Results 1 to 10 of about 131,785 (256)
(K − 1)-Kernels In Strong K-Transitive Digraphs [PDF]
Discussiones Mathematicae Graph Theory, 2015 Let D = (V (D),A(D)) be a digraph and k ≥ 2 be an integer. A subset N of V (D) is k-independent if for every pair of vertices u, v ∈ N, we have d(u, v) ≥ k; it is l-absorbent if for every u ∈ V (D) − N, there exists v ∈ N such that d(u, v) ≤ l.
Wang Ruixia
doaj +8 more sources
International Journal of Mathematics and Mathematical Sciences, 2009 In this paper we present equivalent characterizations of k-Kernel symmetric Matrices. Necessary and sufficient conditions are determined for a matrix to be k-Kernel Symmetric. We give some basic results of kernel symmetric matrices.
A. R. Meenakshi, D. Jaya Shree
doaj +2 more sources
The depression of a graph and k-kernels
Discussiones Mathematicae Graph Theory, 2014 An edge ordering of a graph G is an injection f : E(G) → R, the set of real numbers. A path in G for which the edge ordering f increases along its edge sequence is called an f-ascent ; an f-ascent is maximal if it is not contained in a longer f-ascent ...
Schurch Mark, Mynhardt Christine
doaj +2 more sources
Generalized Symmetric Neutrosophic Fuzzy Matrices [PDF]
Neutrosophic Sets and Systems, 2023 We develop the concept of range symmetric Neutrosophic Fuzzy Matrix and Kernel symmetric Neutrosophic Fuzzy Matrix analogous to that of an EP –matrix in the complex field. First we present equivalent characterizations of a range symmetric matrix and then
M. Anandhkumar +3 more
doaj +1 more source
Electronic Journal of Plant Breeding, 2022 Two crosses in F3 generation were studied for their variability, correlation and path analysis. The cross VRI 8 × K6 had better mean performance in all traits with very good pod and kernel yield per plant with mean of 36.59 g and 22.56 g, respectively ...
P. Ananth Kannappan1, PL. Viswanathan2*, N. Manivannan3 and L. Rajendran2
doaj +1 more source
Kernel Probabilistic K-Means Clustering
Sensors, 2021 Kernel fuzzy c-means (KFCM) is a significantly improved version of fuzzy c-means (FCM) for processing linearly inseparable datasets. However, for fuzzification parameter m=1, the problem of KFCM (kernel fuzzy c-means) cannot be solved by Lagrangian ...
Bowen Liu +4 more
doaj +1 more source
Silhouette Analysis for Performance Evaluation in Machine Learning with Applications to Clustering
Entropy, 2021 Grouping the objects based on their similarities is an important common task in machine learning applications. Many clustering methods have been developed, among them k-means based clustering methods have been broadly used and several extensions have ...
Meshal Shutaywi, Nezamoddin N. Kachouie
doaj +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Kernel-driven models provide an effective way for correcting the thermal radiation directionality effect. Under a general kernel-driven modeling framework proposed by Cao et al., by using three fixed-width hotspot kernels, and considering whether ...
Xiangyang Liu +3 more
doaj +1 more source
K-MACE and Kernel K-MACE Clustering
IEEE Access, 2020 Determining the correct number of clusters (CNC) is an important task in data clustering and has a critical effect on nalizing the partitioning results. K-means is one of the popular methods of clustering that requires CNC.
Soosan Beheshti +2 more
doaj +1 more source
Jurnal Teknologi Informasi dan Ilmu Komputer, 2021 Merebaknya kasus Covid-19 di Indonesia telah memunculkan berbagai macam topik penelitian yang dilakukan oleh para peneliti di berbagai bidang dan dari bermacam institusi.
Budi Nugroho
doaj +1 more source