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Soft Computing for Knowledge Discovery and Data Mining
Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.
Medical Data Analysis
It is a pleasure for us to present the contributions of the First International Symposium on Medical Data Analysis. Traditionally, the eld of medical data analysis can be devided into classical topics such as medical statistics, sur- val analysis, biometrics and medical informatics. Recently, however, time series analysis by physicists, machine learning and data mining with methods such as neural networks, Bayes networks or fuzzy computing by computer scientists have contributed important ideas to the led of medical data analysis. Although all these groups have similar intentions, there was nearly no exchange or discussion between them. With the growing possibilities for storing and ana- zin...
The Exoteric Square of Opposition
The theory of the square of opposition has been studied for over 2,000 years and has seen a resurgence in new theories and research since the second half of the twentieth century. This volume collects papers presented at the Sixth World Congress on the Square of Opposition, held in Crete in 2018, developing an interdisciplinary exploration of the theory. Chapter authors explore subjects such as Aristotle’s ontological square, logical oppositions in Avicenna’s hypothetical logic, and the power of the square of opposition to solve theological problems regarding predestination and theodicy. Other topics covered include: Hegel’s opposition to diagrams De Morgan’s unpublished octagon of opposition turnstile figures of opposition institutional model-theoretic treatment of oppositions Lacan’s four formulas of sexuation the theory of oppositional poly-simplexes The Exoteric Square of Opposition will appeal to pure logicians, historians of logic, semioticians, philosophers, theologians, mathematicians, and psychoanalysts.
Data Mining and Knowledge Discovery with Evolutionary Algorithms
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
Artificial Evolution
This book constitutes the thoroughly refereed post-proceedings of the 7th International Conference on Artificial Evolution, EA 2005, held in Lille, France, in October 2005. The 26 revised full papers presented were carefully reviewed and selected from 78 submissions. The papers cover all aspects of artificial evolution: genetic programming, machine learning, combinatorial optimization, co-evolution, self-assembling, artificial life and bioinformatics.
Applications of Evolutionary Computing
Evolutionary computation (EC) techniques are e?cient nature-inspired pl- ning and optimization methods based on the principles of natural evolution and genetics. Due to their e?ciency and the simple underlying principles, these methods can be used for a large number of problems in the context of problem solving,optimization,andmachinelearning. Alargeandcontinuouslyincreasing number of researchers and practitioners make use of EC techniques in many - plication domains. The book at hand presents a careful selection of relevant EC applications combined with thorough examinations of techniques for a successful application of EC. The presented papers illustrate the current state of the art in the...
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
This book constitutes the refereed proceedings of the 11th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, EvoBIO 2013, held in Vienna, Austria, in April 2013, colocated with the Evo* 2013 events EuroGP, EvoCOP, EvoMUSART and EvoApplications. The 10 revised full papers presented together with 9 poster papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics in the field of biological data analysis and computational biology. They address important problems in biology, from the molecular and genomic dimension to the individual and population level, often drawing inspiration from biological systems in oder to produce solutions to biological problems.
Peacebuilding Paradigms
Peacebuilding is explained by combining interpretive frameworks (paradigms) that have evolved from the subfields of international relations and comparative politics.
Machine Learning and Knowledge Discovery in Databases
Annotation. This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2010, held in Barcelona, Spain, in September 2010. The 120 revised full papers presented in three volumes, together with 12 demos (out of 24 submitted demos), were carefully reviewed and selected from 658 paper submissions. In addition, 7 ML and 7 DM papers were distinguished by the program chairs on the basis of their exceptional scientific quality and high impact on the field. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. A topic widely explored from both ML and DM perspectives was graphs, with motivations ranging from molecular chemistry to social networks.
