Due to the efficiency to handle uncertainty information, the single valued neutrosophic set is widely used in multicriteria decision-making. In MCDM, it is inevitable to measure the distance between two single valued neutrosophic sets. In this paper, an evidence distance for neutrosophic sets is proposed. There are two main contributions of this work. One is a new method to transform the single...

Distance Geometry puts the concept of distance at its center. The basic problem in distance geometry could be described as drawing an edge-weighted undirected graph in R for some given K such that the positions for adjacent vertices have distance which is equal to the corresponding edge weight. As we are unaware of any work in this field using any other norm but `2, we move some first steps usi...

To effectively optimize multi-objective logistics distribution path, the distance and distance related customer satisfaction factor are used as the objective function, a novel kruskal crossover genetic algorithm (KCGA) for multi-objective logistics distribution path optimization is proposed. To test the optimization results, the terminal distribution model and the virtual logistics system opera...

We consider the problem of defining and evaluating the distance between three–dimensional pattern P [1..m, 1..m, 1..m] of voxels and three–dimensional volume V [1..n, 1..n, 1..n] of voxels when also rotations of P are allowed. In particular, we are interested in finding the orientation and location of P with respect of V that gives the minimum distance. We consider several distance measures. Ou...

We consider the problem of defining and evaluating the distance between three–dimensional pattern P [1::m; 1::m; 1::m] of voxels and three–dimensional volume V [1::n; 1::n; 1::n] of voxels when also rotations of P are allowed. In particular, we are interested in finding the orientation and location of P with respect of V that gives the minimum distance. We consider several distance measures. Ou...

In this manuscript, a new form of distance function that can model spaces where a Mahalanobis distance cannot be assumed is proposed. Two novel learning algorithms are proposed to allow that distance function to be learnt, assuming only relativecomparisons training examples. This allows a distance function to be learnt in non-linear, discontinuous spaces, avoiding the need for labelled or quant...

Describing the similarity of time series as distance is the basis for most of data mining research. Existing studies on similarity distance is based on the ”point distance” without considering the geometric characteristics of time series, or is not a metric distance which doesn’t meet the triangle inequality and can’t be directly used in indexing and searching process. A method for time series ...

The stage at which processing of tactile distance occurs is still debated. We addressed this issue by implementing an adaptation-aftereffect paradigm with passive touch. We demonstrated the presence of a strong aftereffect, induced by the simultaneous presentation of pairs of tactile stimuli. After adaptation to two different distances, one on each hand, participants systematically perceived a ...

In the theory of belief functions, the approximation of a basic belief assignment (BBA) is for reducing the high computational cost especially when large number of focal elements are available. In traditional BBA approximation approaches, a focal element's own characteristics such as the mass assignment and the cardinality, are usually used separately or jointly as criteria for the removal of f...