Application of Fuzzy Logic in Water Resources Engineering

Application of Fuzzy Logic in Water Resources Engineering PDF Author: Ishtiyaq Ahmad
Publisher: LAP Lambert Academic Publishing
ISBN: 9783847305415
Category :
Languages : en
Pages : 72

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Book Description
India is bestowed with rich water resources; rainfall is one of the main sources of water. Because of time and spatial variability of rainfall, a number of dams have been constructed all over the country to tap the available water resources so that this water can be utilized in accordance with the requirements of mankind. Proper management of the reservoirs is required for the efficient use of available water resources. Reservoir operation plays a vital role in planning and management of water resources system. Modeling of a rainfall-runoff is gaining a fast momentum for hydrological and water management studies. This evolution provides the mankind with new possibilities to efficiently use the available water. In this study rainfall-runoff model for three reservoirs, namely Ravishankar Sagar, Murumsilli and Dudhawa reservoirs of MRP Project has been developed, for the available data of 17 years, by the application of fuzzy logic. Fuzzified runoff results from the model are compared with linear regression by calculating the relative error with reference to the observed runoff. It has been found that fuzzy logic based rainfall-runoff model performs better than linear regression model

Application of Fuzzy Logic in Water Resources Engineering

Application of Fuzzy Logic in Water Resources Engineering PDF Author: Ishtiyaq Ahmad
Publisher: LAP Lambert Academic Publishing
ISBN: 9783847305415
Category :
Languages : en
Pages : 72

Get Book Here

Book Description
India is bestowed with rich water resources; rainfall is one of the main sources of water. Because of time and spatial variability of rainfall, a number of dams have been constructed all over the country to tap the available water resources so that this water can be utilized in accordance with the requirements of mankind. Proper management of the reservoirs is required for the efficient use of available water resources. Reservoir operation plays a vital role in planning and management of water resources system. Modeling of a rainfall-runoff is gaining a fast momentum for hydrological and water management studies. This evolution provides the mankind with new possibilities to efficiently use the available water. In this study rainfall-runoff model for three reservoirs, namely Ravishankar Sagar, Murumsilli and Dudhawa reservoirs of MRP Project has been developed, for the available data of 17 years, by the application of fuzzy logic. Fuzzified runoff results from the model are compared with linear regression by calculating the relative error with reference to the observed runoff. It has been found that fuzzy logic based rainfall-runoff model performs better than linear regression model

Soft Computing in Water Resources Engineering

Soft Computing in Water Resources Engineering PDF Author: G. Tayfur
Publisher:
ISBN: 9781845646370
Category : Computers
Languages : en
Pages : 289

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Book Description
Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.

Soft Computing in Water Resources Engineering

Soft Computing in Water Resources Engineering PDF Author: G. Tayfur
Publisher: WIT Press
ISBN: 1845646363
Category : Technology & Engineering
Languages : en
Pages : 289

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Book Description
Engineers have attempted to solve water resources engineering problems with the help of empirical, regression-based and numerical models. Empirical models are not universal, nor are regression-based models. The numerical models are, on the other hand, physics-based but require substantial data measurement and parameter estimation. Hence, there is a need to employ models that are robust, user-friendly, and practical and that do not have the shortcomings of the existing methods. Artificial intelligence methods meet this need. Soft Computing in Water Resources Engineering introduces the basics of artificial neural networks (ANN), fuzzy logic (FL) and genetic algorithms (GA). It gives details on the feed forward back propagation algorithm and also introduces neuro-fuzzy modelling to readers. Artificial intelligence method applications covered in the book include predicting and forecasting floods, predicting suspended sediment, predicting event-based flow hydrographs and sedimentographs, locating seepage path in an earth-fill dam body, and the predicting dispersion coefficient in natural channels. The author also provides an analysis comparing the artificial intelligence models and contemporary non-artificial intelligence methods (empirical, numerical, regression, etc.). The ANN, FL, and GA are fairly new methods in water resources engineering. The first publications appeared in the early 1990s and quite a few studies followed in the early 2000s. Although these methods are currently widely known in journal publications, they are still very new for many scientific readers and they are totally new for students, especially undergraduates. Numerical methods were first taught at the graduate level but are now taught at the undergraduate level. There are already a few graduate courses developed on AI methods in engineering and included in the graduate curriculum of some universities. It is expected that these courses, too, will soon be taught at the undergraduate levels.

