Autonomous underwater vehicles (AUVs) are underwater robots which are able to perform certain tasks without the help of a human operator. The key skill of each AUV is the capability to avoid collisions. To this end, appropriate devices and software are necessary with the potential to detect obstacles and to take proper decisions from the point of view of both the task and safety...

The problem of the piecewise linear approximation of fuzzy numbers giving outputs nearest to the inputs with respect to the Euclidean metric is discussed. The results given in Coroianu et al. (Fuzzy Sets Syst 233:26–51, 2013) for the 1-knot fuzzy numbers are generalized for arbitrary n-knot (\(n\ge 2\)) piecewise linear fuzzy numbers. Some results on the existence and properties...

In a connected simple graph, the weighted Roman domination problem is considered at which the cost of positioning at each vertex is imposed in addition to the costs of potential deployments from a vertex to some of its neighboring vertices. Proper decision in practice is prone to a high degree of indeterminacy, mostly raised by unpredictable events that do not obey the rules and...

The assessment of strengths and weaknesses of a solver is often limited by the diversity of the cases where it is tested upon. As such, it is paramount to have a versatile tool which finds the problem instances where such a solver excels/fails. In this manuscript, we propose to use an evolutionary algorithm for creating this tool. To validate our approach, we conducted several...

Fuzzy variable weights comprehensive evaluation is investigated in the paper. Its necessity and principle are discussed. The complexity and weak effect of direct variable weights methods, which are the traditional ways, are illustrated. So the necessity of indirect variable weights methods is shown, which only need to determine a parameter p. To determine it, variable weights...

In this paper, K-means algorithm has been applied for distributed large data using hybrid clustering techniques. K-means is a simple and scalable algorithm which can be applied on large datasets. It is one of the well-known unsupervised clustering algorithms that fail in providing structured to unstructured data to enable extraction of valuable information. Peer-to-peer (P2P...

Computational fluid dynamic (CFD) simulations present numerous challenges in the domain of artificial intelligence. Computational time, resources and cost that can reach disproportional size before leading a simulation to its fully converged solution are one of the central issues in this domain. In this paper, we propose a novel algorithm that finds optimal parameter settings for...

In this paper, we study the improvement of a storage location strategy through the use of big data technology, including data collection, cluster analysis and association analysis, to improve order picking efficiency. A clustering algorithm is used to categorize the types of goods in orders. Classification is performed based on the turnover of goods, value, sales volume...

The aim of the paper is to extend the results concerning the Shannon entropy and Kullback–Leibler divergence in product MV-algebras to the case of R-norm entropy and R-norm divergence. We define the R-norm entropy of finite partitions in product MV-algebras and its conditional version and derive the basic properties of these entropy measures. In addition, we introduce the concept...

We explore systematic connections between weighted (semi-abstract) argumentation frames and t-norm-based fuzzy logics. To this aim we introduce the concept of argumentative immunity, as well as corresponding notions of argumentative soundness and completeness with respect to given sets of logical attack principles. For Gödel logic, a detailed proof of argumentative soundness and...

Differential evolution (DE) has been widely applied to complex global optimization problems. Different search strategies have been designed to find the optimum conditions in a fitness landscape. However, none of these strategies works well over all possible fitness landscapes. Since the fitness landscape associated with a complex global optimization problem usually consists of...

Identification of hidden relationships between domain attributes from different data sources is of great practical significance and forms an emerging field in data mining. However, currently there seldom exist any systematic methods that can effectively handle this problem, especially when dealing with imprecisely described associations. In this paper, a novel data-driven...

Assistive robots in ambient assisted living environments can be equipped with learning capabilities to effectively learn and execute human activities. This paper proposes a human activity learning (HAL) system for application in assistive robotics. An RGB-depth sensor is used to acquire information of human activities, and a set of statistical, spatial and temporal features for...

One aspect that has been poorly studied in multiple-valued logics, and in particular in Łukasiewicz logic, is the generation of instances of varying difficulty for evaluating, comparing and improving satisfiability solvers. With the ultimate goal of finding challenging benchmarks for Łukasiewicz satisfiability solvers, we start by defining a natural and intuitive class of clausal...

The so-called non-associative MV-algebras were introduced recently by the first author and J. Kühr in order to have an appropriate tool for certain logics used in expert systems where associativity of the binary operation is excluded, see, e.g., Botur and Halaš (Arch Math Log 48:243–255, 2009). Since implication is an important logical connective in practically every...

The paper presents a method for solving real fuzzy systems of linear equations with the usage of horizontal fuzzy numbers (HFNs). Based on the multidimensional RDM interval arithmetic and a fuzzy number in a parametric form, the definition of a horizontal fuzzy number with nonlinear left and right borders was given. Additionally, the paper presents the properties of basic...