Natural complexity :: a modeling handbook /
This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorati...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Princeton, NJ :
Princeton University Press,
[2017]
|
| Schriftenreihe: | Primers in complex systems.
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases. Natural Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. Ideal for undergraduates, beginning graduate students, and researchers in the physical and natural sciences, this unique handbook requires no advanced mathematical knowledge or programming skills and is suitable for self-learners with a working knowledge of precalculus and high-school physics. Self-contained and accessible, Natural Complexity enables readers to identify and quantify common underlying structural and dynamical patterns shared by the various systems and phenomena it examines, so that they can form their own answers to the questions of what natural complexity is and how it arises. |
| Beschreibung: | 1 online resource : illustrations |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9781400885497 1400885493 0691176841 9780691176840 0691170355 9780691170350 |
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| 100 | 1 | |a Charbonneau, Paul, |d 1961- |e author. |1 https://id.oclc.org/worldcat/entity/E39PBJrgJGhFxrKTHxhpGhy68C |0 http://id.loc.gov/authorities/names/no2013041497 | |
| 245 | 1 | 0 | |a Natural complexity : |b a modeling handbook / |c Paul Charbonneau. |
| 264 | 1 | |a Princeton, NJ : |b Princeton University Press, |c [2017] | |
| 300 | |a 1 online resource : |b illustrations | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
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| 490 | 1 | |a Primers in complex systems | |
| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | |a Part 1. What Is complexity?: Complexity Is not simple -- Randomness Is not complexity -- Chaos Is not complexity -- Open dissipative systems -- Natural complexity -- About the computer programs listed in this book -- Part 2. Iterated growth: Cellular automata in one spatial dimension -- Cellular automata in two spatial dimensions -- A zoo of 2-D structures from simple rules -- Agents, ants, and highways -- Emergent structures and behaviors -- Part 3. Aggregation: Diffusion-limited aggregation -- Numerical implementation -- A representative simulation -- A zoo of aggregates -- Fractal geometry -- Self-similarity and scale invariance -- Part 4. Percolation: Percolation in one dimension -- Percolation in two dimensions -- Cluster sizes -- Fractal clusters -- Is it really a power law? -- Criticality -- Part 5. Sandpiles: Model definition -- Numerical implementation -- A representative simulation -- Measuring avalanches -- Self-organized criticality -- Part 6. Forest fires: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Back to criticality -- The pros and cons of wildfire management -- Part 7. Traffic jams: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Traffic jams as avalanches -- Car traffic as a SOC system? -- Part 8. Earthquakes: The Burridge-Knopoff model -- Numerical implementation -- A representative simulation -- Model behavior -- Predicting real earthquakes -- Part 9. Epidemics: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Epidemic self-organization -- Small-world networks -- Part 10. Flocking -- Model definition -- Numerical implementation -- A behavioral zoo -- Segregation of active and passive flockers -- Why you should never panic -- Part 11. Pattern formation: Excitable systems -- The hodgepodge machine -- Numerical implementation -- Waves, spirals, spaghettis, and cells -- Spiraling out -- Spontaneous pattern formation -- Part 12. Epilogue: A hike on slickrock -- Johannes Kepler and the unity of nature -- From lichens to solar flares -- Emergence and natural order -- Into the abyss: your turn -- Part A. Basic elements of the Python programming language: Code structure -- Variables and arrays -- Operators -- Loop constructs -- Conditional constructs -- Input/output and graphics -- Part B. Probability density functions: A simple example -- Continuous PDFs -- Some mathematical properties of power-law PDFs -- Cumulative PDFs -- PDFs with logarithmic bin sizes -- Better fits to power-law PDFs -- Part C. Random Numbers and walks: Random deviates -- The classical random walk -- Random walk and diffusion -- Part D. Lattice computation: Nearest-neighbor templates -- Periodic boundary conditions -- Random walks on lattices. | |
