V
Vaclav Snasel
Researcher at Technical University of Ostrava
Publications - 725
Citations - 7514
Vaclav Snasel is an academic researcher from Technical University of Ostrava. The author has contributed to research in topics: Cluster analysis & Computer science. The author has an hindex of 33, co-authored 673 publications receiving 6216 citations. Previous affiliations of Vaclav Snasel include Yonsei University & University of Ostrava.
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BookDOI
Hybrid Artificial Intelligent Systems
TL;DR: The methodology for calculating distortion parameters of newly created attributes after both discretisation and binarisation of attributes for quantitative association rules mining has been proposed and the new application of MMASK for finding frequent sets in discovering quantitative association Rules with preserved privacy has been presented.
Journal ArticleDOI
Consumers’ Acceptance and Use of Information and Communications Technology: A UTAUT and Flow Based Theoretical Model
Saleh Alwahaishi,Vaclav Snasel +1 more
TL;DR: This research composes a new hybrid theoretical framework to identify the factors affecting the acceptance and use of Mobile Internet -as an ICT application- in a consumer context and incorporates eight constructs: Performance expectancy, Effort Expectancy, Facilitating Conditions, Social Influences, Perceived Value, Perception Playfulness, Attention Focus, and Behavioral intention.
Journal ArticleDOI
A Comprehensive Review on NSGA-II for Multi-Objective Combinatorial Optimization Problems
TL;DR: In this article, the authors provide an extensive review of NSGA-II for selected combinatorial optimization problems viz. assignment problem, allocation problem, travelling salesman problem, vehicle routing problem, scheduling problem, and knapsack problem.
Proceedings ArticleDOI
Comparison of Heuristics for Scheduling Independent Tasks on Heterogeneous Distributed Environments
TL;DR: An efficient heuristic method is proposed and then five popular heuristics for minimizing makespan and flowtime in heterogeneous distributed computing systems are compared.
Journal ArticleDOI
α-Fraction First Strategy for Hierarchical Model in Wireless Sensor Networks
TL;DR: An α-fraction first strategy was proposed to build a hierarchical model of wireless sensor networks that concerning the energy consumption and three algorithms were designed for determining the relay nodes in sensor networks, which can be used to construct a two-tier sensor network with fewer relay nodes.