Searching for just a few words should be enough to get started. If you need to make more complex queries, use the tips below to guide you.
Purchase individual online access for 1 year to this journal.
Price: EUR 410.00Impact Factor 2024: 0.4
Fundamenta Informaticae is an international journal publishing original research results in all areas of theoretical computer science. Papers are encouraged contributing:
- solutions by mathematical methods of problems emerging in computer science
- solutions of mathematical problems inspired by computer science.
Topics of interest include (but are not restricted to): theory of computing, complexity theory, algorithms and data structures, computational aspects of combinatorics and graph theory, programming language theory, theoretical aspects of programming languages, computer-aided verification, computer science logic, database theory, logic programming, automated deduction, formal languages and automata theory, concurrency and distributed computing, cryptography and security, theoretical issues in artificial intelligence, machine learning, pattern recognition, algorithmic game theory, bioinformatics and computational biology, quantum computing, probabilistic methods, & algebraic and categorical methods.
Authors: Latkowski, Rafał
Article Type: Research Article
Abstract: In this paper we present a method of data decomposition to avoid the necessity of reasoning on data with missing attribute values. This method can be applied to any algorithm of classifier induction. The original incomplete data is decomposed into data subsets without missing values. Next, methods for classifier induction are applied to these sets. Finally, a conflict resolving method is used to obtain final classification from partial classifiers. We provide an empirical evaluation of the …decomposition method accuracy and model size with use of various decomposition criteria on data with natural missing values. We present also experiments on data with synthetic missing values to examine the properties of proposed method with variable ratio of incompleteness. Show more
Keywords: data mining, rough sets, missing attribute values
Citation: Fundamenta Informaticae, vol. 54, no. 1, pp. 1-16, 2003
Authors: Peltier, Nicolas
Article Type: Research Article
Abstract: A method is proposed to construct decision procedures for various subclasses of first-order logic with equality. We define a notion of complexity of first-order terms and equations, and we propose semantic and syntactic criteria ensuring that existing refinements of the paramodulation calculus terminate on the considered clause sets. These refinements use reduction orderings, selection functions and simplification rules. Since they are sound and refutationally complete, the corresponding classes of formulae are decidable. Moreover, the automatic extraction …of models from saturated clause sets is also possible. A discussion and detailed comparisons with existing works in the field are provided, together with numerous examples and some undecidability results. Show more
Citation: Fundamenta Informaticae, vol. 54, no. 1, pp. 17-65, 2003
Authors: Polkowski, Lech
Article Type: Research Article
Abstract: In this work, we would like to discuss rough inclusions defined in Rough Mereology – a paradigm for approximate reasoning introduced by Polkowski and Skowron [20] – as a basis for common models for rough as well as fuzzy set theories. We would like to adhere to the point of view that tolerance (or, similarity) is the leading motif common to both theories and in this area paths between the two lie. To this end, we demonstrate that rough inclusions …(which represent a hierarchy of tolerance relations) induce rough set theoretic approximations as well as partitions and equivalence relations in the sense of fuzzy set theory. For completeness sake, we also discuss granulation mechanisms based on rough inclusions with applications to Rough–Neuro Computing and Computing with Words. These considerations are also carried out in specialized cases of Menger's as well as Łukasiewicz's rough inclusions introduced in the paper. Show more
Keywords: rough set theory, fuzzy set theory, rough mereology, rough inclusions, granular calculus
Citation: Fundamenta Informaticae, vol. 54, no. 1, pp. 67-88, 2003
Authors: Wojnarski, Marcin
Article Type: Research Article
Abstract: This paper presents a new model of an artificial neural network solving classification problems, called Local Transfer Function Classifier (LTF-C). Its architecture is very similar to this of the Radial Basis Function neural network (RBF), however it utilizes an entirely different learning algorithm. This algorithm is composed of four main parts: changing positions of reception fields, changing their sizes, insertion of new hidden neurons and removal of unnecessary ones during the training. The paper presents …also results of LTF-C application to three real-life tasks: handwritten digit recognition, credit approval and cancer diagnosis. LTF-C was able to solve each of these problems with better accuracy than most popular classification systems. Moreover, LTF-C was relatively small and fast. Show more
Keywords: neural network, classification, recognition, RBF
Citation: Fundamenta Informaticae, vol. 54, no. 1, pp. 89-105, 2003
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
USA
Tel: +1 703 830 6300
Fax: +1 703 830 2300
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
IOS Press
Nieuwe Hemweg 6B
1013 BG Amsterdam
The Netherlands
Tel: +31 20 688 3355
Fax: +31 20 687 0091
[email protected]
For editorial issues, permissions, book requests, submissions and proceedings, contact the Amsterdam office [email protected]
Inspirees International (China Office)
Ciyunsi Beili 207(CapitaLand), Bld 1, 7-901
100025, Beijing
China
Free service line: 400 661 8717
Fax: +86 10 8446 7947
[email protected]
For editorial issues, like the status of your submitted paper or proposals, write to [email protected]
如果您在出版方面需要帮助或有任何建, 件至: [email protected]