| 520 | |a This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases. Natural Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. Ideal for undergraduates, beginning graduate students, and researchers in the physical and natural sciences, this unique handbook requires no advanced mathematical knowledge or programming skills and is suitable for self-learners with a working knowledge of precalculus and high-school physics. Self-contained and accessible, Natural Complexity enables readers to identify and quantify common underlying structural and dynamical patterns shared by the various systems and phenomena it examines, so that they can form their own answers to the questions of what natural complexity is and how it arises. | ||
| 546 | |a In English. | ||
| 650 | 0 | |a Complexity (Philosophy) |0 http://id.loc.gov/authorities/subjects/sh85029376 | |
| 650 | 0 | |a Physics |x Methodology. | |
| 650 | 0 | |a Computational complexity. |0 http://id.loc.gov/authorities/subjects/sh85029473 | |
| 650 | 0 | |a Biocomplexity. |0 http://id.loc.gov/authorities/subjects/sh2005001919 | |
| 650 | 6 | |a Complexité (Philosophie) | |
| 650 | 6 | |a Physique |x Méthodologie. | |
| 650 | 6 | |a Complexité de calcul (Informatique) | |
| 650 | 6 | |a Biocomplexité. | |
| 650 | 7 | |a SCIENCE |x Philosophy & Social Aspects. |2 bisacsh | |
| 650 | 7 | |a COMPUTERS |x Data Modeling & Design. |2 bisacsh | |
| 650 | 7 | |a Biocomplexity |2 fast | |
| 650 | 7 | |a Complexity (Philosophy) |2 fast | |
| 650 | 7 | |a Computational complexity |2 fast | |
| 650 | 7 | |a Physics |x Methodology |2 fast | |
| 653 | |a Burridge-Knopoff stick-slip model. | ||
| 653 | |a Gutenberg-Richter law. | ||
| 653 | |a Johannes Kepler. | ||
| 653 | |a Olami-Feder-Christensen model. | ||
| 653 | |a Python code. | ||
| 653 | |a accretion. | ||
| 653 | |a active flockers. | ||
| 653 | |a agents. | ||
| 653 | |a automobile traffic. | ||
| 653 | |a avalanches. | ||
| 653 | |a cells. | ||
| 653 | |a cellular automata. | ||
| 653 | |a chaos. | ||
| 653 | |a clusters. | ||
| 653 | |a complex behavior. | ||
| 653 | |a complex structure. | ||
| 653 | |a complex system. | ||
| 653 | |a complexity. | ||
| 653 | |a computational model. | ||
| 653 | |a computer program. | ||
| 653 | |a contagious diseases. | ||
| 653 | |a criticality. | ||
| 653 | |a diffusion-limited aggregation. | ||
| 653 | |a earthquake forecasting. | ||
| 653 | |a earthquakes. | ||
| 653 | |a emergence. | ||
| 653 | |a emergent behavior. | ||
| 653 | |a emergent structure. | ||
| 653 | |a epidemic spread. | ||
| 653 | |a epidemic surges. | ||
| 653 | |a excitable system. | ||
| 653 | |a flocking. | ||
| 653 | |a forest fires. | ||
| 653 | |a fractal clusters. | ||
| 653 | |a fractal geometry. | ||
| 653 | |a growth. | ||
| 653 | |a hodgepodge machine. | ||
| 653 | |a infection rate. | ||
| 653 | |a iterated growth. | ||
| 653 | |a lattice. | ||
| 653 | |a lichens. | ||
| 653 | |a natural complex system. | ||
| 653 | |a natural complexity. | ||
| 653 | |a natural order. | ||
| 653 | |a natural phenomena. | ||
| 653 | |a nature. | ||
| 653 | |a open dissipative system. | ||
| 653 | |a panic. | ||
| 653 | |a passive flockers. | ||
| 653 | |a pattern formation. | ||
| 653 | |a percolation threshold. | ||
| 653 | |a percolation. | ||
| 653 | |a phase transition. | ||
| 653 | |a planetary motion. | ||
| 653 | |a power-law. | ||
| 653 | |a random walk. | ||
| 653 | |a randomness. | ||
| 653 | |a repulsion. | ||
| 653 | |a rule-based growth. | ||
| 653 | |a sandpile. | ||
| 653 | |a scale invariance. | ||
| 653 | |a segregation. | ||
| 653 | |a self-organization. | ||
| 653 | |a self-organized criticality. | ||
| 653 | |a self-propulsion. | ||
| 653 | |a self-similarity. | ||
| 653 | |a simple rules. | ||
| 653 | |a small-world network. | ||
| 653 | |a solar flares. | ||
| 653 | |a spaghetti. | ||
| 653 | |a spatiotemporal pattern. | ||
| 653 | |a spiral. | ||
| 653 | |a tagging algorithm. | ||
| 653 | |a traffic jams. | ||
| 653 | |a waves. | ||
| 653 | |a wildfire management. | ||
| 655 | 4 | |a Electronic book. | |
| 758 | |i has work: |a Natural complexity (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFr3c6V4Yy7gHWQVCPbtGb |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |z 9780691176840 |w (OCoLC)962351906 |
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| 830 | 0 | |a Primers in complex systems. |0 http://id.loc.gov/authorities/names/no2009118210 | |
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| adam_text | |
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| author | Charbonneau, Paul, 1961- |
| author_GND | http://id.loc.gov/authorities/names/no2013041497 |
| author_facet | Charbonneau, Paul, 1961- |
| author_role | aut |
| author_sort | Charbonneau, Paul, 1961- |
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| callnumber-first | Q - Science |
| callnumber-label | Q175 |
