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Complex network analysis of discrete self-organising migrating algorithm

Complex network analysis of discrete self-organising migrati...

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International conference on prediction, modeling and analysis of complex systems, NOSTRADAMUS 2014

作者： Davendra, Donald Zelinka, Ivan Senkerik, Roman Pluhacek, Michal VŠB - Technical University of Ostrava Faculty of Electrical Engineering and Computer Science 17 listopadu 15 Ostrava-Poruba708 33 Czech Republic Tomas Bata University in Zlin Faculty of Applied Informatics T.G. Masaryka 5555 Zlin760 01 Czech Republic

ISBN: (纸本)9783319074009

This research analyses the development of a complex network in the swarm based Discrete Self-Organising Migrating Algorithm (DSOMA). The main aim is to evaluate if a complex network is generated in DSOMA, and how the population can be evaluated when the objective is to optimise the flow shop scheduling with blocking problem. The population is evaluated as a complex network over a number of migrations, and different attributes such as adjacency graph, minimal cut, degree centrality, closeness centrality, betweenness centrality, Katz centrality, mean neighbour degree, k-Clique, k-Plan, k-Club, k-Clan and community graph plots are analysed. From the results, it can be concluded that an DSOMA population does behave like a complex network, and therefore can be analysed as such, in order to obtain information about population development. © Springer International Publishing Switzerland 2014

关键词： Complex networks

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Multi-chaotic differential evolution: A preliminary study

Multi-chaotic differential evolution: A preliminary study

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13th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2014

作者： Senkerik, Roman Pluhacek, Michal Zelinka, Ivan Davendra, Donald Kominková Oplatková, Zuzana Tomas Bata University in Zlin Faculty of Applied Informatics Nam T.G. Masaryka 5555 760 01 Zlin Czech Republic Technical University of Ostrava Faculty of Electrical Engineering and Computer Science 17. listopadu 15 708 33 Ostrava-Poruba Czech Republic

ISBN: (纸本)9783319071725

This research deals with the initial investigations on the concept of a multi-chaos-driven evolutionary algorithm Differential Evolution (DE). This paper is aimed at the embedding and alternating of set of two discrete dissipative chaotic systems in the form of chaos pseudo random number generator for DE. Repeated simulations were performed on the selected test function in higher dimensions. Finally, the obtained results are compared with canonical DE. © 2014 Springer International Publishing.

关键词： Optimization

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Performance analysis of torque motor systems with PID controllers tuned by Bacterial Foraging Optimization algorithms

Performance analysis of torque motor systems with PID contro...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications

作者： Radu-Emil Precup Andrei-Leonard Borza Mircea-Bogdan Radac Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

This paper deals with the optimal tuning of proportional-integral-derivative (PID) controllers for a pancake direct current (DC) torque motor system that belongs to a Diesel engine exhaust gas recirculation valve in automotive applications. The Bacterial Foraging Optimization (BFO) algorithms solve an optimization problem which targets the minimization of an objective function expressed as the weighted sum of overshoot plus the integral of squared control error, and the parameters of the PID controllers are the variables of the objective function. Our BFO algorithms are characterized by the validation of the position of bacteria only if the PID control system response is in a valid range. A digitally simulated case study which deals with the shaft angle control of a DC torque motor system is considered. The impact of four parameters of one BFO algorithm on the objective function values is discussed.

关键词： Linear programming Microorganisms Optimization Torque Control systems Tuning Algorithm design and analysis

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Querying 3D Mesh Sequences for Human Action Retrieval

Querying 3D Mesh Sequences for Human Action Retrieval

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International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT)

作者： Christos Veinidis Ioannis Pratikakis Theoharis Theoharis Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Department of Informatics and Telecommunications National and Kapodistrian University of Athens Trondheim Norway

In this paper, the unsupervised human action retrieval problem in 3D mesh sequences is addressed. An action is represented by a mesh sequence wherein each frame is represented by a static shape descriptor. Six state-of-the-art static descriptors are used to extract meaningful information of the mesh objects in the sequence. These descriptors are first examined in terms of similarity performance using Receiver Operating Characteristic (ROC) curves. Then, they are utilized in the action retrieval problem, where the query is a 3D mesh sequence. Each descriptor for an action, is considered as a multidimensional curve which traverses the corresponding points. The temporal similarity estimation is achieved by two variations of the descriptor's normalization in the context of Multidimensional Dynamic Time Warping. Experimental results are given for two standard datasets, one containing real data and another one containing artificial data.

关键词： Shape Three-dimensional displays Computational modeling Histograms Solid modeling Motion segmentation Standards

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A human geospatial predictive analytics framework with application to finding medically underserved areas

A human geospatial predictive analytics framework with appli...

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IEEE Symposium on Computational Intelligence in Big Data (CIBD)

作者： James M. Keller Andrew R. Buck Alina Zare Mihail Popescu Electrical and Computer Engineering Department University of Missouri Columbia MO USA Health Management and Informatics Department University of Missouri Columbia MO USA

Human geography is a concept used to indicate the augmentation of standard geographic layers of information about an area with behavioral variations of the people in the area. In particular, the actions of people can be attributed to both local and regional variations in physical (i.e., terrain) and human (e.g., income, political, cultural) variables. In this paper, we study the utility of a human geographic data cube coupled with computational intelligence as a means to predict conditions across a geographic area. This becomes a Big data problem. In this sense, we are using genotype information to predict phenotype states. We demonstrate the approach on the prediction of medically underserved areas in Missouri.

关键词： Training Biomedical imaging Artificial neural networks Geography Vectors Sociology Statistics

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Bacterial Foraging Optimization approach to the controller tuning for automotive torque motors

Bacterial Foraging Optimization approach to the controller t...

