Fundamenta Informaticae - Volume 176, issue 1

Authors: Dangalchev, Chavdar

Article Type: Research Article

Abstract: Creation and growth are very important in network analysis. In this article we propose one possible model for networks generation. The probabilities of new links are proportional to the expected closeness of the added node. We also propose a new characteristic of graphs - additional closeness, which measures the maximal closeness of a graph after adding a new link. Some properties of the additional closeness are explored. Three different ways of joining two networks are investigated.

Keywords: Networks generation, Networks growth, Graph vulnerability, Closeness, Residual closeness

DOI: 10.3233/FI-2020-1960

Citation: Fundamenta Informaticae, vol. 176, no. 1, pp. 1-15, 2020

Authors: Järvinen, Jouni | Radeleczki, Sándor

Article Type: Research Article

Abstract: We study multigranulation spaces of two equivalences. The lattice-theoretical properties of so-called “optimistic” and “pessimistic” multigranular approximation systems are given. We also consider the ordered sets of rough sets determined by these approximation pairs.

Keywords: Equivalence relation, multigranular approximation, definable set, rough set, coherence, tolerance relation, irredundant covering, atomistic Boolean lattice, completely distributive lattice, Dedekind–MacNeille completion

DOI: 10.3233/FI-2020-1961

Citation: Fundamenta Informaticae, vol. 176, no. 1, pp. 17-41, 2020

Authors: Liu, Liucheng | Yi, Wenmei | Yang, Qian | Peng, Hong | Wang, Jun

Article Type: Research Article

Abstract: Abstracted from the nested structure of biological cells with application on the modeling of economical processes, numerical P systems (in short, NP systems) as a kind of distributed parallel computation systems have been proposed. It has been proven that NP systems and variants are Turing universal for number accepting/generating devices and language generating device. However, universality of NP systems as function computing devices has not been established. Aiming at numerical P systems with thresholds (in short, TNP systems), small universality for computing functions is discussed in this paper. Six small universal function computing devices of TNP systems for two threshold …cases and working on three different modes are constructed, respectively. Show more

Keywords: membrane computing, numerical P systems with thresholds, small universality, function computing devices

DOI: 10.3233/FI-2020-1962

Citation: Fundamenta Informaticae, vol. 176, no. 1, pp. 43-59, 2020

Authors: Maschio, Samuele | Sambin, Giovanni

Article Type: Research Article

Abstract: We present here a new interpretation of topological concepts based on communication. The context that allows us to see this is that of basic pairs, the most elementary structures that allow to present topology. In particular, we prove that the subsets which can be communicated faithfully between the sides of a basic pair are exactly open subsets and closed subsets. We also prove that a relation between two sets of points can be communicated faithfully if and only if it is continuous or open. Finally we introduce new notions of point and of continuous function which are communicable.

Keywords: Topology, communication, basic pairs, constructive mathematics

DOI: 10.3233/FI-2020-1963

Citation: Fundamenta Informaticae, vol. 176, no. 1, pp. 61-78, 2020

Authors: Zhao, Chenyue | Alizadeh, Hosein | Minaei, Behrouz | Mohamadpoor, Majid | Parvin, Hamid | Mahmoudi, Mohammad Reza

Article Type: Research Article

Abstract: This paper studies the cluster ensemble selection problem for unsupervised learning. Given a large ensemble of clustering solutions, our goal is to select a subset of solutions to form a smaller yet better performing cluster ensemble than using all available solutions. The common way of aggregating the chosen solutions is accumulating the information of the selected results to a similarity matrix. This paper suggests transforming the similarity matrix to a modularity matrix and then applying a new consensus function which optimizes modularity measure in it. We represent the modularity maximization problem as a 0-1 quadratic program which can be exactly …solved for small datasets. We also established a new greedy algorithm, namely sum linkage, to optimize the objective function specially for large scale datasets in a very short time. We show that the proposed consensus partition gets much closer to the actual cluster structure than the partitions obtained from the direct application of common cluster ensemble methods. The promising results compared with other most cited consensus functions show the excellent efficiency of the proposed method. Show more

Keywords: Cluster Ensemble Selection, Modularity Optimization, Mathematical Programming, Sum Linkage Algorithm

DOI: 10.3233/FI-2020-1964

Citation: Fundamenta Informaticae, vol. 176, no. 1, pp. 79-102, 2020