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1. |
Record Nr. |
UNINA9910799493403321 |
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Autore |
Hazrat Roozbeh |
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Titolo |
A Course in Python [[electronic resource] ] : The Core of the Language / / by Roozbeh Hazrat |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (255 pages) |
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Collana |
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Springer Undergraduate Mathematics Series, , 2197-4144 |
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Disciplina |
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Soggetti |
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Computer software |
Algorithms |
Mathematics |
Python (Llenguatge de programació) |
Mathematical Software |
General Mathematics |
Llibres electrònics |
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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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1 Basics of Python -- 2 Lists and Tuples -- 3 Decisions and Repetitions -- 4 Functions -- 5 List Comprehension and Generators -- 6 The sympy Library -- 7 The numpy Library -- 8 The matplotlib Library and Projects. |
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Sommario/riassunto |
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This textbook introduces Python and its programming through a multitude of clearly presented examples and worked-out exercises. Based on a course taught to undergraduate students of mathematics, science, engineering and finance, the book includes chapters on handling data, calculus, solving equations, and graphics, thus covering all of the basic topics in Python. Each section starts with a description of a new topic and some basic examples. The author then demonstrates the new concepts through worked out exercises. The intention is to enable the reader to learn from the codes, thus avoiding lengthy, exhausting explanations. With its strong focus on programming and problem solving, and an emphasis on numerical problems that do not require advanced mathematics, this textbook is also ideal for self-study, for instance for researchers who wish to use |
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Python as a computational tool. |
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2. |
Record Nr. |
UNINA9910338246303321 |
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Autore |
Yang Xin-She |
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Titolo |
Mathematical Foundations of Nature-Inspired Algorithms / / by Xin-She Yang, Xing-Shi He |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (114 pages) |
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Collana |
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SpringerBriefs in Optimization, , 2190-8354 |
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Disciplina |
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Soggetti |
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Mathematical optimization |
Numerical analysis |
Markov processes |
Algorithms |
Optimization |
Numerical Analysis |
Markov model |
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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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1 Introduction to Optimization -- 2 Nature-Inspired Algorithms -- 3 Mathematical Foundations -- 4 Mathematical Analysis I -- 5 Mathematical Analysis II. |
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Sommario/riassunto |
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This book presents a systematic approach to analyze nature-inspired algorithms. Beginning with an introduction to optimization methods and algorithms, this book moves on to provide a unified framework of mathematical analysis for convergence and stability. Specific nature-inspired algorithms include: swarm intelligence, ant colony optimization, particle swarm optimization, bee-inspired algorithms, bat algorithm, firefly algorithm, and cuckoo search. Algorithms are analyzed from a wide spectrum of theories and frameworks to offer insight to the main characteristics of algorithms and understand how |
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and why they work for solving optimization problems. In-depth mathematical analyses are carried out for different perspectives, including complexity theory, fixed point theory, dynamical systems, self-organization, Bayesian framework, Markov chain framework, filter theory, statistical learning, and statistical measures. Students and researchers in optimization, operations research, artificial intelligence, data mining, machine learning, computer science, and management sciences will see the pros and cons of a variety of algorithms through detailed examples and a comparison of algorithms. |
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