bhawna garg and deepak saxena application of neural networks in area of management decision making

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Jeffrey Herrmann W. Engineering Decision Making and Risk Management

IIE/Joint Publishers Book of the Year Award 2016! Awarded for ‘an outstanding published book that focuses on a facet of industrial engineering, improves education, or furthers the profession’. Engineering Decision Making and Risk Management emphasizes practical issues and examples of decision making with applications in engineering design and management Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision-making systems, Engineering Decision Making and Risk Management also features: Theoretically sound and practical tools for decision making under uncertainty, multi-criteria decision making, group decision making, the value of information, and risk management Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes End-of-chapter exercises for readers to apply specific learning objectives and practice relevant skills A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in-class activities, slides, and spreadsheets An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics.

8922.38 рублей

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Akira Hirose Complex-Valued Neural Networks. Advances and Applications

Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and superconducting waves. This fact is a critical advantage in practical applications in diverse fields of engineering, where signals are routinely analyzed and processed in time/space, frequency, and phase domains. Complex-Valued Neural Networks: Advances and Applications covers cutting-edge topics and applications surrounding this timely subject. Demonstrating advanced theories with a wide range of applications, including communication systems, image processing systems, and brain-computer interfaces, this text offers comprehensive coverage of: Conventional complex-valued neural networks Quaternionic neural networks Clifford-algebraic neural networks Presented by international experts in the field, Complex-Valued Neural Networks: Advances and Applications is ideal for advanced-level computational intelligence theorists, electromagnetic theorists, and mathematicians interested in computational intelligence, artificial intelligence, machine learning theories, and algorithms.

10192.06 рублей

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Eleftherios Iakovou Supply Chain Management for Sustainable Food Networks

An interdisciplinary framework for managing sustainable agrifood supply chains Supply Chain Management for Sustainable Food Networks provides an up-to-date and interdisciplinary framework for designing and operating sustainable supply chains for agri-food products. Focus is given to decision-making procedures and methodologies enabling policy-makers, managers and practitioners to design and manage effectively sustainable agrifood supply chain networks. Authored by high profile researchers with global expertise in designing and operating sustainable supply chains in the agri-food industry, this book: Features the entire hierarchical decision-making process for managing sustainable agrifood supply chains. Covers knowledge-based farming, management of agricultural wastes, sustainability, green supply chain network design, safety, security and traceability, IT in agrifood supply chains, carbon footprint management, quality management, risk management and policy- making. Explores green supply chain management, sustainable knowledge-based farming, corporate social responsibility, environmental management and emerging trends in agri-food retail supply chain operations. Examines sustainable practices that are unique for agriculture as well as practices that already have been implemented in other industrial sectors such as green logistics and Corporate Social Responsibility (CSR). Supply Chain Management for Sustainable Food Networks provides a useful resource for researchers, practitioners, policy-makers, regulators and C-level executives that deal with strategic decision-making. Post-graduate students in the field of agriculture sciences, engineering, operations management, logistics and supply chain management will also benefit from this book.

8247.97 рублей

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Michael Doumpos Multicriteria Decision Aid and Artificial Intelligence. Links, Theory and Applications

Presents recent advances in both models and systems for intelligent decision making. Organisations often face complex decisions requiring the assessment of large amounts of data. In recent years Multicriteria Decision Aid (MCDA) and Artificial Intelligence (AI) techniques have been applied with considerable success to support decision making in a wide range of complex real-world problems. The integration of MCDA and AI provides new capabilities relating to the structuring of complex decision problems in static and distributed environments. These include the handling of massive data sets, the modelling of ill-structured information, the construction of advanced decision models, and the development of efficient computational optimization algorithms for problem solving. This book covers a rich set of topics, including intelligent decision support technologies, data mining models for decision making, evidential reasoning, evolutionary multiobjective optimization, fuzzy modelling, as well as applications in management and engineering. Multicriteria Decision Aid and Artificial Intelligence: Covers all of the recent advances in intelligent decision making. Includes a presentation of hybrid models and algorithms for preference modelling and optimisation problems. Provides illustrations of new intelligent technologies and architectures for decision making in static and distributed environments. Explores the general topics on preference modelling and learning, along with the coverage of the main techniques and methodologies and applications. Is written by experts in the field. This book provides an excellent reference tool for the increasing number of researchers and practitioners interested in the integration of MCDA and AI for the development of effective hybrid decision support methodologies and systems. Academics and post-graduate students in the fields of operational research, artificial intelligence and management science or decision analysis will also find this book beneficial.

