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21st IEEE International Symposium on Computational Intelligence and Informatics

作者： Rozgonyi, Balint Tamas Gyongyossy, Natabara Mate Korcsok, Beata Botzheim, Janos Budapest Univ Technol & Econ Fac Mech Engn Dept Mechatron Opt & Mech Engn Informat 4-6 Bertalan Lajos St H-1111 Budapest Hungary

ISBN: (纸本)9781665426848

With the advancement of social artificial agents the need for correct understanding of sentiment is growing. In this paper we propose a method for building a context-less word-level emotional model of words in the Hungarian language based on Russell's Circumpex model of affect. By utilizing bacterial evolutionary algorithm for feature selection, a method for efficient web-based annotation is proposed. Using the latent information of word embeddings multi-layer perceptron networks are trained to realize an interpolative function of two-dimensional emotion vectors over the embedding space. Dimensionality reduction via correlation analysis is also discussed.

关键词： bacterial evolutionary algorithm Feature Selection Russell Emotional Model Word2Vec Word Sentiment Interpolation

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Interactive bacterial evolutionary algorithm for Work Pace Optimization of Cobots 20

Interactive Bacterial Evolutionary Algorithm for Work Pace O...

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20th IEEE International Symposium on Computational Intelligence and Informatics (CINTI)

作者： Gyongyossy, Natabara Mate Domonkos, Mark Botzheim, Janos Budapest Univ Technol & Econ Dept Mechatron Opt & Mech Engn Informat Fac Mech Engn 4-6 Bertalan Lajos St H-1111 Budapest Hungary

ISBN: (纸本)9781728183398

As cobots become more popular in manufacturing, the close cooperation between the robot and the human operator becomes more complex. This paper proposes a method for optimizing the robot's work pace by interactive bacterial evolutionary algorithm. One of the main contributions is the interactivity of the optimization via the operator's feedback. Beside the operator's subjective evaluation, heart rate signals are also measured. The paper focuses mainly on the concept of this method tested with the help of some volunteers. Preliminary tests show that the algorithm is able to find comfortable configurations with less then 1% of them evaluated.

关键词： human-robot interaction ergonomics work pace bacterial evolutionary algorithm cobot

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Cancer Prediction Through a bacterial evolutionary algorithm Based Adaptive Weighted Fuzzy C-Means Approach

Cancer Prediction Through a Bacterial Evolutionary Algorithm...

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International Conference on Computer, Communication and Computational Sciences (IC4S)

作者： Sangeetha, M. Karthikeyan, N. K. Tamijeselvy, P. Nachammai, M. SKCT IT Dept Coimbatore Tamil Nadu India CIT CSE & IT Dept Coimbatore Tamil Nadu India SKCT CSE Dept Coimbatore Tamil Nadu India SKACAS CS Dept Coimbatore Tamil Nadu India

ISBN: (纸本)9789811303418;9789811303401

Clustering of tumor plays a significant part in classifying malignancies from carcinoma genetic data and hence is introduced to deal among the classification problem. It is used in critical applications like cancer treatment for diagnosis and prognosis, analysis of gene expression and related areas. In earlier research works, various tumor clustering schemes were presented based on the single clustering systems and implemented successfully to a variety of biomolecular data for cancer class detection. But, it suffered from some drawbacks similar to starvation of stability, accuracy, and robustness. The ensemble grouping schemes are introduced to overcome these limitations. In this research work, efficient dimensionality reduction is done by using Enhanced Independent Component Analysis (EICA) and effective Feature Selection (FS) using Geometric Particle Swarm Optimization (GPSO) are used. Finally, the competent Adaptive Weighted Fuzzy C-Means Clustering (AWFCM) with metaheuristic optimization scheme of bacterial evolutionary algorithm (BEA) is also proposed. It improves the performance of tumor clustering of biomolecular data. The performance of various ensemble clustering schemes is evaluated based on the efficient feature selection methods.

关键词： Bi-clustering Bayesian principal component analysis (Bi-BPCA) Weighted fuzzy C-Means bacterial evolutionary algorithm

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Fuzzy Cognitive Maps and bacterial evolutionary algorithm Approach to Integrated Waste Management Systems

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2014年第4期18卷 538-548页

作者： Buruzs, Adrienn Hatwagner, Miklos Ferenc Koczy, Laszlo Tamas Szechenyi Istvan Univ Dept Environm Engn Egyet Ter 1 Gyor Hungary Szechenyi Istvan Univ Dept Informat Technol Gyor Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat Budapest Hungary

Sustainable waste management systems necessarily include many interacting factors. Due to the complexity and uncertainties occurring in sustainable waste management systems, we propose the use of Fuzzy Cognitive Maps (FCM) and bacterial evolutionary algorithm (BEA) [1] to support the planning and decision making process of integrated systems, as the combination of methods FCM and BEA seems to be suitable to model such complex mechanisms as Integrated Waste Management Systems (IWMS). This paper is an attempt to assess the sustainability of the IWMS in a holistic approach. While the FCM model represents the IWMS as a whole, the BEA is used for parameter optimization and identification. An interpretation of the results obtained by the FCM for the actual regional IWMS is also presented. We have obtained some surprising results, contradicting the general assumptions in the literature concerning the relative importance of constituting components in waste management systems.

