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Artificial Neural Network Applications in the Calibration of Engines

Artificial Neural Network Applications in the Calibration of Engines Author Richard Fiifi Turkson
ISBN-10 3659956619
Release 2016-11-01
Pages 52
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Computational Intelligence in Automotive Applications

Computational Intelligence in Automotive Applications Author Danil Prokhorov
ISBN-10 9783540792574
Release 2008-05-28
Pages 365
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What is computational intelligence (CI)? Traditionally, CI is understood as a collection of methods from the ?elds of neural networks (NN), fuzzy logic and evolutionary computation. Various de?nitions and opinions exist, but what belongs to CI is still being debated; see, e.g., [1–3]. More recently there has been a proposal to de?ne the CI not in terms of the tools but in terms of challenging problems to be solved [4]. With this edited volume I have made an attempt to give a representative sample of contemporary CI activities in automotive applications to illustrate the state of the art. While CI researchand achievements in some specialized ?elds described (see, e.g., [5, 6]), this is the ?rst volume of its kind dedicated to automotive technology. As if re?ecting the general lack of consensus on what constitutes the ?eld of CI, this volume 1 illustrates automotive applications of not only neural and fuzzy computations which are considered to be the “standard” CI topics, but also others, such as decision trees, graphicalmodels, Support Vector Machines (SVM), multi-agent systems, etc. This book is neither an introductory text, nor a comprehensive overview of all CI research in this area. Hopefully, as a broad and representative sample of CI activities in automotive applications, it will be worth reading for both professionals and students. When the details appear insu?cient, the reader is encouraged to consult other relevant sources provided by the chapter authors.



Using high fidelity simulations and artificial neural networks in calibration and control of high degree of freedom internal combustion engines

Using high fidelity simulations and artificial neural networks in calibration and control of high degree of freedom internal combustion engines Author Bin Wu
ISBN-10 UOM:39015063180262
Release 2006
Pages
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Soft Computing in Artificial Intelligence

Soft Computing in Artificial Intelligence Author Young Im Cho
ISBN-10 9783319055152
Release 2014-07-08
Pages 153
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This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.



The Control Handbook Second Edition

The Control Handbook  Second Edition Author William S. Levine
ISBN-10 1420073613
Release 2010-12-08
Pages 942
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At publication, The Control Handbook immediately became the definitive resource that engineers working with modern control systems required. Among its many accolades, that first edition was cited by the AAP as the Best Engineering Handbook of 1996. Now, 15 years later, William Levine has once again compiled the most comprehensive and authoritative resource on control engineering. He has fully reorganized the text to reflect the technical advances achieved since the last edition and has expanded its contents to include the multidisciplinary perspective that is making control engineering a critical component in so many fields. Now expanded from one to three volumes, The Control Handbook, Second Edition organizes cutting-edge contributions from more than 200 leading experts. The second volume, Control System Applications, includes 35 entirely new applications organized by subject area. Covering the design and use of control systems, this volume includes applications for: Automobiles, including PEM fuel cells Aerospace Industrial control of machines and processes Biomedical uses, including robotic surgery and drug discovery and development Electronics and communication networks Other applications are included in a section that reflects the multidisciplinary nature of control system work. These include applications for the construction of financial portfolios, earthquake response control for civil structures, quantum estimation and control, and the modeling and control of air conditioning and refrigeration systems. As with the first edition, the new edition not only stands as a record of accomplishment in control engineering but provides researchers with the means to make further advances. Progressively organized, the other two volumes in the set include: Control System Fundamentals Control System Advanced Methods



Neural Network Control and Its Application to Automotive Engine Control

Neural Network Control and Its Application to Automotive Engine Control Author Li-Wen Chen
ISBN-10 UCAL:C3389191
Release 1995
Pages 250
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Adaptive Dynamic Programming for Control

Adaptive Dynamic Programming for Control Author Huaguang Zhang
ISBN-10 9781447147572
Release 2012-12-14
Pages 424
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There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three main aspects of ADP in which the methods proposed for stabilization and for tracking and games benefit from the incorporation of optimal control methods: • infinite-horizon control for which the difficulty of solving partial differential Hamilton–Jacobi–Bellman equations directly is overcome, and proof provided that the iterative value function updating sequence converges to the infimum of all the value functions obtained by admissible control law sequences; • finite-horizon control, implemented in discrete-time nonlinear systems showing the reader how to obtain suboptimal control solutions within a fixed number of control steps and with results more easily applied in real systems than those usually gained from infinite-horizon control; • nonlinear games for which a pair of mixed optimal policies are derived for solving games both when the saddle point does not exist, and, when it does, avoiding the existence conditions of the saddle point. Non-zero-sum games are studied in the context of a single network scheme in which policies are obtained guaranteeing system stability and minimizing the individual performance function yielding a Nash equilibrium. In order to make the coverage suitable for the student as well as for the expert reader, Adaptive Dynamic Programming in Discrete Time: • establishes the fundamental theory involved clearly with each chapter devoted to a clearly identifiable control paradigm; • demonstrates convergence proofs of the ADP algorithms to deepen understanding of the derivation of stability and convergence with the iterative computational methods used; and • shows how ADP methods can be put to use both in simulation and in real applications. This text will be of considerable interest to researchers interested in optimal control and its applications in operations research, applied mathematics computational intelligence and engineering. Graduate students working in control and operations research will also find the ideas presented here to be a source of powerful methods for furthering their study.