| callnumber-raw | Q175.32.C65 C43 2017 |
| callnumber-search | Q175.32.C65 C43 2017 |
| callnumber-sort | Q 3175.32 C65 C43 42017 |
| callnumber-subject | Q - General Science |
| collection | ZDB-4-EBA |
| contents | Part 1. What Is complexity?: Complexity Is not simple -- Randomness Is not complexity -- Chaos Is not complexity -- Open dissipative systems -- Natural complexity -- About the computer programs listed in this book -- Part 2. Iterated growth: Cellular automata in one spatial dimension -- Cellular automata in two spatial dimensions -- A zoo of 2-D structures from simple rules -- Agents, ants, and highways -- Emergent structures and behaviors -- Part 3. Aggregation: Diffusion-limited aggregation -- Numerical implementation -- A representative simulation -- A zoo of aggregates -- Fractal geometry -- Self-similarity and scale invariance -- Part 4. Percolation: Percolation in one dimension -- Percolation in two dimensions -- Cluster sizes -- Fractal clusters -- Is it really a power law? -- Criticality -- Part 5. Sandpiles: Model definition -- Numerical implementation -- A representative simulation -- Measuring avalanches -- Self-organized criticality -- Part 6. Forest fires: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Back to criticality -- The pros and cons of wildfire management -- Part 7. Traffic jams: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Traffic jams as avalanches -- Car traffic as a SOC system? -- Part 8. Earthquakes: The Burridge-Knopoff model -- Numerical implementation -- A representative simulation -- Model behavior -- Predicting real earthquakes -- Part 9. Epidemics: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Epidemic self-organization -- Small-world networks -- Part 10. Flocking -- Model definition -- Numerical implementation -- A behavioral zoo -- Segregation of active and passive flockers -- Why you should never panic -- Part 11. Pattern formation: Excitable systems -- The hodgepodge machine -- Numerical implementation -- Waves, spirals, spaghettis, and cells -- Spiraling out -- Spontaneous pattern formation -- Part 12. Epilogue: A hike on slickrock -- Johannes Kepler and the unity of nature -- From lichens to solar flares -- Emergence and natural order -- Into the abyss: your turn -- Part A. Basic elements of the Python programming language: Code structure -- Variables and arrays -- Operators -- Loop constructs -- Conditional constructs -- Input/output and graphics -- Part B. Probability density functions: A simple example -- Continuous PDFs -- Some mathematical properties of power-law PDFs -- Cumulative PDFs -- PDFs with logarithmic bin sizes -- Better fits to power-law PDFs -- Part C. Random Numbers and walks: Random deviates -- The classical random walk -- Random walk and diffusion -- Part D. Lattice computation: Nearest-neighbor templates -- Periodic boundary conditions -- Random walks on lattices. |
| ctrlnum | (OCoLC)980848243 |
| dewey-full | 501 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 501 - Philosophy and theory |
| dewey-raw | 501 |
| dewey-search | 501 |
| dewey-sort | 3501 |
| dewey-tens | 500 - Natural sciences and mathematics |
| discipline | Allgemeine Naturwissenschaft |
| format | Electronic eBook |
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What Is complexity?: Complexity Is not simple -- Randomness Is not complexity -- Chaos Is not complexity -- Open dissipative systems -- Natural complexity -- About the computer programs listed in this book -- Part 2. Iterated growth: Cellular automata in one spatial dimension -- Cellular automata in two spatial dimensions -- A zoo of 2-D structures from simple rules -- Agents, ants, and highways -- Emergent structures and behaviors -- Part 3. Aggregation: Diffusion-limited aggregation -- Numerical implementation -- A representative simulation -- A zoo of aggregates -- Fractal geometry -- Self-similarity and scale invariance -- Part 4. Percolation: Percolation in one dimension -- Percolation in two dimensions -- Cluster sizes -- Fractal clusters -- Is it really a power law? -- Criticality -- Part 5. Sandpiles: Model definition -- Numerical implementation -- A representative simulation -- Measuring avalanches -- Self-organized criticality -- Part 6. Forest fires: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Back to criticality -- The pros and cons of wildfire management -- Part 7. Traffic jams: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Traffic jams as avalanches -- Car traffic as a SOC system? -- Part 8. Earthquakes: The Burridge-Knopoff model -- Numerical implementation -- A representative simulation -- Model behavior -- Predicting real earthquakes -- Part 9. Epidemics: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Epidemic