8772.98 рублей

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Nutt Paul C. Handbook of Decision Making

Wiley's new Handbook of Decision Making is a vital reference text for all students and professionals of management, organization and decision making. The handbook offers a wide range of theoretical and empirical approaches to the understanding of organizational and strategic decisions. Contributors are internationally known experts drawn from North America, Canada and Europe who have spent many years in the study of decision making, and decision making relevant topics. We believe the handbook will become a tour de force in the understanding decision making, offering a wide variety of perspectives, topics, and summative understanding of the field. Chapters in the Handbook were prepared by the leading experts in their field and include cutting edge empirical, theoretical, and review chapters. The chapters bring together for the first time a critical mass of writing on decision making as an organizational and research activity. The Editors are two of the leading international experts in decision making and contribute to the Handbook with five original Chapters that offer an appraisal of the field and suggestions for research, as well as the current status of decision making practice and suggestion for improvement.

9195.84 рублей

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Yuri Raydugin Project Risk Management. Essential Methods for Project Teams and Decision Makers

An easy to implement, practical, and proven risk management methodology for project managers and decision makers Drawing from the author's work with several major and mega capital projects for Royal Dutch Shell, TransCanada Pipelines, TransAlta, Access Pipeline, MEG Energy, and SNC-Lavalin, Project Risk Management: Essential Methods for Project Teams and Decision Makers reveals how to implement a consistent application of risk methods, including probabilistic methods. It is based on proven training materials, models, and tools developed by the author to make risk management plans accessible and easily implemented. Written by an experienced risk management professional Reveals essential risk management methods for project teams and decision makers Packed with training materials, models, and tools for project management professionals Risk Management has been identified as one of the nine content areas for Project Management Professional (PMP®) certification. Yet, it remains an area that can get bogged down in the real world of project management. Practical and clearly written, Project Risk Management: Essential Methods for Project Teams and Decision Makers equips project managers and decision makers with a practical understanding of the basics of risk management as they apply to project management. (PMP and Project Management Professional are registered marks of the Project Management Institute, Inc.)

5108.8 рублей

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Derong Liu Fundamentals of Computational Intelligence. Neural Networks, Fuzzy Systems, and Evolutionary Computation

Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation. The text focuses on inspiration, design, theory, and practical aspects of implementing procedures to solve real-world problems. While other books in the three fields that comprise computational intelligence are written by specialists in one discipline, this book is co-written by current former Editor-in-Chief of IEEE Transactions on Neural Networks and Learning Systems, a former Editor-in-Chief of IEEE Transactions on Fuzzy Systems, and the founding Editor-in-Chief of IEEE Transactions on Evolutionary Computation. The coverage across the three topics is both uniform and consistent in style and notation. Discusses single-layer and multilayer neural networks, radial-basis function networks, and recurrent neural networks Covers fuzzy set theory, fuzzy relations, fuzzy logic interference, fuzzy clustering and classification, fuzzy measures and fuzzy integrals Examines evolutionary optimization, evolutionary learning and problem solving, and collective intelligence Includes end-of-chapter practice problems that will help readers apply methods and techniques to real-world problems Fundamentals of Computational intelligence is written for advanced undergraduates, graduate students, and practitioners in electrical and computer engineering, computer science, and other engineering disciplines.

8997.79 рублей

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Gerard Gaynor H. Decisions. An Engineering and Management Perspective

DECISIONS focuses on how organizations can improve decision-making processes to improve organizational performance in a global economy. Presents research related to problems associated with meeting requirements, schedules, and costs Defines the scope of macro and micro decisions Raises the issue of the role of engineering, manufacturing, and marketing in making organizational decisions Includes references to Peter Drucker’s studies on decision-making

3895.63 рублей

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Witold Pedrycz Fuzzy Multicriteria Decision-Making. Models, Methods and Applications

Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications addresses theoretical and practical gaps in considering uncertainty and multicriteria factors encountered in the design, planning, and control of complex systems. Including all prerequisite knowledge and augmenting some parts with a step-by-step explanation of more advanced concepts, the authors provide a systematic and comprehensive presentation of the concepts, design methodology, and detailed algorithms. These are supported by many numeric illustrations and a number of application scenarios to motivate the reader and make some abstract concepts more tangible. Fuzzy Multicriteria Decision-Making: Models, Algorithms and Applications will appeal to a wide audience of researchers and practitioners in disciplines where decision-making is paramount, including various branches of engineering, operations research, economics and management; it will also be of interest to graduate students and senior undergraduate students in courses such as decision making, management, risk management, operations research, numerical methods, and knowledge-based systems.

12746.87 рублей

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Gregory Parnell S. Decision Making in Systems Engineering and Management

Decision Making in Systems Engineering and Management is a comprehensive textbook that provides a logical process and analytical techniques for fact-based decision making for the most challenging systems problems. Grounded in systems thinking and based on sound systems engineering principles, the systems decisions process (SDP) leverages multiple objective decision analysis, multiple attribute value theory, and value-focused thinking to define the problem, measure stakeholder value, design creative solutions, explore the decision trade off space in the presence of uncertainty, and structure successful solution implementation. In addition to classical systems engineering problems, this approach has been successfully applied to a wide range of challenges including personnel recruiting, retention, and management; strategic policy analysis; facilities design and management; resource allocation; information assurance; security systems design; and other settings whose structure can be conceptualized as a system.

11022.43 рублей

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Yi Qian Heterogeneous Cellular Networks

A timely publication providing coverage of radio resource management, mobility management and standardization in heterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentum in industry and the research community, attracting the attention of standardization bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are looking into increasing the capacity and coverage of the cellular networks. This book focuses on recent progresses, covering the related topics including scenarios of heterogeneous network deployment, interference management in the heterogeneous network deployment, carrier aggregation in a heterogeneous network, cognitive radio, cell selection/reselection and load balancing, mobility and handover management, capacity and coverage optimization for heterogeneous networks, traffic management and congestion control. This book enables readers to better understand the technical details and performance gains that are made possible by this state-of-the-art technology. It contains the information necessary for researchers and engineers wishing to build and deploy highly efficient wireless networks themselves. To enhance this practical understanding, the book is structured to systematically lead the reader through a series of case-studies of real world scenarios. Key features: Presents this new paradigm in cellular network domain: a heterogeneous network containing network nodes with different characteristics such as transmission power and RF coverage area Provides a clear approach by containing tables, illustrations, industry case studies, tutorials and examples to cover the related topics Includes new research results and state-of-the-art technological developments and implementation issues

11622.14 рублей

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Franco Taroni Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation" Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. • Includes self-contained introductions to probability and decision theory. • Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. • Features implementation of the methodology with reference to commercial and academically available software. • Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. • Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. • Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. • Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. • Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

7798.37 рублей

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Louis Anthony Cox, Jr. Breakthroughs in Decision Science and Risk Analysis

Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.

9748.31 рублей

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Hojjat Adeli Computational Intelligence. Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the cutting edge technological paradigms under the umbrella of computational intelligence. Computational intelligence schemes are investigated with the development of a suitable framework for fuzzy logic, neural networks and evolutionary computing, neuro-fuzzy systems, evolutionary-fuzzy systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: Covers all the aspects of fuzzy, neural and evolutionary approaches with worked out examples, MATLAB® exercises and applications in each chapter Presents the synergies of technologies of computational intelligence such as evolutionary fuzzy neural fuzzy and evolutionary neural systems Considers real world problems in the domain of systems modelling, control and optimization Contains a foreword written by Lotfi Zadeh Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing is an ideal text for final year undergraduate, postgraduate and research students in electrical, control, computer, industrial and manufacturing engineering.

