Browse

You are looking at 1 - 10 of 3,236 items for :

  • Electrical Engineering x
Clear All
Open access

M. Javaid, M. Abbas, Jia-Bao Liu, W. C. Teh and Jinde Cao

Abstract

A topological property or index of a network is a numeric number which characterises the whole structure of the underlying network. It is used to predict the certain changes in the bio, chemical and physical activities of the networks. The 4-layered probabilistic neural networks are more general than the 3-layered probabilistic neural networks. Javaid and Cao [Neural Comput. and Applic., DOI 10.1007/s00521-017-2972-1] and Liu et al. [Journal of Artificial Intelligence and Soft Computing Research, 8(2018), 225-266] studied the certain degree and distance based topological indices (TI’s) of the 3-layered probabilistic neural networks. In this paper, we extend this study to the 4-layered probabilistic neural networks and compute the certain degree-based TI’s. In the end, a comparison between all the computed indices is included and it is also proved that the TI’s of the 4-layered probabilistic neural networks are better being strictly greater than the 3-layered probabilistic neural networks.

Open access

Ryotaro Kamimura

Abstract

The present paper1 aims to propose a new type of information-theoretic method to maximize mutual information between inputs and outputs. The importance of mutual information in neural networks is well known, but the actual implementation of mutual information maximization has been quite difficult to undertake. In addition, mutual information has not extensively been used in neural networks, meaning that its applicability is very limited. To overcome the shortcoming of mutual information maximization, we present it here in a very simplified manner by supposing that mutual information is already maximized before learning, or at least at the beginning of learning. The method was applied to three data sets (crab data set, wholesale data set, and human resources data set) and examined in terms of generalization performance and connection weights. The results showed that by disentangling connection weights, maximizing mutual information made it possible to explicitly interpret the relations between inputs and outputs.

Open access

Parisa Rastin, Basarab Matei, Guénaël Cabanes, Nistor Grozavu and Younès Bennani

Abstract

Collaborative Clustering is a data mining task the aim of which is to use several clustering algorithms to analyze different aspects of the same data. The aim of collaborative clustering is to reveal the common underlying structure of data spread across multiple data sites by applying clustering techniques. The idea of collaborative clustering is that each collaborator shares some information about the segmentation (structure) of its local data and improve its own clustering with the information provided by the other learners. This paper analyses the impact of the quality and the diversity of the potential learners to the quality of the collaboration for topological collaborative clustering algorithms based on the learning of a Self-Organizing Map (SOM). Experimental analysis on real data-sets showed that the diversity between learners impact the quality of the collaboration. We also showed that some internal indexes of quality are a good estimator of the increase of quality due to the collaboration.

Open access

Michal Mizera, Pawel Nowotarski, Aleksander Byrski and Marek Kisiel-Dorohinicki

Abstract

Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.

Open access

Md Meftahul Ferdaus, Sreenatha G. Anavatti, Matthew A. Garratt and Mahardhika Pratama

Abstract

Advanced and accurate modelling of a Flapping Wing Micro Air Vehicle (FW MAV) and its control is one of the recent research topics related to the field of autonomous MAVs. Some desiring features of the FW MAV are quick flight, vertical take-off and landing, hovering, and fast turn, and enhanced manoeuvrability contrasted with similar-sized fixed and rotary wing MAVs. Inspired by the FW MAV’s advanced features, a four-wing Nature-inspired (NI) FW MAV is modelled and controlled in this work. The Fuzzy C-Means (FCM) clustering algorithm is utilized to construct the data-driven NIFW MAV model. Being model free, it does not depend on the system dynamics and can incorporate various uncertainties like sensor error, wind gust etc. Furthermore, a Takagi-Sugeno (T-S) fuzzy structure based adaptive fuzzy controller is proposed. The proposed adaptive controller can tune its antecedent and consequent parameters using FCM clustering technique. This controller is employed to control the altitude of the NIFW MAV, and compared with a standalone Proportional Integral Derivative (PID) controller, and a Sliding Mode Control (SMC) theory based advanced controller. Parameter adaptation of the proposed controller helps to outperform it static PID counterpart. Performance of our controller is also comparable with its advanced and complex counterpart namely SMC-Fuzzy controller.

