Roman Senkerik

Analytical Programming - a Novel Approach for Evolutionary Synthesis of Symbolic Structures

This chapter discusses an alternative approach for symbolic structures and solutions synthesis and demonstrates a comparison with other methods, for example Genetic Programming (GP) or Grammatical Evolution (GE). Generally, there are two well known methods, which can be used for symbolic structures synthesis by means of computers. The first one is called GP and the other is GE. Another interesting research was carried out by Artificial Immune Systems (AIS) or/and systems, which do not use tree structures like linear GP and other similar algorithm like Multi Expression Programming (MEP), etc. In this chapter, a different method called Analytic Programming (AP), is presented. AP is a grammar free algorithmic superstructure, which can be used by any programming language and also by any arbitrary Evolutionary Algorithm (EA) or another class of numerical optimization method. This chapter describes not only theoretical principles of AP, but also its comparative study with selected well known case examples from GP as well as applications on synthesis of: controller, systems of deterministic chaos, electronics circuits, etc. For simulation purposes, AP has been co-joined with EA’s like Differential Evolution (DE), Self-Organising Migrating Algorithm (SOMA), Genetic Algorithms (GA) and Simulated Annealing (SA). All case studies has been carefully prepared and repeated in order to get valid statistical data for proper conclusions. The term symbolic regression represents a process during which measured data sets are fitted, thereby a corresponding mathematical formula is obtained in an analytical way. An output

Designing PID Controller For DC Motor System By Means Of Enhanced PSO Algorithm With Discrete Chaotic Lozi Map.

The main aim of this paper is the utilization of discrete chaotic Lozi map based chaos number generator to enhance the performance of PSO algorithm. This paper presents the results of research, in whichchaos enhanced PSO algorithm is used to design an optimal PID controller for DC motor system. Obtained results are compared with other non-heuristic and heuristic methods.

Chaos Driven Evolutionary Algorithm for the Traveling Salesman Problem

Donald Davendra1∗, Ivan Zelinka1, Roman Senkerik2 and Magdalena Bialic-Davendra3 1Department of Informatics, Faculty of Electrical Engineering and Computing Science, Technical University of Ostrava, Tr. 17. Listopadu 15, Ostrava 2Department of Informatics and Artificial Intelligence, Faculty of Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin 76001 3Department of Finance and Accounting, Faculty of Management and Economics, Mostni 5139, Zlin 76001 Czech Republic

Modern Trends and Techniques in Computer Science

This book is based on the research papers presented in the 3rd Computer Science On-line Conference 2014 (CSOC 2014).The conference is intended to provide an international forum for discussions on the latest high-quality research results in all areas related to Computer Science. The topics addressed are the theoretical aspects and applications of Artificial Intelligences, Computer Science, Informatics and Software Engineering. The authors provide new approaches and methods to real-world problems, and in particular, exploratory research that describes novel approaches in their field. Particular emphasis is laid on modern trends in selected fields of interest. New algorithms or methods in a variety of fields are also presented. This book is divided into three sections and covers topics including Artificial Intelligence, Computer Science and Software Engineering. Each section consists of new theoretical contributions and applications which can be used for the further development of knowledge of everybody who is looking for new knowledge or new inspiration for further research.

Study On Swarm Dynamics Converted Into Complex Network.

In this study it is presented a summarization of our research of possible ways of creating of complex networks from the inner dynamics of Swarm Intelligence based algorithms. The particle swarm optimization algorithm and the firefly algorithm are studied in this paper. Several methods of complex network creation are proposed and discussed alongside with possibilities for future research and application.

Evolutionary Synthesis Of Control Law For Higher Periodic Orbits Of Chaotic Logistic Equation.

This research deals with a synthesis of control law for selected discrete chaotic system by means of analytic programming. The novelty of the approach is that a tool for symbolic regression – analytic programming is used for the purpose of stabilization of higher periodic orbits – oscillations between several values of chaotic system. The paper consists of the descriptions of analytic programming as well as chaotic system and used blackbox type cost function. For experimentation, Self-Organizing Migrating Algorithm (SOMA) with analytic programming and Differential evolution (DE) as second algorithm for meta-evolution were used.

Scheduling The Flow Shop With Blocking Problem With The Chaos-Induced Discrete Self Organising Migrating Algorithm.

The dissipative Lozi chaotic map is embedded in the Discrete Self OrganisingMigrating Algorithm (DSOMA) algorithm, as a pseudorandom number generator (PRNG). This novel chaotic based algorithm is applied to the flow shop with blocking scheduling problem. The algorithm is tested on the Taillard problem sets and compared favourably with published heuristics.

Converting PSO dynamics into complex network - Initial study

In this paper it is presented the initial study on the possibility of capturing the inner dynamic of Particle Swarm Optimization algorithm into a complex network structure. Inspired in previous works there are two different approaches for creating the complex network presented in this paper. Visualizations of the networks are presented and commented. The possibilities for future applications of the proposed design are given in detail.

Analytical programming with extended individuals

This paper proposes a new technique for the estimation of values of constants in programs synthesized by Analytical Programming (AP). Proposed technique divides the features of an individual in Evolutionary Algorithm (EA) into two parts – program part and constant part. Features in program part are mapped to synthesized program and features in constant part are used as constant values. AP with implementation of this technique is tested on four benchmark functions – Quintic, Sextic, 3Sine and 4Sine.

Software Engineering in Intelligent Systems

This volume is based on the research papers presented in the 4th Computer Science On-line Conference. The volume Software Engineering in Intelligent Systems presents new approaches and methods to real-world problems, and in particular, exploratory research that describes novel approaches in the field of Software Engineering. Particular emphasis is laid on modern trends in selected fields of interest. New algorithms or methods in a variety of fields are also presented. The Computer Science On-line Conference (CSOC 2015) is intended to provide an international forum for discussions on the latest high-quality research results in all areas related to Computer Science. The addressed topics are the theoretical aspects and applications of Computer Science, Artificial Intelligences, Cybernetics, Automation Control Theory and Software Engineering.