self-organization -- Small-world networks -- Part 10. Flocking -- Model definition -- Numerical implementation -- A behavioral zoo -- Segregation of active and passive flockers -- Why you should never panic -- Part 11. Pattern formation: Excitable systems -- The hodgepodge machine -- Numerical implementation -- Waves, spirals, spaghettis, and cells -- Spiraling out -- Spontaneous pattern formation -- Part 12. Epilogue: A hike on slickrock -- Johannes Kepler and the unity of nature -- From lichens to solar flares -- Emergence and natural order -- Into the abyss: your turn -- Part A. Basic elements of the Python programming language: Code structure -- Variables and arrays -- Operators -- Loop constructs -- Conditional constructs -- Input/output and graphics -- Part B. Probability density functions: A simple example -- Continuous PDFs -- Some mathematical properties of power-law PDFs -- Cumulative PDFs -- PDFs with logarithmic bin sizes -- Better fits to power-law PDFs -- Part C. Random Numbers and walks: Random deviates -- The classical random walk -- Random walk and diffusion -- Part D. Lattice computation: Nearest-neighbor templates -- Periodic boundary conditions -- Random walks on lattices.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases. Natural Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. Ideal for undergraduates, beginning graduate students, and researchers in the physical and natural sciences, this unique handbook requires no advanced mathematical knowledge or programming skills and is suitable for self-learners with a working knowledge of precalculus and high-school physics. 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| genre | Electronic book. |
| genre_facet | Electronic book. |
| id | ZDB-4-EBA-ocn980848243 |
| illustrated | Illustrated |
| indexdate | 2024-11-27T13:27:46Z |
| institution | BVB |
| isbn | 9781400885497 1400885493 0691176841 9780691176840 0691170355 9780691170350 |
| language | English |
| lccn | 2016953537 |
| oclc_num | 980848243 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource : illustrations |
| psigel | ZDB-4-EBA |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | Princeton University Press, |
| record_format | marc |
| series | Primers in complex systems. |
| series2 | Primers in complex systems |
| spelling | Charbonneau, Paul, 1961- author. https://id.oclc.org/worldcat/entity/E39PBJrgJGhFxrKTHxhpGhy68C http://id.loc.gov/authorities/names/no2013041497 Natural complexity : a modeling handbook / Paul Charbonneau. Princeton, NJ : Princeton University Press, [2017] 1 online resource : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Primers in complex systems Includes bibliographical references and index. Print version record. Part 1. What Is complexity?: Complexity Is not simple -- Randomness Is not complexity -- Chaos Is not complexity -- Open dissipative systems -- Natural complexity -- About the computer programs listed in this book -- Part 2. Iterated growth: Cellular automata in one spatial dimension -- Cellular automata in two spatial dimensions -- A zoo of 2-D structures from simple rules -- Agents, ants, and highways -- Emergent structures and behaviors -- Part 3. Aggregation: Diffusion-limited aggregation -- Numerical implementation -- A representative simulation -- A zoo of aggregates -- Fractal geometry -- Self-similarity and scale invariance -- Part 4. Percolation: Percolation in one dimension -- Percolation in two dimensions -- Cluster sizes -- Fractal clusters -- Is it really a power law? -- Criticality -- Part 5. Sandpiles: Model definition -- Numerical implementation -- A representative simulation -- Measuring avalanches -- Self-organized criticality -- Part 6. Forest fires: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Back to criticality -- The pros and cons of wildfire management -- Part 7. Traffic jams: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Traffic jams as avalanches -- Car traffic as a SOC system? -- Part 8. Earthquakes: The Burridge-Knopoff model -- Numerical implementation -- A representative simulation -- Model behavior -- Predicting real earthquakes -- Part 9. Epidemics: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Epidemic self-organization -- Small-world networks -- Part 10. Flocking -- Model definition -- Numerical implementation -- A behavioral zoo -- Segregation of active and passive flockers -- Why you should never panic -- Part 11. Pattern formation: Excitable systems -- The hodgepodge machine -- Numerical implementation -- Waves, spirals, spaghettis, and cells -- Spiraling out -- Spontaneous pattern formation -- Part 12. Epilogue: A hike on slickrock -- Johannes Kepler