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A compact microstrip parallel coupled line filter for ultra wide band applications by means of combining a network of coupled line and defected ground is proposed. The design equations for three and five interconnected networks are derived and implemented. Simulations for three different configurations for filters are optimized. Then three prototype circuits are constructed, a bandpass filter with center frequency 2.25 GHz and two different bandpass filters (in terms of perturbations) with center frequencies 2.33GHz. For 2.25 GHz circuit wide fractional bandwidth of about 90% is obtained but undesired high return loss existed. For 2.33GHz circuit with grooves in sides fractional bandwidth of about 60% is obtained at about 3.4 GHz center frequency. However undesired return loss existed for this circuit whereas good out off band performance is achieved. For 2.33GHz circuit with grooves in whole sections the center frequency got shifted to about 3.4 GHz and about 50% fractional bandwidth is obtained with very good out off band performance observed.

A solution strategy is presented using a five-section transmission line impedance transformer aiming for multiple band matching network circuits. In this paper, the analysis, which is based on the transmission line theory and application of the evolutionary algorithm for the solution of the stated problem are explained. Design of the matching networks was performed and optimized at three different frequencies 1.8 GHz, 2.4 GHz and 3 GHz at the same time. Tests were performed for two different load configurations. The optimized design values obtained from the particle swarm optimization algorithm were verified for correctness using microwave simulator. After the fabrication of the circuits, the measurements were taken for these circuits for the validation of the design. From the observations that were made, it can be concluded that particle swarm optimization can be a good choice for the design and optimization of multiple band matching network circuits.

Solar power forecasting is very important in ensuring correct and reliable operation of solar power grids. In forecasting the solar power output, it is not very easy to determine which parameters are crucial. In this work, the effect of using temperature at noon as well as cloud percentage at noon were used as inputs and solar power output was considered as the output. Effects of using different kernels were studied. It is noticed that when root mean square error (RMSE) and mean absolute error (MAE) values were considered linear and radial kernels produced relatively better results. Moreover having temperature data together with cloud percentage data produced more accurate modelling and enabled to determine more accurate solar power output with relatively lower RMSE and MAE values.

In this paper, an approach for teaching basic antenna theory and propagation to senior level undergraduate students for electrical engineering related fields is proposed and described. The method combines mathematical and theoretical studies with antenna design and laboratory measurements to reinforce the subject’s theoretical and practical aspects together. Topics discussed in lectures include performing antenna radiation calculations, learning how to make antenna radiation pattern measurements, and designing of antennas such as microstrip patch antenna. The education is based on teaching these principles and enabling students to make some antenna measurements. At the end of the semester, an analysis on learning outcomes of the course was performed and feedback from students was taken. The feedback from students showed that there was a huge satisfaction in terms of achieving the goals in learning outcomes. The course structure proposed can be a good example for instructors who teach antennas and propagation courses.

Application of metaheuristic algorithms has been of continued interest in the field of electrical engineering because of their powerful features. In this work special design is done for a tapered transmission line used for matching an arbitrary real load to a 50{\Omega} line. The problem at hand is to match this arbitrary load to 50 {\Omega} line using three section tapered transmission line with impedances in decreasing order from the load. So the problem becomes optimizing an equation with three unknowns with various conditions. The optimized values are obtained using Particle Swarm Optimization. It can easily be shown that PSO is very strong in solving this kind of multiobjective optimization problems., Comment: 6 pages, 5 figures, 1 table

In this work, we modelled the exchange rates using Support Vector Regression (SVR). The currency selected in this work was Turkish Lira (TRY) and compared the rates between United States Dollars (USD), Euro (EUR), and British Pounds (GBP). The modelling was done for the period of January 2018 till October 2019 data, with the aim to investigate three different issues. The difference in using ν-regression and e–regression was investigated. The effect of using different kernel functions was examined. Also, the effect of using multiple different exchange rates together (multi-rate) compared with modeling only one rate (single-rate) was explored. The results showed very successful modelling of the currencies producing very accurate results using the ν-regression modelling with radial kernel and using multi-rate modelling.