Advances in Internal Combustion Engine Research

Advances in Internal Combustion Engine Research Author Dhananjay Kumar Srivastava
ISBN-10 9789811075759
Release 2017-11-29
Pages 345
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This book discusses all aspects of advanced engine technologies, and describes the role of alternative fuels and solution-based modeling studies in meeting the increasingly higher standards of the automotive industry. By promoting research into more efficient and environment-friendly combustion technologies, it helps enable researchers to develop higher-power engines with lower fuel consumption, emissions, and noise levels. Over the course of 12 chapters, it covers research in areas such as homogeneous charge compression ignition (HCCI) combustion and control strategies, the use of alternative fuels and additives in combination with new combustion technology and novel approaches to recover the pumping loss in the spark ignition engine. The book will serve as a valuable resource for academic researchers and professional automotive engineers alike.



Proceedings of the International Conference on Neural Networks

Proceedings of the International Conference on Neural Networks Author IEEE Neural Networks Council
ISBN-10 UCSD:31822021255716
Release 1996
Pages 2275
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The 1996 IEEE International Conference on Neural Networks

The 1996 IEEE International Conference on Neural Networks Author
ISBN-10 0780332113
Release 1996
Pages 2275
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Design of Experiments Approach for Implementation and Calibration of an OBD II Compliant EGR Monitor Using a Transient Diesel Engine Test Cell

Design of Experiments Approach for Implementation and Calibration of an OBD II Compliant EGR Monitor Using a Transient Diesel Engine Test Cell Author Adam D. Wise
ISBN-10 WISC:89079350518
Release 2001
Pages 284
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Design of Experiments Approach for Implementation and Calibration of an OBD II Compliant EGR Monitor Using a Transient Diesel Engine Test Cell has been writing in one form or another for most of life. You can find so many inspiration from Design of Experiments Approach for Implementation and Calibration of an OBD II Compliant EGR Monitor Using a Transient Diesel Engine Test Cell also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Design of Experiments Approach for Implementation and Calibration of an OBD II Compliant EGR Monitor Using a Transient Diesel Engine Test Cell book for free.



Engineering Applications of Neural Networks

Engineering Applications of Neural Networks Author Chrisina Jayne
ISBN-10 9783642329098
Release 2013-04-19
Pages 512
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This book constitutes the refereed proceedings of the 13th International Conference on Engineering Applications of Neural Networks, EANN 2012, held in London, UK, in September 2012. The 49 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers describe the applications of neural networks and other computational intelligence approaches to intelligent transport, environmental engineering, computer security, civil engineering, financial forecasting, virtual learning environments, language interpretation, bioinformatics and general engineering.



Automotive Engineering International

Automotive Engineering International Author
ISBN-10 UOM:39076002249170
Release 2002-07
Pages
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The Computational Brain

The Computational Brain Author Patricia S. Churchland
ISBN-10 9780262339667
Release 2016-10-28
Pages 568
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Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research.This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.



AIAA Aerospace Sciences Meeting and Exhibit 42nd

AIAA Aerospace Sciences Meeting and Exhibit  42nd Author
ISBN-10 PSU:000055056670
Release 2004
Pages
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Neural networks theory technology and applications

Neural networks theory  technology  and applications Author Patrick K. Simpson
ISBN-10 0780325648
Release 1996
Pages 943
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Neural networks theory technology and applications has been writing in one form or another for most of life. You can find so many inspiration from Neural networks theory technology and applications also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Neural networks theory technology and applications book for free.



Engine Modeling and Control

Engine Modeling and Control Author Rolf Isermann
ISBN-10 9783642399343
Release 2014-07-01
Pages 637
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The increasing demands for internal combustion engines with regard to fuel consumption, emissions and driveability lead to more actuators, sensors and complex control functions. A systematic implementation of the electronic control systems requires mathematical models from basic design through simulation to calibration. The book treats physically-based as well as models based experimentally on test benches for gasoline (spark ignition) and diesel (compression ignition) engines and uses them for the design of the different control functions. The main topics are: - Development steps for engine control - Stationary and dynamic experimental modeling - Physical models of intake, combustion, mechanical system, turbocharger, exhaust, cooling, lubrication, drive train - Engine control structures, hardware, software, actuators, sensors, fuel supply, injection system, camshaft - Engine control methods, static and dynamic feedforward and feedback control, calibration and optimization, HiL, RCP, control software development - Control of gasoline engines, control of air/fuel, ignition, knock, idle, coolant, adaptive control functions - Control of diesel engines, combustion models, air flow and exhaust recirculation control, combustion-pressure-based control (HCCI), optimization of feedforward and feedback control, smoke limitation and emission control This book is an introduction to electronic engine management with many practical examples, measurements and research results. It is aimed at advanced students of electrical, mechanical, mechatronic and control engineering and at practicing engineers in the field of combustion engine and automotive engineering.