Open access

Rudolf Drga, Dagmar Janáčová, Rudolf Palenčár and Stanislav Ďuriš

Abstract

The present work focuses on the solution of management of measuring spatial characteristics of security detectors using a positioner, a precision manipulator. It deals with program management software in LabView. Graphical programming with subroutines, which are described as virtual instruments, is used. There are published results of measurements of the spatial characteristics of the PIR detector, where it is preferably used as the measuring station.

Open access

Linus Michaeli, Ján Šaliga, Pavol Dolinský and Imrich Andráš

Abstract

Compressive sensing is a processing approach aiming to reduce the data stream from the observed object with the inherent sparsity using the optimal signal models. The compression of the sparse input signal in time or in the transform domain is performed in the transmitter by the Analog to Information Converter (AIC). The recovery of the compressed signal using optimization based on the differential evolution algorithm is presented in the article as an alternative to the faster pseudoinverse algorithm. Pseudoinverse algorithm results in an unambiguous solution associated with lower compression efficiency. The selection of the mathematically appropriate signal model affects significantly the compression efficiency. On the other hand, the signal model influences the complexity of the algorithm in the receiving block. The suitability of both recovery methods is studied on examples of the signal compression from the passive infrared (PIR) motion sensors or the ECG bioelectric signals.

Open access

M. Abdullah Eissa

Abstract

This paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the high demands on the availability and efficiency of electrical power production, the design of robust load-frequency controller is becoming increasingly important due to its potential in increasing the reliability, maintainability and safety of power systems. So, the proposed controller has been applied for load-frequency control (LFC) of a single-area power system. The effectiveness of the proposed SNPID controller has been compared with the conventional controllers. The simulation results show that the proposed controller approach provides better damping of oscillations with a smaller settling time. This confirms its superiority against its counterparts. In addition, the results show the robustness of the proposed controller against the parametric variation of the system.

Open access

Miroslav Mahdal, Josef Dobeš and Milada Kozubková

Abstract

Aerodynamically generated noise affects passenger comfort in cars, high-speed trains, and airplanes, and thus, automobile manufacturers aim for its reduction. Investigation methods of noise and vibration sources can be divided into two groups, i.e. experimental research and mathematical research. Recently, owing to the increase in computing power, research in aerodynamically generated noise (aero-acoustics) is beginning to use modern methods such as computational fluid dynamics or fluid-structure interaction. The mathematical model of turbulent flow is given by the system of partial differential equations, its solution is ambiguous and thus requires verification by physical experiment. The results of numerical methods are affected by the boundary conditions of high quality gained from the actual experiment. This article describes an application of complex measurement methodology in the aerodynamic and acoustic (vibro-acoustic) fields. The first part of the paper is focused on the specification of the experimental equipment, i.e. the wind tunnel, which was significantly upgraded in order to obtain the relevant aerodynamics and vibro-acoustics data. The paper presents specific results from the measurement of the aerodynamic and vibro-acoustic fields.

Open access

Piotr Kuryło, Elena Pivarčiová, Joanna Cyganiuk and Peter Frankovský

Abstract

This paper discusses the problem of possibilities for applying a machine vision in the measurement of the trajectory of the upper limb movement in rehabilitation exercises. The fundamental presumption of designed system was to get the image from the camera’s CCD processor, possibilities of measuring and its processing. As a result of the application system, it is possible to dynamically determine the radius between the shoulder and forearm, and also the angle between the shoulder and the chest of the man, as function of the limb motion. The created system gives the possibility to use a non-invasive method of measurement, allows visualization and full analysis of the rehabilitation progress and also allows keeping electronic records of patients.