| 000 | 01359 a2200253 4500 | ||
|---|---|---|---|
| 001 | 9056990713 | ||
| 005 | 20250317100354.0 | ||
| 008 | 250312041998GB eng | ||
| 020 | _a9789056990718 | ||
| 037 |
_bTaylor & Francis _cGBP 55.99 _fBB |
||
| 040 | _a01 | ||
| 041 | _aeng | ||
| 072 | 7 |
_aRN _2thema |
|
| 072 | 7 |
_aRN _2bic |
|
| 072 | 7 |
_aARC008000 _2bisac |
|
| 072 | 7 |
_aSCI026000 _2bisac |
|
| 072 | 7 |
_a307.76 _2bisac |
|
| 100 | 1 | _aPeter M. Allen | |
| 245 | 1 | 0 |
_aCities and Regions as Self-Organizing Systems _bModels of Complexity |
| 250 | _a1 | ||
| 260 |
_aOxford _bRoutledge _c19980225 |
||
| 300 | _a296 p | ||
| 520 | _bA clear methodological and philosophical introduction to complexity theory as applied to urban and regional systems is given, together with a detailed series of modelling case studies compiled over the last couple of decades. Based on the new complex systems thinking, mathematical models are developed which attempt to simulate the evolution of towns, cities, and regions and the complicated co-evolutionary interaction there is both between and within them. The aim of these models is to help policy analysis and decision-making in urban and regional planning, energy policy, transport policy, and many other areas of service provision, infrastructure planning, and investment that are necessary for a successful society. | ||
| 999 |
_c476 _d476 |
||