This excellently written monograph provides – for the first time ever - a thorough introduction and systematic overview of all aspects of intelligent data processing on the Web. It presents both the current state of research as well as application aspects. All major topics related to Web Intelligence which can have impact on future directions and developments are presented in detail. This book will be a valuable source of reference for years to all research and development professionals interested in Web Intelligence. Students will also appreciate the numerous illustrations and examples.
This volume is an attempt to capture the essence of the state-of-the-art of intelligent agent technology and to identify the new challenges and opportunities that it is or will be facing. The most important feature of the volume is that it emphasizes a multi-faceted, holistic view of this emerging technology, from its computational foundations OCo in terms of models, methodologies, and tools for developing a variety of embodiments of agent-based systems OCo to its practical impact on tackling real-world problems. Contents: Formal Agent Theories; Computational Architecture and Infrastructure; Learning and Adaptation; Knowledge Discovery and Data Mining Agents; Distributed Intelligence; Agent Based Applications. Readership: Graduate students in computer science and engineering, academics/lecturers, researchers, software/systems engineers, IT engineers and industrialists.
This book presents up-to-date theory and methods of statistical hypothesis testing based on measure theory. The so-called statistical space is a measurable space adding a family of probability measures. Most topics in the book will be developed based on this term. The book includes some typical data sets, such as the relation between race and the death penalty verdict, the behavior of food intake of two kinds of Zucker rats, and the per capita income and expenditure in China during the 1978-2002 period. Emphasis is given to the process of finding appropriate statistical techniques and methods of evaluating these techniques.
This book is the first of its kind to comprehensively describe the principles of demand response. This allows consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage in response to the grid reliability need, time-based rates or other forms of financial incentives. The main contents of the book include modeling of demand response resources, incentive design, scheduling and dispatch algorithms, and impacts on grid operation and planning. Through case studies and illustrative examples, the authors highlight and compare the advantages, disadvantages and benefits that demand response can have on grid operations and electricity market efficiency. First book of its kind to introduce the principles of demand response; Combines theory with real-world applications useful for both professionals and academic researchers; Covers demand response in the context of power system applications.
Over the last 15 years, the application of innovative steel concepts in the automotive industry has increased steadily. Numerical simulation technology of hot forming of high-strength steel allows engineers to modify the formability of hot forming steel metals and to optimize die design schemes. Theories, Methods and Numerical Technology of Sheet Metal Cold and Hot Forming focuses on hot and cold forming theories, numerical methods, relative simulation and experiment techniques for high-strength steel forming and die design in the automobile industry. Theories, Methods and Numerical Technology of Sheet Metal Cold and Hot Forming introduces the general theories of cold forming, then expands upon advanced hot forming theories and simulation methods, including: the forming process, constitutive equations, hot boundary constraint treatment, and hot forming equipment and experiments. Various calculation methods of cold and hot forming, based on the authors’ experience in commercial CAE software for sheet metal forming, are provided, as well as a discussion of key issues, such as hot formability with quenching process, die design and cooling channel design in die, and formability experiments. Theories, Methods and Numerical Technology of Sheet Metal Cold and Hot Forming will enable readers to develop an advanced knowledge of hot forming, as well as to apply hot forming theories, calculation methods and key techniques to direct their die design. It is therefore a useful reference for students and researchers, as well as automotive engineers.
This book constitutes the refereed proceedings of the 7th International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing, RSFDGrC'99, held in Yamaguchi, Japan, in November 1999. The 45 revised regular papers and 15 revised short papers presented together with four invited contributions were carefully reviewed and selected from 89 submissions. The book is divided into sections on rough computing: foundations and applications, rough set theory and applications, fuzzy set theory and applications, nonclassical logic and approximate reasoning, information granulation and granular computing, data mining and knowledge discovery, machine learning, and intelligent agents and systems.
This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.
This book constitutes the refereed proceedings of the Third Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD '99, held in Beijing, China, in April 1999. The 29 revised full papers presented together with 37 short papers were carefully selected from a total of 158 submissions. The book is divided into sections on emerging KDD technology; association rules; feature selection and generation; mining in semi-unstructured data; interestingness, surprisingness, and exceptions; rough sets, fuzzy logic, and neural networks; induction, classification, and clustering; visualization; causal models and graph-based methods; agent-based and distributed data mining; and advanced topics and new methodologies.
Understanding the dynamics of multi-phase flows has been a challenge in the fields of nonlinear dynamics and fluid mechanics. This chapter reviews our work on two-phase flow dynamics in combination with complex network theory. We systematically carried out gas-water/oil-water two-phase flow experiments for measuring the time series of flow signals which is studied in terms of the mapping from time series to complex networks. Three network mapping methods were proposed for the analysis and identification of flow patterns, i.e. Flow Pattern Complex Network (FPCN), Fluid Dynamic Complex Network (FDCN) and Fluid Structure Complex Network (FSCN). Through detecting the community structure of FPCN based on K-means clustering, distinct flow patterns can be successfully distinguished and identified. A number of FDCN’s under different flow conditions were constructed in order to reveal the dynamical characteristics of two-phase flows. The FDCNs exhibit universal power-law degree distributions. The power-law exponent and the network information entropy are sensitive to the transition among different flow patterns, which can be used to characterize nonlinear dynamics of the two-phase flow. FSCNs were constructed in the phase space through a general approach that we introduced. The statistical properties of FSCN can provide quantitative insight into the fluid structure of two-phase flow. These interesting and significant findings suggest that complex networks can be a potentially powerful tool for uncovering the nonlinear dynamics of two-phase flows.
The cave-temple complex popularly known as the Dunhuang caves is the world's largest extant repository of Tang Buddhist art. Among the best preserved of the Dunhuang caves is the Zhai Family Cave, built in 642. It is this remarkable cave-temple that forms the focus of Ning Qiang's cross-disciplinary exploration of the interrelationship of art, religion, and politics during the Tang. In his careful examination of the paintings and sculptures found there, the author combines the historical study of pictures with the pictorial study of history. By employing this two-fold approach, he is able to refer to textual evidence in interpreting the formal features of the cave-temple paintings and to employ visual details to fill in the historical gaps inevitably left by text-oriented scholars. The result is a comprehensive analysis of the visual culture of the period and a vivid description of social life in medieval China. and remained hidden until the early 1940s. Once exposed, the early artwork appeared fresh and colorful in comparison with other Tang paintings at Dunhuang. The relatively fine condition of the Zhai Family Cave is crucial to our understanding of the original pictorial program found there and offers a unique opportunity to investigate the visual details of the original paintings and sculptures in the cave. At the same time, the remaining traces of reconstruction and redecoration provide a new perspective on how, for over three centuries, a wealthy Chinese clan used its familial cave as a political showcase. Art, Religion, and Politics in Medieval China: The Dunhuang Cave of the Zhai Family is an in-depth study on the meaning and function of an exemplary Tang memorial cave and an important contribution to studies of Chinese religion, politics, sociology, literature, and folklore as well as to Chinese art history.
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