and the unity of nature -- From lichens to solar flares -- Emergence and natural order -- Into the abyss: your turn -- Part A. Basic elements of the Python programming language: Code structure -- Variables and arrays -- Operators -- Loop constructs -- Conditional constructs -- Input/output and graphics -- Part B. Probability density functions: A simple example -- Continuous PDFs -- Some mathematical properties of power-law PDFs -- Cumulative PDFs -- PDFs with logarithmic bin sizes -- Better fits to power-law PDFs -- Part C. Random Numbers and walks: Random deviates -- The classical random walk -- Random walk and diffusion -- Part D. Lattice computation: Nearest-neighbor templates -- Periodic boundary conditions -- Random walks on lattices. This book provides a short, hands-on introduction to the science of complexity using simple computational models of natural complex systems--with models and exercises drawn from physics, chemistry, geology, and biology. By working through the models and engaging in additional computational explorations suggested at the end of each chapter, readers very quickly develop an understanding of how complex structures and behaviors can emerge in natural phenomena as diverse as avalanches, forest fires, earthquakes, chemical reactions, animal flocks, and epidemic diseases. Natural Complexity provides the necessary topical background, complete source codes in Python, and detailed explanations for all computational models. Ideal for undergraduates, beginning graduate students, and researchers in the physical and natural sciences, this unique handbook requires no advanced mathematical knowledge or programming skills and is suitable for self-learners with a working knowledge of precalculus and high-school physics. Self-contained and accessible, Natural Complexity enables readers to identify and quantify common underlying structural and dynamical patterns shared by the various systems and phenomena it examines, so that they can form their own answers to the questions of what natural complexity is and how it arises. In English. Complexity (Philosophy) http://id.loc.gov/authorities/subjects/sh85029376 Physics Methodology. Computational complexity. http://id.loc.gov/authorities/subjects/sh85029473 Biocomplexity. http://id.loc.gov/authorities/subjects/sh2005001919 Complexité (Philosophie) Physique Méthodologie. Complexité de calcul (Informatique) Biocomplexité. SCIENCE Philosophy & Social Aspects. bisacsh COMPUTERS Data Modeling & Design. bisacsh Biocomplexity fast Complexity (Philosophy) fast Computational complexity fast Physics Methodology fast Burridge-Knopoff stick-slip model. Gutenberg-Richter law. Johannes Kepler. Olami-Feder-Christensen model. Python code. accretion. active flockers. agents. automobile traffic. avalanches. cells. cellular automata. chaos. clusters. complex behavior. complex structure. complex system. complexity. computational model. computer program. contagious diseases. criticality. diffusion-limited aggregation. earthquake forecasting. earthquakes. emergence. emergent behavior. emergent structure. epidemic spread. epidemic surges. excitable system. flocking. forest fires. fractal clusters. fractal geometry. growth. hodgepodge machine. infection rate. iterated growth. lattice. lichens. natural complex system. natural complexity. natural order. natural phenomena. nature. open dissipative system. panic. passive flockers. pattern formation. percolation threshold. percolation. phase transition. planetary motion. power-law. random walk. randomness. repulsion. rule-based growth. sandpile. scale invariance. segregation. self-organization. self-organized criticality. self-propulsion. self-similarity. simple rules. small-world network. solar flares. spaghetti. spatiotemporal pattern. spiral. tagging algorithm. traffic jams. waves. wildfire management. Electronic book. has work: Natural complexity (Text) https://id.oclc.org/worldcat/entity/E39PCFr3c6V4Yy7gHWQVCPbtGb https://id.oclc.org/worldcat/ontology/hasWork Print version: 9780691176840 (OCoLC)962351906 Print version: Druck-Ausgabe, Hbk. 9780691176840 Print version: Druck-Ausgabe, Pbk. 9780691170350 Primers in complex systems. http://id.loc.gov/authorities/names/no2009118210 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1431859 Volltext |
