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Nuclear Materials Safety Management
With the end of the Cold War, new opportunities for interaction have opened up between the United States and the countries of the Former Soviet Union. Many of these important initiatives involve the US Department of Energy (DOE) and the Ministry of the Russian Federation for Atomic Energy (MINA TOM). Currently, collaboration is under way which involves reactor safety, the disposition of fissile materials from the weapons program, radioactive waste disposal, and the safety of nuclear warheads. Another fruitful area of interchange resulted from the radiochemical storage tank accident at the site of the Siberian Chemical Compound at Tomsk-7 in 1993. DOE and MINATOM agreed to meet and exchange i...
Innovations in Intelligent Machines-4
This research volume is a continuation of our previous volumes on intelligent machine. It is divided into three parts. Part I deals with big data and ontologies. It includes examples related to the text mining, rule mining and ontology. Part II is on knowledge-based systems. It includes context-centered systems, knowledge discovery, interoperability, consistency and systems of systems. The final part is on applications. The applications involve prediction, decision optimization and assessment. This book is directed to the researchers who wish to explore the field of knowledge engineering further.
Transactions on Rough Sets III
The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This third volume of the Transactions on Rough Sets presents 11 revised papers that have been through a careful peer reviewing process by the journal's Editorial Board. The research monograph "Time Complexity of Decision Trees" by Mikhail Ju. Moshkov is presented in the section on dissertation and monographs. Among the regular papers the one by Zdzislaw Pawlak entitled "Flow Graphs and Data Mining" deserves a special mention.
Dynamic Programming Multi-Objective Combinatorial Optimization
This book introduces a fairly universal approach to the design and analysis of exact optimization algorithms for multi-objective combinatorial optimization problems. It proposes the circuits without repetitions representing the sets of feasible solutions along with the increasing and strictly increasing cost functions as a model for such problems. The book designs the algorithms for multi-stage and bi-criteria optimization and for counting the solutions in the framework of this model. As applications, this book studies eleven known combinatorial optimization problems: matrix chain multiplication, global sequence alignment, optimal paths in directed graphs, binary search trees, convex polygon triangulation, line breaking (text justification), one-dimensional clustering, optimal bitonic tour, segmented least squares, optimization of matchings in trees, and 0/1 knapsack problem. The results presented are useful for researchers in combinatorial optimization. This book is also useful as the basis for graduate courses.
Mathematical Reviews
None
Rough Sets and Current Trends in Computing
This book constitutes the refereed proceedings of the Third International Conference on Rough Sets and Current Trends in Computing, RSCTC 2002, held in Malvern, PA, USA in October 2002. The 76 revised regular papers and short communications presented together with 2 keynotes and 5 plenary papers were carefully reviewed and selected from more than 100 submissions. The book offers topical sections on foundation and methods; granular and neural computing; probabilistic reasoning; data mining, machine learning and pattern recognition; Web mining; and applications.
Combinatorial Machine Learning
Decision trees and decision rule systems are widely used in different applications as algorithms for problem solving, as predictors, and as a way for knowledge representation. Reducts play key role in the problem of attribute (feature) selection. The aims of this book are (i) the consideration of the sets of decision trees, rules and reducts; (ii) study of relationships among these objects; (iii) design of algorithms for construction of trees, rules and reducts; and (iv) obtaining bounds on their complexity. Applications for supervised machine learning, discrete optimization, analysis of acyclic programs, fault diagnosis, and pattern recognition are considered also. This is a mixture of research monograph and lecture notes. It contains many unpublished results. However, proofs are carefully selected to be understandable for students. The results considered in this book can be useful for researchers in machine learning, data mining and knowledge discovery, especially for those who are working in rough set theory, test theory and logical analysis of data. The book can be used in the creation of courses for graduate students.
