MENDEL is an open access international journal dedicated for rapid publication of high-quality, peer-reviewed research articles in fields covered by Evolutionary Computation, Genetic Programming, Swarm Intelligence, Neural Networks, Deep Learning, Fuzzy Logic, Big Data, Chaos, Bayesian Methods, Optimization, Intelligent Image Processing, and Bio-inspired Robotics.

The journal is fully open access, meaning that all articles are available on the internet to all users immediately upon publication (Gold Open Access). The journal is published by the Institute of Automation and Computer Science of the Brno University of Technology.

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Editor in chief: doc. Ing. Radomil Matoušek, PhD.
ISSN: 1803-3814 (print)
ISSN: 2571-3701 (online)
Homepage: https://mendel-journal.org/

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Recent Submissions

  • Minimum-Volume Covering Ellipsoids: Improving the Efficiency of the Wolfe-Atwood Algorithm for Large-Scale Instances by Pooling and Batching 

    Kudela, Jakub (Institute of Automation and Computer Science, Brno University of Technology, 2019-12-20)
    The Minimum-Volume Covering Ellipsoid (MVCE) problem is an important optimization problem that comes up in various areas of engineering and statistics. In this paper, we improve the state-of-the-art Wolfe-Atwood algorithm ...
  • How to Burn a Network or Spread Alarm 

    Simon, Marek; Huraj, Ladislav; Dirgova Luptakova, Iveta; Pospichal, Jiri (Institute of Automation and Computer Science, Brno University of Technology, 2019-12-20)
    This paper compares centrality indices usage within a heuristic method for a fast spread of alarm, or crucial information. Such indices can be used as a core part within more sophisticated optimisation methods, which should ...
  • A Survey on Artificial Intelligence in Malware as Next-Generation Threats 

    Thanh, Cong Truong; Zelinka, Ivan (Institute of Automation and Computer Science, Brno University of Technology, 2019-12-20)
    Recent developments in Artificial intelligence (AI) have a vast transformative potential for both cybersecurity defenders and cybercriminals. Anti-malware solutions adopt intelligent techniques to detect and prevent threats ...
  • Self-Organizing Migrating Algorithm Pareto 

    Diep, Quoc Bao; Zelinka, Ivan; Das, Swagatam (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    In this paper, we propose a new method named Pareto-based self-organizing migrating algorithm (SOMA Pareto), in which the algorithm is divided into the Organization, Migration, and Update processes. The important key in ...
  • Comparison of Evolutionary Development of Cellular Automata Using Various Representations 

    Bidlo, Michal (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    A comparative study is presented regarding the evolutionary design of complex multi-state cellular automata. In particular, two-dimensional cellular automata will be considered in combination with pattern development problem ...
  • Modeling of Complex Systems by Means of Partial Algebras 

    Bila, Jiri; Rodríguez, Ricardo Jorge; Novak, Martin (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    Complex systems are very hard to describe by some unified language and calculus. In cases when their nature is very heterogeneous is possible to use with advantage state description. Formalization of operations on the set ...
  • Efficient Computation of Fitness Function for Evolutionary Clustering 

    Muravyov, Sergey; Antipov, Denis; Buzdalova, Arina; Filchenkov, Andrey (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    Evolutionary algorithms (EAs) are random search heuristics which can solve various optimization problems. There are plenty of papers describing different approaches developed to apply evolutionary algorithms to the clustering ...
  • Hybrid Symbolic Regression with the Bison Seeker Algorithm 

    Merta, Jan (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    This paper focuses on the use of the Bison Seeker Algorithm (BSA) in a hybrid genetic programming approach for the supervised machine learning method called symbolic regression. While the basic version of symbolic regression ...
  • Simulation-Based Rail Traffic Optimizations Applying Multicriterial Evaluations of Variants 

    Bažant, Michael; Kavička, Antonín; Diviš, Roman; Varga, Michal (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    The contribution pays attention to assessing a selected method related to multicriterial evaluations of variants. That method is exploited for supporting automatized decision-making processes related to special operational ...
  • Load Frequency Control of HVDC Link Interconnected Power System Using Genetic Algorithm 

    Chanana, Saurabh; Kumar, Saurabh (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    Advances in power electronics have improved grid support functions such as tie-line power control and frequency control, making renewable generation and High Voltage DC (HVDC) links more common in power system applications. ...
  • On the Leader Selection in the Self-Organizing Migrating Algorithm 

    Tomaszek, Lukas; Zelinka, Ivan; Chadli, Mohammed (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    In this article, a novel leader selection strategy for the self-organizing migrating algorithm is introduced. This strategy replaces original AllToOne and AllToRand strategies. It is shown and statistically tested, that ...
  • Ant Colony Optimisation for Performing Computational Task in Cellular Automata 

    Bidlo, Michal; Korgo, Jakub (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    A method is presented for the design of cellular automata rules by means of ant algorithms. In particular, Elitist Ant System and a~modified MAX-MIN Ant System are applied to search for transition functions of 1D cellular ...
  • An Ensemble-Based Malware Detection Model Using Minimum Feature Set 

    Zelinka, Ivan; Amer, Eslam (Institute of Automation and Computer Science, Brno University of Technology, 2019-12-20)
    Current commercial antivirus detection engines still rely on signature-based methods. However, with the huge increase in the number of new malware, current detection methods become not suitable. In this paper, we introduce ...
  • InterRC: An Inter-Resources Collaboration Heuristic for Scheduling Independent Tasks on Heterogeneous Distributed Environments 

    Khiat, Abdelhamid; Tari, Abdelkamel (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    The independent task scheduling problem in distributed computing environments with makespan optimization as an objective is an NP-Hard problem. Consequently, an important number of approaches looking to approximate the ...
  • Predicting the Spread of Malware Outbreaks Using Autoencoder Based Neutral Networks 

    Gopika, Bhardwaj; Rashi, Yadav (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    Malware Outbreaks are pervasive in today's digital world. However, there is a lack of awareness on part of general public on how to safeguard against such attacks and a need for increased cooperation between various national ...
  • Spiral Extrusion Die Design using Modified Differential Evolution Algorithm 

    Pluhacek, Michal; Hrdy, Michal; Viktorin, Adam; Kadavy, Tomas; Senkerik, Roman (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    In this work, a spiral extrusion die for industrial production of plastic foil has been designed using a modified differential evolution algorithm. The proposed method managed to provide a die design that was compliant ...
  • Properties of Simple and Generalized Laguerre Functions for Time-delay System Approximations 

    Zsitva, Norbert (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    The properties of the simple and generalized Laguerre functions for time-invariant system approximations are discussed. The expressions for these functions are presented and the differences between them are shown. The ...
  • Unconventional Methods in Voynich Manuscript Analysis 

    Zelinka, Ivan; Zmeskal, Oldrich; Windsor, Leah; Cai, Zhiqiang (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    This paper discusses the possible use of unconventional algorithms on analysis and categorization of the unknown text, including documents written in unknown languages. Scholars have identied about ten famous manuscripts, ...
  • Evolving Predictions for Executive Pay Features in Board Networks 

    Hauptman, Ami; Benbassat, Amit; Rosenboim, Rosit (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    Numerous recent studies in finance literature have shown that board networks are an important inter-corporate setting, influencing corporate decisions made by the board of directors, for example the determination of executive ...
  • Machine Learning Blunts the Needle of Advanced SQL Injections 

    Volkova, Marina; Chmelar, Petr; Sobotka, Lukas (Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24)
    SQL injection is one of the most popular and serious information security threats. By exploiting database vulnerabilities, attackers may get access to sensitive data or enable compromised computers to conduct further network ...

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