Artificial Intelligence
H. Karim Tabbahfar; F. Tabib Mahmoudi
Abstract
Background and Objectives: Considering the drought and global warming, it is very important to monitor changes in water bodies for surface water management and preserve water resources in the natural ecosystem. For this purpose, using the appropriate spectral indices has high capabilities to distinguish ...
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Background and Objectives: Considering the drought and global warming, it is very important to monitor changes in water bodies for surface water management and preserve water resources in the natural ecosystem. For this purpose, using the appropriate spectral indices has high capabilities to distinguish surface water bodies from other land covers. This research has a special consideration to the effect of different types of land covers around water bodies. For this reason, two different water bodies, lake and wetland, have been used to evaluate the implementation results.Methods: The main objective of this research is to evaluate the capabilities of the genetic algorithm in optimum selection of the spectral indices extracted from Sentinel-2 satellite image due to distinguish surface water bodies in two case studies: 1) the pure water behind the Karkheh dam and 2) the Shadegan wetland having water mixed with vegetation. In this regard, the set of optimal indices is obtained with the genetic algorithm followed by the support vector machine (SVM) classifier. Results: The evaluation of the classification results based on the optimum selected spectral indices showed that the overall accuracy and Kappa coefficient of the recognized surface water bodies are 98.18 and 0.9827 in the Karkheh dam and 98.04 and 0.93 in Shadegan wetland, respectively. Evaluation of each of the spectral indices measured in both study areas was carried out using quantitative decision tree (DT) classifier. The best obtained DT classification results show the improvements in overall accuracy by 1.42% in the Karkheh Dam area and 1.56% in the Shadegan Wetland area based on the optimum selected indices by genetic algorithm followed by SVM classifier. Moreover, the obtained classification results are superior compared with Random Forest classifier using the optimized set of spectral features.Conclusion: Applying the genetic algorithm on the spectral indices was able to obtain two optimal sets of effective indices that have the highest amount of accuracy in classifying water bodies from other land cover objects in the study areas. Considering the collective performance, genetic algorithm selects an optimal set of indices that can detect water bodies more accurately than any single index.
Antenna Design
R. Shirmohamadi; M. Bod; G. Dadashzadeh
Abstract
Background and Objectives: Multi-input multi-output (MIMO) antennas have been of interest in wireless communications in recent years. In these systems, many antennas are placed next to each other. The most important issue in the design of MIMO antennas is mutual coupling. Many methods have been proposed ...
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Background and Objectives: Multi-input multi-output (MIMO) antennas have been of interest in wireless communications in recent years. In these systems, many antennas are placed next to each other. The most important issue in the design of MIMO antennas is mutual coupling. Many methods have been proposed to reduce the mutual coupling of MIMO antennas. Many of these methods require an additional substrate on top or bottom of the antenna. In the reduction of mutual couplings electromagnetic band-gap (EBG) structures are preferred because they are coplanar with the antenna and can be compactly designed. In this paper, to reduce mutual coupling in MIMO antennas, a novel compact EBG structure based on the genetic algorithm optimization is proposed.Methods: The method proposed in this paper to design an optimal EBG structure is to use a genetic algorithm (GA). In this method, an EBG unit cell is designed by a binary code, and then the 7×2 EBG structure of the unit cell is placed between two antenna elements with λ/2 distance. The optimization algorithm tries to find the best unit cell to reduce the mutual coupling between two elements. After 70 generations in the genetic algorithm, the GA determines a compact structure of EBG elements which reduces mutual coupling significantly.Results: Two-element patch antennas with and without the proposed EBG structure are fabricated and the mutual couplings between array elements are measured at 5.68GHz in both cases. It is shown that the proposed compact EBG structure reduced the isolation of the two antennas by 27 dB. This decrease in mutual coupling is much higher than in the previous papers. The proposed EBG has little effect on other antenna radiation parameters such as S11 and radiation patterns.Conclusion: In general, in this paper, a compact and coplanar EBG structure is proposed to significantly reduce the mutual coupling in MIMO antennas. The method presented in this paper can be used for other MIMO antenna configurations at other frequencies and the proposed method will create a completely optimal structure to reduce mutual coupling.
Antenna Design
M. Bod; F. Geran
Abstract
Background and Objectives: Self-supported rear-radiating feeds have been widely used as reflector antenna feeds for mini terrestrial and satellite links. While in most terrestrial and satellite links a dual-polarized antenna for send and receive applications are required, all of the reported works regarding ...