| spellingShingle | Charbonneau, Paul, 1961- Natural complexity : a modeling handbook / Primers in complex systems. Part 1. What Is complexity?: Complexity Is not simple -- Randomness Is not complexity -- Chaos Is not complexity -- Open dissipative systems -- Natural complexity -- About the computer programs listed in this book -- Part 2. Iterated growth: Cellular automata in one spatial dimension -- Cellular automata in two spatial dimensions -- A zoo of 2-D structures from simple rules -- Agents, ants, and highways -- Emergent structures and behaviors -- Part 3. Aggregation: Diffusion-limited aggregation -- Numerical implementation -- A representative simulation -- A zoo of aggregates -- Fractal geometry -- Self-similarity and scale invariance -- Part 4. Percolation: Percolation in one dimension -- Percolation in two dimensions -- Cluster sizes -- Fractal clusters -- Is it really a power law? -- Criticality -- Part 5. Sandpiles: Model definition -- Numerical implementation -- A representative simulation -- Measuring avalanches -- Self-organized criticality -- Part 6. Forest fires: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Back to criticality -- The pros and cons of wildfire management -- Part 7. Traffic jams: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Traffic jams as avalanches -- Car traffic as a SOC system? -- Part 8. Earthquakes: The Burridge-Knopoff model -- Numerical implementation -- A representative simulation -- Model behavior -- Predicting real earthquakes -- Part 9. Epidemics: Model definition -- Numerical implementation -- A representative simulation -- Model behavior -- Epidemic self-organization -- Small-world networks -- Part 10. Flocking -- Model definition -- Numerical implementation -- A behavioral zoo -- Segregation of active and passive flockers -- Why you should never panic -- Part 11. Pattern formation: Excitable systems -- The hodgepodge machine -- Numerical implementation -- Waves, spirals, spaghettis, and cells -- Spiraling out -- Spontaneous pattern formation -- Part 12. Epilogue: A hike on slickrock -- Johannes Kepler and the unity of nature -- From lichens to solar flares -- Emergence and natural order -- Into the abyss: your turn -- Part A. Basic elements of the Python programming language: Code structure -- Variables and arrays -- Operators -- Loop constructs -- Conditional constructs -- Input/output and graphics -- Part B. Probability density functions: A simple example -- Continuous PDFs -- Some mathematical properties of power-law PDFs -- Cumulative PDFs -- PDFs with logarithmic bin sizes -- Better fits to power-law PDFs -- Part C. Random Numbers and walks: Random deviates -- The classical random walk -- Random walk and diffusion -- Part D. Lattice computation: Nearest-neighbor templates -- Periodic boundary conditions -- Random walks on lattices. Complexity (Philosophy) http://id.loc.gov/authorities/subjects/sh85029376 Physics Methodology. Computational complexity. http://id.loc.gov/authorities/subjects/sh85029473 Biocomplexity. http://id.loc.gov/authorities/subjects/sh2005001919 Complexité (Philosophie) Physique Méthodologie. Complexité de calcul (Informatique) Biocomplexité. SCIENCE Philosophy & Social Aspects. bisacsh COMPUTERS Data Modeling & Design. bisacsh Biocomplexity fast Complexity (Philosophy) fast Computational complexity fast Physics Methodology fast |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85029376 http://id.loc.gov/authorities/subjects/sh85029473 http://id.loc.gov/authorities/subjects/sh2005001919 |
| title | Natural complexity : a modeling handbook / |
| title_auth | Natural complexity : a modeling handbook / |
| title_exact_search | Natural complexity : a modeling handbook / |
| title_full | Natural complexity : a modeling handbook / Paul Charbonneau. |
| title_fullStr | Natural complexity : a modeling handbook / Paul Charbonneau. |
| title_full_unstemmed | Natural complexity : a modeling handbook / Paul Charbonneau. |
| title_short | Natural complexity : |
| title_sort | natural complexity a modeling handbook |
| title_sub | a modeling handbook / |
| topic | Complexity (Philosophy) http://id.loc.gov/authorities/subjects/sh85029376 Physics Methodology. Computational complexity. http://id.loc.gov/authorities/subjects/sh85029473 Biocomplexity. http://id.loc.gov/authorities/subjects/sh2005001919 Complexité (Philosophie) Physique Méthodologie. Complexité de calcul (Informatique) Biocomplexité. SCIENCE Philosophy & Social Aspects. bisacsh COMPUTERS Data Modeling & Design. bisacsh Biocomplexity fast Complexity (Philosophy) fast Computational complexity fast Physics Methodology fast |
| topic_facet | Complexity (Philosophy) Physics Methodology. Computational complexity. Biocomplexity. Complexité (Philosophie) Physique Méthodologie. Complexité de calcul (Informatique) Biocomplexité. SCIENCE Philosophy & Social Aspects. COMPUTERS Data Modeling & Design. Biocomplexity Computational complexity Physics Methodology Electronic book. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=1431859 |
| work_keys_str_mv | AT charbonneaupaul naturalcomplexityamodelinghandbook |