Resources, Environment and Engineering by Xie, Liquan PDF

By Xie, Liquan

ISBN-10: 1138027022

ISBN-13: 9781138027022

ISBN-10: 1315738317

ISBN-13: 9781315738314

Resources, setting and Engineering includes sixty six technical papers from the 2014 Technical Congress on assets, surroundings and Engineering (CREE 2014, Hong Kong, 6-7 September 2014, together with the 4th Technical convention on Chemical Engineering, CCE 2014). The contributions evaluate fresh technological advances within the fields of assets and the surroundings, and exhibit the advancements happening within the parts of assets, environmental security and linked engineering practice.

The e-book covers quite a lot of subject matters, including:
• Water assets and management
• city wastewater and finished therapy techniques
• nutrients defense and probability management
• protection engineering and environmental toxins control
• Biotechnology and meals engineering
• Civil and hydraulic engineering
• Oil and gasoline engineering
• Mining engineering
• Chemical engineering
• different matters on the topic of the safety and development of assets and environments

Resources, setting and Engineering can be priceless to lecturers and pros in either source and environmental engineering.

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Extra resources for Resources, Environment and Engineering

Sample text

Program. 71(2): 179–194. , Sorooshian, S. & Gupta, V. 1992. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resour. Res. 28(4): 1015–1031. K. & Sorooshina, S. 1993. Shuffled complex evolution approach for effective and efficient global minimization. J. Optimiz. Theory App. 76(3): 501–521. , Sorooshian, S. K. 1994. Optimal use of the SCE–UA global optimization method for calibrating watershed models. J. Hydrol. 158(3): 265–284. C. & Shi, Y. 2004. Guest editorial on special issue on particle swarm optimization.

750 8 19 14 18 8 17 10 8 8 12 Ten runs were made with different randomly generated initial parameter values. Table 2 shows the best points in each of the 10 runs and their associated objective function values (ξ ) and iteration numbers (J ). From Table 2, it can be concluded that: (1) The optimal parameter values calibrated from different initial values are stable, which indicates that the parameter calibration results are not influenced by different initial values. (2) All of the ten runs can find the global optima without producing unrelated local optimal values.

Swarm Intelligence. Morgan Kaufmann, San Francisco, USA. Lingireddy, S. 1998.  Civil Eng.  15(2):125–144. L. H. 2011. Study of the Xinanjiang model parameter calibration. J. Hydrol. Eng. 18(11): 1513–1521. A. & Mead, R. 1965. A simplex method for function minimization. Computer J. 7(4):308–313. D. 1964. An efficient method for finding the minimum of a function of several variables without calculating derivatives. The Comp. J. 7(2):155–162. H. 1960. An automatic method of finding the greatest of least value of a Function.

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Resources, Environment and Engineering by Xie, Liquan

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