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Background and Objectives: Self-supported rear-radiating feeds have been widely used as reflector antenna feeds for mini terrestrial and satellite links. While in most terrestrial and satellite links a dual-polarized antenna for send and receive applications are required, all of the reported works regarding this topic are presenting a single polarized self-supported reflector antenna. In this paper, a dual-polarized hat feed reflector antenna with a low sidelobe and low cross-polarization level is presented. Methods: The proposed antenna consists of an orthogonal mode transducer (OMT), a 60 cm ring focus reflector, and a rear radiating waveguide feed known as the hat feed. 21 parameters of hat feed structure are selected and optimized with a genetic algorithm (GA). A predefined ring focus curve is used as a reflector in the optimization procedure. Dual polarization for send and receive applications is also obtained by an OMT at the rear side of the reflector antenna.Results: A prototype of the proposed hat feed reflector antenna is fabricated and the measurement results are compared with simulation ones. The proposed antenna has return loss better than 15 dB at both polarizations in the 17.7~19.7 GHz frequency range. The 60cm reflector antenna has 40dBi gain which means that the proposed antenna has about 70% radiation efficiency. About 20dB sidelobe level and more than 40 dB cross-polarization have also been realized in the measurement patterns of the proposed antenna. Conclusion: A dual-polarized hat feed reflector antenna with excellent radiation efficiency, high sidelobe, and low cross-polarization level is proposed. The proposed antenna can be a good candidate for high-frequency terrestrial and satellite communications.
Data Mining
Y. Rohani; Z. Torabi; S. Kianian
Abstract
Background: Prediction of students' academic performance is essential for systems emphasizing students' greater success. The results can largely lead to increase in the quality of the educating and learning. Through the application of data mining, useful and innovative patterns can be extracted from ...
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Background: Prediction of students' academic performance is essential for systems emphasizing students' greater success. The results can largely lead to increase in the quality of the educating and learning. Through the application of data mining, useful and innovative patterns can be extracted from the educational data.Methods: In this paper, a new metaheuristic algorithm, combination of simulated annealing and genetic algorithms, is proposed for predicting students’ academic performance in educational data mining. Although metaheuristic algorithms are one of the best options for discovering the hidden relationships between data in data science, they do not separately perform well in accurate prediction of students’ academic performance. Therefore, the proposed method integrates the advantages of both genetic and simulated annealing algorithms. The genetic algorithm is applied to explore new solutions, while simulated annealing is used to increase the exploitation power. By using this combination, the proposed algorithm has been able to predict the students’ academic performance with high accuracy.Results: The efficiency of the proposed algorithm is evaluated on five different educational data sets, including two data sets of students of Shahid Rajaee University of Tehran and three online educational data sets. Our experimental results show and accuracy improvement of the proposed algorithm in comparison to the four similar metaheuristic and five popular classification methods respectively.
Artificial Intelligence
F. Jamshidi; M. Vaghefi
Abstract
Background and Objectives: A robot arm is a multi-input multi-output and non-linear system that has many industrial applications. Parameter uncertainties and external disturbances attenuate the performance of this system and a controller design is hence necessary to overcome them.Methods: In ...
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Background and Objectives: A robot arm is a multi-input multi-output and non-linear system that has many industrial applications. Parameter uncertainties and external disturbances attenuate the performance of this system and a controller design is hence necessary to overcome them.Methods: In this paper, the interval Type II Fuzzy fractional-order proportional integral differential (IT2FO-FPID) controller is designed to control a robot arm with 2 degrees of freedom (two-link robot arm). Whale optimization algorithm (WOA) is used to determine the optimal value of controller parameters. The performance of IT2FO-FPID is compared with PID, fractional-order PID (FOPID) and Fuzzy FOPID whose parameters are determined by WOA. The performance of IT2FO-FPID whose parameters are determined by WOA, genetic algorithm, and particle swarm optimization methods are compared.Results: Quantitative and qualitative results of simulations indicate performance improvement with the IT2FO-FPID controller. The ability of WOA in optimizing the parameters of the IT2FO-FPID controller is demonstrated.Conclusion: Sensitivity analysis and the study of the effect of parameter variations and disturbances confirm the robust performance of WOA-based IT2FO-FPID.
Control
H. Nasiri Soloklo; N. Bigdeli
Abstract
Background and Objectives: In this paper, a predictive functional control based on Laguerre functions is designed for control of an industrial heating furnace. The fractional order model (FOM) of the heating furnace is assumed as the plant model.Methods: For designing the predictive functional controller ...
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Background and Objectives: In this paper, a predictive functional control based on Laguerre functions is designed for control of an industrial heating furnace. The fractional order model (FOM) of the heating furnace is assumed as the plant model.Methods: For designing the predictive functional controller (PFC), a reduced integer order approximation of the fractional order heating furnace model is derived. The order of the reduced integer model is determined based on Hankel singular values of the original system. Coefficients of the reduced integer model are assumed to be unknown. Unknown parameters are then obtained by minimizing a many-objective fitness function including weighted summation of differences of step responses, steady state errors, maximum overshoots as well as magnitude of frequency responses of the original and reduced systems. Routh-Hurwitz criteria are used as stability criteria and added to optimization problem as its constraints. The optimization tool is Genetic algorithm.Results: Advantages of the proposed method are preserving stability and focusing on various important features of both time and frequency responses of system. In addition, it uses a direct order reduction method without the need to intermediated approximations such as Oustaloup approximation.Conclusion: Laguerre-based PFC controller has been evaluated via two scenarios and the obtained results represent the satisfactory performance of the proposed controller.