In this work our aim was to use support vector regression technique to predict unemployment rate and gross domestic product (GDP) of the Organization for the Economic Cooperation and Development (OECD) countries. The original data for unemployment rate and GDP taken from OECD was tested with the models generated by support vector regression. The analysis of using different kernels as well as analysis of using extended data from four countries in predicting the unemployment rate and GDP were considered separately. For unemployment rate, the relative error in average was 2.055% using the radial kernel and using extended data from four countries. Similarly, for GDP the relative error in average was 0.503%. It was observed that in fact support vector regression is a very powerful modelling tool in using the existing historical data for predicting the values of interest.

In this work the analysis of support vector regression method for the design of microstrip patch antenna is evaluated. Two section of transmission lines for the feed of the patch antenna is proposed and data is collected from a microwave simulator with different width values of these transmission lines. The data obtained for the design is used in a support vector regression to see if the modeling using support vector regression can be justified. The model obtained by the regression predicted very good results where the average predicted errors were lower than 3 dB.

This paper describes a design of RF energy harvesting circuit which works at multiple frequencies. The circuit is based on a modified patch antenna which has dual operating points followed by a multi-stage matching network and a rectifying circuit. The RF energy harvesting circuit is designed and fabricated. Simulation results and some measurements which are taken are presented in this paper. It was observed that the design circuit has good operation at the frequency of 1.7 GHz and acceptable distinct operation at frequencies of2.41 GHz and 2.62 GHz.

Solving real case optimization problems by providing high solution quality is an interesting field of research. In this paper, a newly proposed optimization algorithm enhanced leader particle swarm optimization (ELPSO) is used for solving two different microwave matching network circuits. The experimental results are compared with standard particle swarm optimization (PSO) algorithm. The results indicated that the new approach ELPSO produces reliable performance and the optimum solutions are reached in less number of iterations compared to PSO. It can be concluded that ELPSO can be recommended as a good optimization algorithm in solving real case complex problems.

Metaheuristic algorithms are investigated and used by many researchers in different areas. It is crucial to find optimal solutions for all problems under study especially for the ones which require sensitive optimization. Especially, for real case problems, solution quality and convergence speed of the algorithms are highly desired characteristics. In this paper, a new optimization algorithm called Core Levels Algorithm (COLA) based on the use of metaheuristics is proposed and analyzed. In the algorithm, two core levels are applied recursively to create new offsprings from the parent vectors which provides a desired balance on the exploration and exploitation characteristics. The algorithm’s performance is first studied on some well-known benchmark functions and then compared with previously proposed efficient evolutionary algorithms. The experimental results showed that even at the early stages of optimization, obtained values are very close or exactly the same as the optimum values of the analyzed functions. Then, the performance of COLA is investigated on real case problems such as some selected microwave circuit designs. The results denoted that COLA produces stable results and provides high accuracy of optimization without high parameter dependency even for the real case problems.

The use of swarm intelligence algorithms for solving complex optimisation problems is an interesting area since they can produce remarkable results. The animal migration optimisation (AMO) algorithm is one of the swarm intelligence algorithms which is derived from the migration behaviour of animals. The implementation of AMO algorithm for complex array optimisation problems is given. The experimental studies show that the AMO algorithm produces high-quality results and it is capable to overcome strong local optimum points by using its attributes. Also, it has few number of steps which are quite easy to implement. The AMO can be suggested as a powerful algorithm for optimisation problems including complex array designs when the high solution quality is desired.

This short paper presents a work on the design of low noise microwave amplifiers using particle swarm optimization (PSO) technique. Particle Swarm Optimization is used as a method that is applied to a single stage amplifier circuit to meet two criteria: desired gain and desired low noise. The aim is to get the best optimized design using the predefined constraints for gain and low noise values. The code is written to apply the algorithm to meet the desired goals and the obtained results areverified using different simulators. The results obtained show that PSO can be applied very efficiently for this kind of design problems with multiple constraints.