Fuzzy Logic Applications in Engineering Science

Fuzzy Logic Applications in Engineering Science PDF Author: J. Harris
Publisher: Springer Science & Business Media
ISBN: 1402040784
Category : Technology & Engineering
Languages : en
Pages : 232

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Book Description
Fuzzy logic is a relatively new concept in science applications. Hitherto, fuzzy logic has been a conceptual process applied in the field of risk management. Its potential applicability is much wider than that, however, and its particular suitability for expanding our understanding of processes and information in science and engineering in our post-modern world is only just beginning to be appreciated. Written as a companion text to the author’s earlier volume "An Introduction to Fuzzy Logic Applications", the book is aimed at professional engineers and students and those with an interest in exploring the potential of fuzzy logic as an information processing kit with a wide variety of practical applications in the field of engineering science and develops themes and topics introduced in the author’s earlier text.

Fuzzy Logic in Geology

Fuzzy Logic in Geology PDF Author: Robert V. Demicco
Publisher: Elsevier
ISBN: 0080521894
Category : Computers
Languages : en
Pages : 374

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Book Description
What is fuzzy logic?--a system of concepts and methods for exploring modes of reasoning that are approximate rather than exact. While the engineering community has appreciated the advances in understanding using fuzzy logic for quite some time, fuzzy logic's impact in non-engineering disciplines is only now being recognized. The authors of Fuzzy Logic in Geology attend to this growing interest in the subject and introduce the use of fuzzy set theory in a style geoscientists can understand. This is followed by individual chapters on topics relevant to earth scientists: sediment modeling, fracture detection, reservoir characterization, clustering in geophysical data analysis, ground water movement, and time series analysis. George Klir is the Distinguished Professor of Systems Science and Director of the Center for Intelligent Systems, Fellow of the IEEE and IFSA, editor of nine volumes, editorial board member of 18 journals, and author or co-author of 16 booksForeword by the inventor of fuzzy logic-- Professor Lotfi Zadeh

Fuzzy Logic

Fuzzy Logic PDF Author: Marek J. Patyra
Publisher: Springer Science & Business Media
ISBN: 3322889556
Category : Technology & Engineering
Languages : en
Pages : 326

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Book Description
This edited volume contains ten papers on the subject of fuzzy technology. Fuzzy technology emerged as a combination of fuzzy sets theory, fuzzy logic and fuzzy-based reasoning. As a technology it gained a very practical meaning through thousands of applications in different theoretical as well as practical disciplines, covering mathematics, physics, chemistry, biology, life science, social science, economy, computer science, and (foremost) electrical, electronic, mechanical, nuclear, chemical, textile, aeronautic, ocean, and many other engineering disciplines. The goal of this book is to create an interest in fuzzy technology among researchers, engineers, professionals and students involved in the research and development in the broad area of artificial intelligence. This book is also intended to bring the reader up-to-date in the area of implementations and applications of fuzzy technology, as well as to generate and stimulate new research ideas in this area. It may inspire and motivate the researcher in new directions, as well as creating a force for new efforts to make a fuzzy technology commonly known and used in science and engineering. This volume appears at a time of unprecedented research interest in the field of fuzzy technology. I intentionally wrote research due to the events that have occurred during the last couple of years. To be more specific, I should describe this interest geographically.

Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering

Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering PDF Author: Shahab Araghinejad
Publisher: Springer Science & Business Media
ISBN: 9400775067
Category : Science
Languages : en
Pages : 299