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IEEE International Symposium on Industrial Electronics (ISIE)

This paper proposes the Bacterial Foraging Optimization (BFO)-based tuning of controllers for a pancake DC torque motor in the framework of a Diesel engine exhaust gas recirculation valve as a representative automotive torque motor actuator. The validation of the position of bacteria only if the control system response is in a valid range is inserted in the BFO algorithm. PID and sliding mode controllers are optimally tuned by the BFO algorithm focused on solving an optimization problem that minimizes an objective function expressed as the weighted sum of overshoot plus the integral of squared error. The parameters of these two controllers belong to the vector variables of the objective function. A case study that deals with the shaft angle control of an automotive torque motor actuator is included to validate our approach by simulation results. The comparison of control system performance is carried out.

关键词： Microorganisms Optimization Tuning Torque DC motors Actuators Vectors

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Particle Swarm Optimization of fuzzy models for Anti-Lock Braking Systems

Particle Swarm Optimization of fuzzy models for Anti-Lock Br...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Radu-Emil Precup Marius-Csaba Sabau Claudia-Adina Dragos Mircea-Bogdan Radac Lucian-Ovidiu Fedorovici Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

This paper suggests a Particle Swarm Optimization (PSO) approach to the optimal tuning of fuzzy models for Anti-lock Braking Systems (ABSs). A set of ten local state-space models of the ABS is first obtained by the linearization of the nonlinear state-space model of the ABS process at ten operating points. The initial Takagi-Sugeno (T-S) fuzzy models are next obtained by the modal equivalence principle, namely by placing the local state-space models of the process in the rule consequents. The optimization problem targets the minimization of the objective function (OF) expressed as the mean squared modeling error, and the vector variable of the OF consists of the feet of the triangular input membership functions. A PSO algorithm solves the optimization problem and gives the optimal T-S fuzzy models. A set of real-time experimental results is included to validate the PSO approach and the optimal T-S fuzzy models for real-world ABS laboratory equipment.

关键词： Vectors Optimization Wheels Mathematical model Tuning Adaptation models State-space methods

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Multi-robot charged system search-based optimal path planning in static environments

Multi-robot charged system search-based optimal path plannin...

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IEEE International Symposium on Intelligent Control (ISIC)

作者： Radu-Emil Precup Emil M. Petriu Lucian-Ovidiu Fedorovici Mircea-Bogdan Radac Florin Dragan Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania University of Ottawa School of Electrical Engineering and Computer Science Ottawa ON Canada

This paper proposes an optimal path planning approach based on Charged System Search (CSS) algorithms. The approach is applied to multiple mobile robots on holonomic wheeled platforms. Optimization problems (o.p.s) are defined for each robot to minimize the weighted sum of four objective functions whose minimization targets four path planning objectives. The CSS algorithms are mapped onto the o.p.s considering that the fitness functions are the objective functions, the search spare is the solution space, the agents (charged particles) are the mobile robots, and the population of agents is the set of mobile robots. Therefore, the optimal solutions to the o.p.s are the optimal paths. The new path planning approach is validated by experiments, and a comparison with other nature-inspired optimization-based path planning approaches is given.

关键词： Path planning Sociology Statistics Collision avoidance Optimization Mobile robots

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Model-free tuning solution for sliding mode control of servo systems

Model-free tuning solution for sliding mode control of servo...

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Annual IEEE Systems Conference

作者： Radu-Emil Precup Mircea-Bogdan Radac Claudia-Adina Dragos Stefan Preitl Emil M. Petriu Department of Automation and Applied Informatics Politehnica University of Timisoara Timisoara Romania School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

This paper suggests a model-free tuning solution for a sliding mode control system (SMCS) structure dedicated to servo systems. The new SMCS structure is viewed in the framework of reference trajectory tracking using a first-order nonlinear dynamic system as a local approximation of the process model. The sliding mode control signal augments the control signal specific to a model-free PI control system (CS) structure in order to compensate for the estimation errors which affect the systematic design and performance. The derivatives in the local approximation of the process model are estimated numerically using a Savitzky-Golay filter to carry out both differentiation and smoothing. A simple design approach is proposed for the SMCS structure. The real-time experimental results concerning the speed control of a laboratory nonlinear DC servo system prove the performance improvement of the SMCS structure against a model-free PI CS structure.

关键词： Tuning Trajectory Process control Sliding mode control Servomotors Mathematical model Linear approximation

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Design and simulation of anti-collision RFID system based on SDMA-OFDM

Design and simulation of anti-collision RFID system based on...

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IEEE International Conference on Multimedia Computing and Systems (ICMCS)

作者： Hadjer Saadi Rachida Touhami Mustapha C.E. Yagoub LINS Faculty of Electronics and Informatics USTHB Bab Ezzouar Algeria School of Electrical Engineering and Computer Science University of Ottawa Ottawa Ontario Canada

This paper discusses the implementation of an efficient anti-collision algorithm for RFID systems. Conventional TDMA methods do not show a high efficiency and speediness in collision detection and do not take into account the spatial characteristics of tags distribution. By combining the TDMA (Time Division Multiple Access) and SDMA (Space Division Multiple Access) algorithms, the proposed approach takes into account the characteristics of the tag position in the reading area of the reader. Knowing that the SDMA method is based on the principle of Digital Beam Forming (DBF), we used the FFT and IFFT blocks to form the different beams and the OFDM technique to meet the orthogonality condition. We then divided the space into two subsets of beams and applied the TDMA method to detect any collision. The developed RFID anti-collision SDMA system has been coded by VHDL and simulated using the ISE software for FPGA implementation.

关键词： Multiaccess communication OFDM Demodulation Amplitude shift keying Radiofrequency identification Software Field programmable gate arrays

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