves into advanced topics within the evolutionary computation field, including multi-objective optimization, dynamic optimization, constrained optimization, robust optimization, expensive optimization, and other pivotal scientific studies related to optimization. Designed to be approachable and inclusive, this textbook equips readers with the essential mathematical background necessary for understanding intelligent optimization. It employs an accessible writing style, complemented by extensive pseudo-code and diagrams that vividly illustrate the mechanisms, principles, and algorithms of optimization. With a focus on practicality, this textbook provides diverse real-world application examples spanning engineering, games, logistics, and other domains, enabling readers to confidently apply intelligent techniques to actual optimization problems. Recognizing the importance of hands-on experience, the textbook introduces the Open-source Framework for Evolutionary Computation platform (OFEC) as a user-friendly tool. This platform serves as a comprehensive toolkit for implementing, evaluating, visualizing, and benchmarking various optimization algorithms. The book guides readers on maximizing the utility of OFEC for conducting experiments and analyses in the field of evolutionary computation, facilitating a deeper understanding of intelligent optimization through practical application. |
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