The book describes the utility and efficiency of nature based algorithms in optimization, classification and simulation of natural resource management problems.The book deals with climate change, hydrology, renewable energy and natural ecosystems and tries to find solution to its common uncertainties so that proper mitigation steps can be undertaken to reduce both quantity and probability of such anomalies. The book aims to propose some methodologies which can help related engineers and planners to mitigate the common abnormalities that exist to derail the equilibrium of a natural ecosystem and its biotic as well as abiotic components.…mehr
The book describes the utility and efficiency of nature based algorithms in optimization, classification and simulation of natural resource management problems.The book deals with climate change, hydrology, renewable energy and natural ecosystems and tries to find solution to its common uncertainties so that proper mitigation steps can be undertaken to reduce both quantity and probability of such anomalies. The book aims to propose some methodologies which can help related engineers and planners to mitigate the common abnormalities that exist to derail the equilibrium of a natural ecosystem and its biotic as well as abiotic components.
Artikelnr. des Verlages: 86081761, 978-94-007-5151-4
2013
Seitenzahl: 360
Erscheinungstermin: 5. Juni 2013
Englisch
Abmessung: 241mm x 160mm x 24mm
Gewicht: 714g
ISBN-13: 9789400751514
ISBN-10: 9400751516
Artikelnr.: 36021985
Herstellerkennzeichnung
Books on Demand GmbH
In de Tarpen 42
22848 Norderstedt
info@bod.de
040 53433511
Autorenporträt
Mrinmoy Majumder is presently working as an Assistant Professor of School of Hydro-Informatics Engineering in National Institute of Technology Agartala,India.He has completed his PhD in 2010 from Jadavpur University. Presently he is doing his teaching and research on Hydro-informatics, Natural resource management and Nature based algorithms. He has published more than 25 papers in various national and international journals and has written 3 books. Rabindra Nath Barman is presently working as an Assistant Professor of Department of Production Engineering in National Institute of Technology Agartala,India. He has completed his PhD from Jadavpur University in the year of 2012.He is interested in fluid mechanics and water resource principles. He has published more than 25 papers in various national and international journals and has written a few book chapters.
Inhaltsangabe
From the Contents: Selection of Optimized Location for Eco-Parks with the help of Ant Colony Optimization.- Application of Hive Theory for identification of suitable habitats for Porcupines.- Tradeoff Analysis between Rainfall and Load Factor of a Small Scale Hydro Power Plant by Particle Swarm Optimization.- Application of Artificial Neural Network in Short Term Rainfall Forecasting.- Application of Genetic Algorithm for prediction of growth rate of Bufo Melanostictus in an Urban Forest.- Comparison of Nature Based Algorithms in Impact Analysis of Climate Change on Water Resources.- A Neuro-Fuzzy approach for selection of crops in vertical irrigation.- Comparison of Neuro-Fuzzy techniques in estimation of Extreme Events.- Comparison of Conceptual and Nature Based Models in prediction of subsurface flow.
From the Contents: Selection of Optimized Location for Eco-Parks with the help of Ant Colony Optimization.- Application of Hive Theory for identification of suitable habitats for Porcupines.- Tradeoff Analysis between Rainfall and Load Factor of a Small Scale Hydro Power Plant by Particle Swarm Optimization.- Application of Artificial Neural Network in Short Term Rainfall Forecasting.- Application of Genetic Algorithm for prediction of growth rate of Bufo Melanostictus in an Urban Forest.- Comparison of Nature Based Algorithms in Impact Analysis of Climate Change on Water Resources.- A Neuro-Fuzzy approach for selection of crops in vertical irrigation.- Comparison of Neuro-Fuzzy techniques in estimation of Extreme Events.- Comparison of Conceptual and Nature Based Models in prediction of subsurface flow.
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