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In this paper we study inverse problems of electric conductivity that arise in the design of spherical shielding or cloaking shells and other functional devices used to control static electric fields. The shells are considered consisting of a finite number of layers filled with homogeneous isotropic or anisotropic medium. The inverse problems under study are reduced to control problems with the layers electric conductivities taken as controls. A different choice of minimized functionals allows us to solve a wide range of design problems using one approach. A numerical algorithm to solve these problems is based on particle swarm optimization. Various results of numerical experiments are discussed in order to find the most effective designs. The findings obtained in this study describe a broad set of specific easy-to-manufacture structures that have the highest cloaking or shielding performance in the class of layered shells.

In this paper, a new asinh-type control scheme with gravity compensation for the position control problem of robot manipulators in joint space is presented. The properties and characteristics of the asinh control structure make the position error and the motion velocity asymptotically converge to the equilibrium point. A strict Lyapunov function to formally prove global asymptotic stability is developed. The tuning of the control gains is obtained by PSO (Particle Swarm Optimization) technique without saturating the servomotors. To illustrate the effectiveness and performance of the proposed scheme, an experimental comparative analysis between the proportional-derivative (PD) and atanh controls against the proposed algorithm on a three degrees of freedom direct-drive robot manipulator is carried out.

In this paper, a new flexible wearable radio frequency identification (RFID) five-shaped slot patch tag placed on the human arm is designed for ultra-high frequency (UHF) healthcare sensing applications. The compact proposed tag consists of a patch structure provided with five shaped slot radiators and a flexible substrate, which minimize the human body’s impact on the antenna radiation performance. We have optimized our designed tag using the particle swarm optimization (PSO) method with curve fitting within MATLAB to minimize antenna parameters to achieve a good return loss and an attractive radiation performance in the operating band. The PSO-optimized tag’s performance has been examined over the specific placement in some parts of the human body, such as wrist and chest, to evaluate the tag response and enable our tag antenna conception in wearable biomedical sensing applications. Finally, we have tested the robustness of this tag by evaluating its sensitivity as a function of the antenna radiator placement over the ground plane or by shaping the ground plane substrate for the tag’s position from the human body. Our numerical results show an optimal tag size with good matching features and promising read ranges near the human body.

U ovom radu se analizira problem terminiranja mobilnog robota (MR) u cilju pronalaženja optimalnog načina opsluživanja mašina alatki u inteligentnom tehnološkom sistemu. Da bi se rešio ovaj NP-hard optimizacioni problem, koriste se različiti biološki inspirisani metaheuristički algoritmi optimizacije, poput algoritama inspirisanog inteligencijom roja čestica - Particle Swarm Optimization (PSO), algoritma inspirisanog inteligencijom jata kitova - Whale optimization algorithm (WOA) i modifikovanog WOA (mWOA). Najbolje performanse pokazao je algoritam mWOA, koji je biološki inspirisan algoritam zasnovan na principu lova jata grbavih kitova. Inteligentni tehnološki sistem korišćen za eksperimentalnu verifikaciju predloženog algoritma se sastoji od osam mašina alatki na kojima se vrši obrada tri dela, koji imaju pet tipova fleksibilnosti, dok se terminirani unutrašnji transport materijala u tehnološkom sistemu vrši jednim mobilnim robotom. Razvijeni algoritam je implementiran u MATLAB softverskom paketu, In this paper, the authors analyze single mobile robot scheduling problem in order to find an optimal way to transport parts in intelligent manufacturing system. Because of the combinatorial complexity, this problem is considered to be NP-hard and the authors propose three different metaheuristic algorithms (PSO, WOA and mWOA) to solve it. Manufacturing system consists of eight machine tools, three parts and single mobile robot used for material transport tasks. Optimal scheduling plans are obtained by single objective optimization procedure, using four fitness functions. The experimental results show that mWOA outperforms all other algorithms. All the algorithms are implemented in MATLAB software package

Stock return prediction is considered a challenging task in financial domain. The existence of inherent noise and volatility in daily stock price returns requires a highly complex prediction system. Generalizations of fuzzy systems have shown promising results for this task owing to their ability to handle strong uncertainty in dynamic financial markets. Moreover, financial variables are usually in difficult to interpret causal relationships. To overcome these problems, here we propose an interval-valued fuzzy cognitive map with PSO algorithm learning. This system is suitable for modelling complex nonlinear problems through causal reasoning. As the inputs of the system, we combine causally connected financial indicators and linguistic variables extracted from management discussion in annual reports. Here we show that the proposed method is effective for predicting abnormal stock return. In addition, we demonstrate that this method outperforms fuzzy cognitive maps and adaptive neuro-fuzzy rule-based systems with PSO learning., Predikce výnosů akcií je v oblasti financí považována za náročnou úlohu. Existence inherentního šumu a kolísání denních výnosů cen akcií vyžaduje velmi komplexní predikční systém. Generalizace fuzzy systémů ukazují slibné výsledky vzhledem k jejich schopnosti modelovat silnou nejistotu na dynamických finančních trzích. Finanční proměnné jsou navíc obvykle v obtížně interpretovatelných kauzálních vztazích. Abychom překonali tyto problémy, navrhujeme zde intervalovou fuzzy kognitivní mapu s učením pomocí PSO algoritmu. Tento systém je vhodný pro modelování komplexních nelineárních problémů pomocí kauzálního usuzování. Jako vstupy systému spojujeme kauzálně propojené finanční ukazatele a jazykové proměnné, které jsou získávány z diskuse managementu ve výročních zprávách. Ukazujeme, že navrhovaná metoda je účinná pro predikci abnormálního výnosu akcií. Navíc prokazujeme, že tato metoda překonává fuzzy kognitivní mapy a adaptivní systémy založené na neuro-fuzzy pravidlech s PSO učením.