10872.33 рублей

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Guanrong Chen Fundamentals of Complex Networks. Models, Structures and Dynamics

Complex networks such as the Internet, WWW, transportation networks, power grids, biological neural networks, and scientific cooperation networks of all kinds provide challenges for future technological development. • The first systematic presentation of dynamical evolving networks, with many up-to-date applications and homework projects to enhance study • The authors are all very active and well-known in the rapidly evolving field of complex networks • Complex networks are becoming an increasingly important area of research • Presented in a logical, constructive style, from basic through to complex, examining algorithms, through to construct networks and research challenges of the future

9372.7 рублей

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Pascale Zarate Tools for Collaborative Decision-Making

Decision-making has evolved recently thanks to the introduction of information and communication technologies in many organizations, which has led to new kinds of decision-making processes, called “collaborative decision-making”, at the organizational and cognitive levels. This book looks at the development of the decision-making process in organizations. Decision-aiding and its paradigm of problem solving are defined, showing how decision-makers now need to work in a cooperative way. Definitions of cooperation and associated concepts such as collaboration and coordination are given and a framework of cooperative decision support systems is presented, including intelligent DSS, cooperative knowledge-based systems, workflow, group support systems, collaborative engineering, integrating with a collaborative decision-making model in part or being part of global projects. Several models and experimental studies are also included showing that these new processes have to be supported by new types of tools, several of which are described in order to calculate or simulate solutions or global solutions for decision-making modification. Definitions and new trends for these models are given, along with types of systems. Contents 1. Alteration of Decision-Making Processes in Organizations. 2. New Decision-Making Processes. 3. The Need to Cooperate. 4. Cooperative Decision-Making. 5. Activity Support Systems. 6. Cooperative Decision Support Systems: CDSSS. About the Authors Pascale Zaraté is Professor at Toulouse 1 Capitole University, France. She conducts her research at the IRIT Laboratory and is the Editor-in-Chief of the International Journal of Decision Support Systems Technologies. She is co-chair of the European Working Group on DSS and has published several studies and books.

5594.14 рублей

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John Silvia E. Dynamic Economic Decision Making. Strategies for Financial Risk, Capital Markets, and Monetary Policy

A comprehensive analysis of the macroeconomic and financial forces altering the economic landscape Financial decision-making requires one to anticipate how their decision will not only affect their business, but also the economic environment. Unfortunately, all too often, both private and public sector decision-makers view their decisions as one-off responses and fail to see their decisions within the context of an evolving decision-making framework. In Decision-Making in a Dynamic Economic Setting, John Silvia, Chief Economist of Wells Fargo and one of the top 5 economic forecasters according to Bloomberg News and USA Today, skillfully puts this discipline in perspective. Details realistic, decision-making approaches and applications under a broad set of economic scenarios Analyzes monetary policy and addresses the impact of financial regulations Examines business cycles and how to identify economic trends, how to deal with uncertainty and manage risk, the building blocks of growth, and strategies for innovation Decision-Making in a Dynamic Economic Setting details the real-world application of economic principles and financial strategy in making better business decisions.

4470.2 рублей

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Lorenzo Beatriz Advanced Wireless Networks. Cognitive, Cooperative & Opportunistic 4G Technology

With 40% new material the new edition of Advanced Wireless Networks provides a comprehensive representation of the key issues in 4G wireless networks. Focussing on cognitive, cooperative and opportunistic paradigms to provide further increase in network efficiency, the book explores and addresses issues in wireless internet, mobile cellular and WLAN, as well as sensor, ad hoc, bio-inspired, active and cognitive networks. It examines the problem of cross-layer optimisation and network information theory as well as adaptability and reconfigurability in wireless networks. This book is an integral description of future wireless networks and the interconnection between their elements. The information is presented in a logical order within each chapter making it ideal for all levels of reader including researchers involved in modelling and analysis of future networks as well as engineers working in the area. Each chapter starts with introductory material and gradually includes more sophisticated models and mathematical tools concluding with a comprehensive list of references. Fully updated throughout with five new chapters on Opportunistic Communications; Relaying and Mesh Networks; Topology Control; Network Optimization; and Cognitive Radio Resource Management Unifies the latest research on cognitive, cooperative and opportunistic paradigms in wireless communications Provides efficient analytical tools for network analysis Discusses security issues, an essential element of working with wireless networks Supports advanced university and training courses in the field Companion website containing extra appendix on Queuing theory

14330.18 рублей

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"This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation" Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. • Includes self-contained introductions to probability and decision theory. • Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. • Features implementation of the methodology with reference to commercial and academically available software. • Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. • Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. • Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. • Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. • Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

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