关键词： integrated waste management system sustainability factors fuzzy cognitive map bacterial evolutionary algorithm optimization

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Global stability of fuzzy cognitive maps

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NEURAL COMPUTING & APPLICATIONS 2023年第10期35卷 7283-7295页

作者： Harmati, Istvan A. Hatwagner, Miklos F. Koczy, Laszlo T. Szechenyi Istvan Univ Dept Math & Comp Sci Egyet Ter 1 H-9026 Gyor Hungary Szechenyi Istvan Univ Dept Informat Technol Egyet Ter 1 H-9026 Gyor Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat Magyartudosok Korutja 2 H-1117 Budapest Hungary

Complex systems can be effectively modelled by fuzzy cognitive maps. Fuzzy cognitive maps (FCMs) are network-based models, where the connections in the network represent causal relations. The conclusion about the system is based on the limit of the iteratively applied updating process. This iteration may or may not reach an equilibrium state (fixed point). Moreover, if the model is globally asymptotically stable, then this fixed point is unique and the iteration converges to this point from every initial state. There are some FCM models, where global stability is the required property, but in many FCM applications, the preferred scenario is not global stability, but multiple fixed points. Global stability bounds are useful in both cases: they may give a hint about which parameter set should be preferred or avoided. In this article, we present novel conditions for the global asymptotical stability of FCMs, i.e. conditions under which the iteration leads to the same point from every initial vector. Furthermore, we show that the results presented here outperform the results known from the current literature.

关键词： Fuzzy cognitive map (FCM) Stability Fixed point Convergence of fuzzy cognitive map bacterial evolutionary algorithm

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A synthetic biology approach for the design of genetic algorithms with bacterial agents

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INTERNATIONAL JOURNAL OF PARALLEL EMERGENT AND DISTRIBUTED SYSTEMS 2021年第3期36卷 275-292页

作者： Gargantilla Becerra, A. Gutierrez, M. Lahoz-Beltra, R. Ctr Nacl Biotecnol CSIC Madrid Dept Syst Biol Madrid Spain Univ Diego Portales Escuela Informat & Telecomunicac Santiago Chile Complutense Univ Madrid Madrid Fac Biol Sci Dept Biodivers Ecol & Evolut Biomath Madrid Spain

Bacteria have been a source of inspiration for the design of evolutionary algorithms. At the beginning of the twentieth century synthetic biology was born, a discipline whose goal is the design of biological systems that do not exist in nature, for example, programmable synthetic bacteria. In this paper, we introduce as a novelty the designing of evolutionary algorithms where all the steps are conducted by synthetic bacteria. To this end, we designed a genetic algorithm, which we have named BAGA, illustrating its utility solving simple instances of optimisation problems such as function optimisation, 0/1 knapsack problem, Hamiltonian path problem. The results obtained open the possibility of conceiving evolutionary algorithms inspired by principles, mechanisms and genetic circuits from synthetic biology. In summary, we can conclude that synthetic biology is a source of inspiration either for the design of evolutionary algorithms or for some of their steps, as shown by the results obtained in our simulation experiments.

关键词： bacterial evolutionary algorithm synthetic bacteria bacterial agents Gro cell programming language

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A Study on Solving Single Stage Batch Process Scheduling Problems with an evolutionary algorithm Featuring bacterial Mutations 17th

A Study on Solving Single Stage Batch Process Scheduling Pro...

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17th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Hegyhati, Mate Osz, Oliver Hatwagner, Miklos Szechenyi Istvan Univ H-9026 Gyor Hungary

ISBN: (纸本)9783319912530;9783319912523

The short term scheduling of batch processes is an active research field of chemical engineering, that has been addressed by many different techniques over the last decades. These approaches, however, are unable to solve long-term scheduling problems due their size, and the vast number of discrete decisions they entail. evolutionary algorithms already proved to be efficient for some classes of large scheduling problems, and recently, the utilization of bacterial mutations has shown promising results on other fields. In this paper, an evolutionary algorithm featuring bacterial mutation is introduced to solve a case study of a single stage product scheduling problem. The solution performance of the algorithm was compared to a method from the literature. The results indicate that the proposed approach can find the optimal solution under relatively short execution times.