This letter presents the concept of particle swarm optimization (PSO) technique applied to two sets of microwave circuits: microstrip coupler and single shunt stub matching circuit. The PSO technique that is applied to these two set of designs is tested and compared with simulation results. The results show that PSO is an efficient method for solving these kinds of problems and can be applied for the design of microwave circuits. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 1333–1336, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23369

Artificial immune systems are classified as computational systems inspired by theoretical immunology and are mechanisms that can solve complex problems. Clonal selection algorithm is a selection algorithm, which is derived as a special selection algorithm to this artificial intelligence concept. In this work, Clonal selection algorithm is applied to design a simple microwave matching network for a load with arbirtary impedance. The results obtained were tested in a microwave simulator and indicated that clonal selection algorithm can be very effectively applied for microwave design problems. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:991–993, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.25935

Evolutionary and swarm algorithms have found many applications in design problems since todays computing power enables these algorithms to find solutions to complicated design problems very fast. Newly proposed hybrid algorithm, bat algorithm, has been applied for the design of microwave microstrip couplers for the first time. Simulation results indicate that the bat algorithm is a very fast algorithm and it produces very reliable results., Comment: 7 pages, 4 figures, 1 table

This letter presents a proof-of-concept implementation of a millimeter-wave reflectometer for measuring complex reflection coefficients. The reflectometer is based on the six-port architecture and consists of a single section of WR-10 rectangular waveguide and a set of three Schottky power detectors. Design considerations as well as measurements in the 75 to 110 GHz range are described and discussed. Because of its simple architecture, the reflectometer is amenable to scaling for measurements well into the submillimeter-wave region of the spectrum.

A quasi-optical balanced doubler based on the dual-polarized sinuous antenna is presented. The input fundamental and output second harmonic signals are isolated by polarization and external wire-grid polarizers are used for impedance tuning. The doubler exhibits 1.6 dB of conversion gain at an input frequency of 5 GHz with a bandwidth of 10%.

The design, construction, and investigation of a compact reflectometer suitable for measuring return loss magnitude and phase of biological materials and chemical agents at submillimeter wavelengths is presented. The instrument, which consists of a section of rectangular waveguide and an ensemble of Schottky diode power detectors is designed as a proof-of-principle demonstration and is a relatively simple implementation of the six-port analyzer originally investigated by Engen and coworkers. Design considerations for the reflectometer are presented and measurements in the 270 GHz to 320 GHz range are discussed. In addition, preliminary return loss measurements on sample biological materials (salmon and herring DNA) in the millimeter-wave region are presented and described.

The design, construction, and investigation of a reflectometer for measuring return loss magnitude and phase at submillimeter wavelengths is presented. The instrument, which consists of a section of rectangular waveguide and an ensemble of Schottky diode power detectors is designed as a proof-of-principle demonstration and is a relatively simple implementation of the six-port analyzer originally investigated by Engen and coworkers. Design considerations for the reflectometer are presented and measurements in the 270 GHz to 320 GHz range are discussed.

The experimental investigation of a reflectometer for measuring return loss magnitude and phase at submillimeter wavelengths is presented. The reflectometer, which is designed as a proof-of-principle demonstration, is based on the sampled-transmission line architecture and its design and operation are described. The instrument is a relatively simple implementation of the six-port network analyzer introduced by Engen and consists of a section of rectangular waveguide and an ensemble of Schottky diode power detectors. Design considerations for the instrument are presented and measurements in the 270 GHz to 285 GHz range are discussed.

A reflectometer designed for operation at submillimeter wavelengths and based on the sampled-transmission line architecture is described. The reflectometer is a relatively simple implementation of the six-port network analyzer introduced by Engen (IEEE Trans. Microwave Theory Tech., vol. MTT-25, no. 12, pp. 1080-1083, 1979) and consists of a section of rectangular waveguide and an ensemble of Schottky diode power detectors. Design considerations for the instrument are described and measurements in the 270 GHz to 285 GHz range are presented and discussed.