Purpose: The purpose of this paper is to propose a mathematical model for the prediction of railway freight volume, and therefore provide railway freight resource allocation with an accurate direction. With an accurate railway freight volume prediction, railway freight enterprises can integrate the limited resources and organize transport more reasonably. Design/methodology/approach: In this paper, a PSO-GRNN model is proposed to predict the railway freight volume. In this model, GRNN is applied to carry out the nonlinear regression analysis and output the prediction value, PSO algorithm is applied to optimize the GRNN model by searching the best smoothing parameter. In order to improve the performance of PSO algorithm, time linear decreasing inertia weight algorithm and time varying acceleration coefficient algorithm are applied in the paper. Originality/value: A railway freight volume prediction index system containing seventeen indexes from five aspects is established in this paper. And PSO-GRNN model constructed in this paper are applied to predict the railway freight volume from 2007 to 2011. Finally, an empirical study is given to verify the feasibility and accuracy of the PSO-GRNN model by comparing with RBFNN model and BPNN model. The result shows that PSO-GRNN model has a good performance in reducing the prediction error, and can be applied in actual production easily, Peer Reviewed

The main aim of this paper is the utilization of discrete chaotic Dissipative standard map based chaos number generator to enhance the performance of PSO algorithm. This paper presents application of proposed algorithm to design PID controller for 4th order system. Results of this application are compared with previously published results in the area of evolutionary PID controller design.

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.

The main aim of this paper is the utilization of discrete chaotic Dissipative standard map based chaos number generator to enhance the performance of PSO algorithm. This paper presents application of proposed algorithm to design PID controller for 4th order system. Results of this application are compared with previously published results in the area of evolutionary PID controller design.

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.

Diplomová práce se zabývá způsoby optimalizace v obrazových aplikacích. Jsou zde popsány vybrané optimalizační metody a aplikace zpracování obrazu. Byly vybrány tři evoluční algoritmy, konkrétně včelí algoritmus, spojitý genetický algoritmus a algoritmus PSO, které byly podrobně popsány a implementovány v prostředí Matlab pro využití v registraci obrazu, přizpůsobené filtraci, segmentaci a rekonstrukci obrazu. Nechybí zde ani srovnání všech zrealizovaných algoritmů., This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.

Diplomová práce se zabývá způsoby optimalizace v obrazových aplikacích. Jsou zde popsány vybrané optimalizační metody a aplikace zpracování obrazu. Byly vybrány tři evoluční algoritmy, konkrétně včelí algoritmus, spojitý genetický algoritmus a algoritmus PSO, které byly podrobně popsány a implementovány v prostředí Matlab pro využití v registraci obrazu, přizpůsobené filtraci, segmentaci a rekonstrukci obrazu. Nechybí zde ani srovnání všech zrealizovaných algoritmů., This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.

Diplomová práce se zabývá způsoby optimalizace v obrazových aplikacích. Jsou zde popsány vybrané optimalizační metody a aplikace zpracování obrazu. Byly vybrány tři evoluční algoritmy, konkrétně včelí algoritmus, spojitý genetický algoritmus a algoritmus PSO, které byly podrobně popsány a implementovány v prostředí Matlab pro využití v registraci obrazu, přizpůsobené filtraci, segmentaci a rekonstrukci obrazu. Nechybí zde ani srovnání všech zrealizovaných algoritmů., This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.

Diplomová práce se zabývá způsoby optimalizace v obrazových aplikacích. Jsou zde popsány vybrané optimalizační metody a aplikace zpracování obrazu. Byly vybrány tři evoluční algoritmy, konkrétně včelí algoritmus, spojitý genetický algoritmus a algoritmus PSO, které byly podrobně popsány a implementovány v prostředí Matlab pro využití v registraci obrazu, přizpůsobené filtraci, segmentaci a rekonstrukci obrazu. Nechybí zde ani srovnání všech zrealizovaných algoritmů., This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.

Diplomová práce se zabývá způsoby optimalizace v obrazových aplikacích. Jsou zde popsány vybrané optimalizační metody a aplikace zpracování obrazu. Byly vybrány tři evoluční algoritmy, konkrétně včelí algoritmus, spojitý genetický algoritmus a algoritmus PSO, které byly podrobně popsány a implementovány v prostředí Matlab pro využití v registraci obrazu, přizpůsobené filtraci, segmentaci a rekonstrukci obrazu. Nechybí zde ani srovnání všech zrealizovaných algoritmů., This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.