关键词： Single stage product scheduling bacterial evolutionary algorithm

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Improved Behavioral Analysis of Fuzzy Cognitive Map Models 17th

Improved Behavioral Analysis of Fuzzy Cognitive Map Models

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17th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Hatwagner, Miklos F. Vastag, Gyula Niskanen, Vesa A. Koczy, Laszlo T. Szechenyi Istvan Univ Dept Informat Technol Gyor Hungary Szechenyi Istvan Univ Dept Leadership & Org Commun Gyor Hungary Univ Helsinki Dept Econ & Management Helsinki Finland Szechenyi Istvan Univ Dept Informat Technol Gyor Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat Budapest Hungary

ISBN: (纸本)9783319912622;9783319912615

Fuzzy CognitiveMaps (FCMs) are widely applied for describing the major components of complex systems and their interconnections. The popularity of FCMs ismostly based on their simple system representation, easy model creation and usage, and its decision support capabilities. The preferable way of model construction is based on historical, measured data of the investigated system and a suitable learning technique. Such data are not always available, however. In these cases experts have to define the strength and direction of causal connections among the components of the system, and their decisions are unavoidably affected by more or less subjective elements. Unfortunately, even a small change in the estimated strength may lead to significantly different simulation outcome, which could pose significant decision risks. Therefore, the preliminary exploration of model `sensitivity' to subtle weight modifications is very important to decision makers. This way their attention can be attracted to possible problems. This paper deals with the advanced version of a behavioral analysis. Based on the experiences of the authors, their method is further improved to generate more life-like, slightly modified model versions based on the original one suggested by experts. The details of the method is described, its application and the results are presented by an example of a banking application. The combination of Pareto-fronts and bacterial evolutionary algorithm is a novelty of the approach.

关键词： Banking Fuzzy Cognitive Maps Model uncertainty Multi-objective optimization bacterial evolutionary algorithm

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Evaluation of Waste Management Systems Using Fuzzy Cognitive Maps and Optimization

Evaluation of Waste Management Systems Using Fuzzy Cognitive...

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Asian Control Conference

作者： Adrienn Buruzs Miklos F. Hatwagner Peter Foldesi Laszlo T. Koczy Dept. of Environmental Engineering Szechenyi Istvan University Dept. of Information Technology Szechenyi Istvan University Dept. of Logistics Szechenyi Istvan University

ISBN: (纸本)9781479978632

Integrated Waste Management Systems (IWMS) are very complex systems with a lot of uncertainty. These can be defined as the selection and application of suitable techniques, technologies and management programs to achieve waste management objectives and goals. In order to support the decision making process in waste management we propose the use of Fuzzy Cognitive Map (FCM) and bacterial evolutionary algorithm (BEA) methods since the combination of the FCM and BEA seem to be suitable to model complex mechanisms such as IWMS. While the FCM is formed for a chosen system by determining the concepts and their relationships, it is possible to quantitatively simulate the system considering its parameters. However, if the time series of the factors of the system are known, then the connection matrix of FCM, thus the causal relations among the parameters can be determined by optimization. This way a more objective description of IWMS can be given.

关键词： Integrated Waste Management System Fuzzy Cognitive Maps bacterial evolutionary algorithm Optimization

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Using Fuzzy Cognitive Map Approach to model the casual relationships in stakeholder management at companies 5

Using Fuzzy Cognitive Map Approach to model the casual relat...

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5th IEEE International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Susniene, D. Torma, A. Buruzs, A. Hatwagner, M. F. Koczy, L. T. Kaunas Univ Technol Fac Technol & Business K Donelaicio St 73 LT-44029 Kaunas Lithuania Szechenyi Istvan Univ Dept Environm Engn H-9026 Gyor Hungary Szechenyi Istvan Univ Dept Informat Tecnol H-9026 Gyor Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat Budapest Hungary

ISBN: (纸本)9781479972807

The aim of this paper is to investigate the operation of a Stakeholder Relationship Management System (SRMS) as a method for business management and project support by fuzzy approach. The criteria defined in connection with the SRMS will be modelled by using the Fuzzy Cognitive Map (FCM) approach in order to define the causality and weights of interconnections between the factors and to support decision making in that way.

关键词： Stakeholder Relationship Management System Fuzzy Cognitive Map bacterial evolutionary algorithm Factor Reduction Model

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