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Book Description
“Data-Driven Modeling: Using MATLAB® in Water Resources and Environmental Engineering” provides a systematic account of major concepts and methodologies for data-driven models and presents a unified framework that makes the subject more accessible to and applicable for researchers and practitioners. It integrates important theories and applications of data-driven models and uses them to deal with a wide range of problems in the field of water resources and environmental engineering such as hydrological forecasting, flood analysis, water quality monitoring, regionalizing climatic data, and general function approximation. The book presents the statistical-based models including basic statistical analysis, nonparametric and logistic regression methods, time series analysis and modeling, and support vector machines. It also deals with the analysis and modeling based on artificial intelligence techniques including static and dynamic neural networks, statistical neural networks, fuzzy inference systems, and fuzzy regression. The book also discusses hybrid models as well as multi-model data fusion to wrap up the covered models and techniques. The source files of relatively simple and advanced programs demonstrating how to use the models are presented together with practical advice on how to best apply them. The programs, which have been developed using the MATLAB® unified platform, can be found on extras.springer.com. The main audience of this book includes graduate students in water resources engineering, environmental engineering, agricultural engineering, and natural resources engineering. This book may be adapted for use as a senior undergraduate and graduate textbook by focusing on selected topics. Alternatively, it may also be used as a valuable resource book for practicing engineers, consulting engineers, scientists and others involved in water resources and environmental engineering.

Practical Applications of Fuzzy Technologies

Practical Applications of Fuzzy Technologies PDF Author: Hans-Jürgen Zimmermann
Publisher: Springer Science & Business Media
ISBN: 146154601X
Category : Mathematics
Languages : en
Pages : 680

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Book Description
Since the late 1980s, a large number of very user-friendly tools for fuzzy control, fuzzy expert systems, and fuzzy data analysis have emerged. This has changed the character of this area and started the area of `fuzzy technology'. The next large step in the development occurred in 1992 when almost independently in Europe, Japan and the USA, the three areas of fuzzy technology, artificial neural nets and genetic algorithms joined forces under the title of `computational intelligence' or `soft computing'. The synergies which were possible between these three areas have been exploited very successfully. Practical Applications of Fuzzy Sets focuses on model and real applications of fuzzy sets, and is structured into four major parts: engineering and natural sciences; medicine; management; and behavioral, cognitive and social sciences. This book will be useful for practitioners of fuzzy technology, scientists and students who are looking for applications of their models and methods, for topics of their theses, and even for venture capitalists who look for attractive possibilities for investments.

Advanced Fuzzy Logic Approaches in Engineering Science

Advanced Fuzzy Logic Approaches in Engineering Science PDF Author: Ram, Mangey
Publisher: IGI Global
ISBN: 1522557105
Category : Technology & Engineering
Languages : en
Pages : 488

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Book Description
Fuzzy logic techniques have had extraordinary growth in various engineering systems. The developments in engineering sciences have caused apprehension in modern years due to high-tech industrial processes with ever-increasing levels of complexity. Advanced Fuzzy Logic Approaches in Engineering Science provides innovative insights into a comprehensive range of soft fuzzy logic techniques applied in various fields of engineering problems like fuzzy sets theory, adaptive neuro fuzzy inference system, and hybrid fuzzy logic genetic algorithms belief networks in industrial and engineering settings. The content within this publication represents the work of particle swarms, fuzzy computing, and rough sets. It is a vital reference source for engineers, research scientists, academicians, and graduate-level students seeking coverage on topics centered on the applications of fuzzy logic in high-tech industrial processes.

Fuzzy Logic with Engineering Applications

Fuzzy Logic with Engineering Applications PDF Author: Timothy J. Ross
Publisher: John Wiley & Sons
ISBN: 0470860766
Category : Technology & Engineering
Languages : en
Pages : 652

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Book Description
Fuzzy logic refers to a large subject dealing with a set of methods to characterize and quantify uncertainty in engineering systems that arise from ambiguity, imprecision, fuzziness, and lack of knowledge. Fuzzy logic is a reasoning system based on a foundation of fuzzy set theory, itself an extension of classical set theory, where set membership can be partial as opposed to all or none, as in the binary features of classical logic. Fuzzy logic is a relatively new discipline in which major advances have been made over the last decade or so with regard to theory and applications. Following on from the successful first edition, this fully updated new edition is therefore very timely and much anticipated. Concentration on the topics of fuzzy logic combined with an abundance of worked examples, chapter problems and commercial case studies is designed to help motivate a mainstream engineering audience, and the book is further strengthened by the inclusion of an online solutions manual as well as dedicated software codes. Senior undergraduate and postgraduate students in most engineering disciplines, academics and practicing engineers, plus some working in economics, control theory, operational research etc, will all find this a valuable addition to their bookshelves.