- Many design optimization problems have problems that seek fast, efficient and reliable based solutions. In such cases, artificial intelligence-based modeling is used to solve costly and complex problems. This study ...
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- Many design optimization problems have problems that seek fast, efficient and reliable based solutions. In such cases, artificial intelligence-based modeling is used to solve costly and complex problems. This study is based on the modeling of a multiband helical antenna using the Latin hypercube sampling (LHS) method using a reduced data enhanced multilayer perceptron (eMLP). The proposed helical antenna is dual-band and has resonance frequencies of 2.4 GHz and 2.75 GHz. The enhanced structure of the artificial neural network (ANN) was tested using 4 different training algorithms and a maximum of 10 different MLP architectures to determine the most suitable model in a simple and quick way. Then, performance comparison with other ANN networks was made to confirm the success of the model. Considering the high cost of antenna simulations, it is clear that the proposed model will save a lot of time. In addition, thanks to the selected sampling model, a wide range of modeling can be done with minimum data. When the target and prediction data are compared, it is seen that these data overlap to a large extent. As a result of the study, it was seen that the ANN modeling and the 125 samples used, were as accurate as an electromagnetic (EM) simulator for other input parameters in a wide range selected.
In this paper, an optimization method based on the combination of Nelder-Mead (NM) simplex concepts and charged system search algorithm (CSS) is proposed and called NM-CSS. NM, as a search technique, involves the iter...
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In this paper, an optimization method based on the combination of Nelder-Mead (NM) simplex concepts and charged system search algorithm (CSS) is proposed and called NM-CSS. NM, as a search technique, involves the iterative formation and transformation of a geometrically arranged set of points known as a simplex to uncover the optimal solution. By incorporating NM into metaheuristic algorithms, the convergence speed and solution quality can be notably boosted. Throughout each iteration, the solutions undergo various operations, including reflection, contraction, and expansion, to enhance the effectiveness of the algorithm. In this algorithm, produced solutions by the CSS are sorted and divided into two groups of good and bad solutions, and then the NM operators are applied to bad solutions to generate the possible best ones. The proposed algorithm is verified through some mathematical benchmark functions. Then, it is implemented on a real-size reinforced concrete bridge to reach an optimum design. To recognize the effective parameters in the design of structural components of reinforced concrete bridges, a sensitivity analysis is carried out. The total cost of materials in piers and the deck is defined as an objective function, and the cross-section area of structural elements and longitudinal reinforcements are chosen as design variables. The results of simulations represent the stability and robustness of the proposed NM-CSS method compared to standard CSS. In other words, utilizing the proposed NM-CSS algorithm in an optimum design of the piers and deck results in saving %3.685 and %2.084 of costs, respectively, in comparison with the results of the standard CSS.
Wireless sensor networks have been used widely in environmental tracking and monitoring. Nevertheless, WSNs are facing a number of challenges, such as unreasonable cluster head selection and energy-hole problems while...
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Wireless sensor networks have been used widely in environmental tracking and monitoring. Nevertheless, WSNs are facing a number of challenges, such as unreasonable cluster head selection and energy-hole problems while nodes have unbalanced energy consumption. Thus, the paper aims to propose an energy-efficient non-uniform clustering routing protocol to enhance nodes energy efficiency and balance the energy consumption in WSNs. In addition, a non-uniform clustering network partition is introduce to reduce the probability of energy hole occurrences and optimize cluster heads dynamical selection method to suggest an improved shuffled frog leaping algorithm. Ultimately, the simulation experiment has demonstrated a 20% gain of energy efficiency to extend network lifetime by the proposed protocol and enhanced algorithm.
An adaptive flower pollination algorithm (AFPA) is evolved with respect to the accuracy and stability performance. AFPA is developed by modifying both global and local search operators. The exploration and exploitatio...
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In the power system, when monitoring various devices and transmission lines, because the transmission lines are generally in the wild, the surrounding weather environment and geographical environment are very complica...
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ISBN:
(数字)9781728198880
ISBN:
(纸本)9781728198897
In the power system, when monitoring various devices and transmission lines, because the transmission lines are generally in the wild, the surrounding weather environment and geographical environment are very complicated. Therefore, during video monitoring and recognition, the collected video images will be Affected by the weather and light, the quality of the collected images is reduced. However, the recognition in the later stage does not consider how to filter out these influences, and it is often difficult to achieve the desired results when performing subsequent image processing such as target recognition and tracking. For ARM+FPGA, DSP+FPGA image processing system, the cost is high, Low resource utilization, it is difficult to use simple FPGA to control the process and complex branch judgment, therefore, this paper designs a real-time enhanced monitoring terminal based on FPGA based on the idea of FPGA-based hardware and software collaborative processing. Complete image acquisition and real-time enhanced preprocessing in the monitoring terminal to improve the ability to accurately identify the transmission line during subsequent processing and achieve accurate identification. Use an FPGA chip as the core of the system, cache the image through SDRAM, use Sopc as the control core, coordinate software and hardware to perform image processing, easy to use hardware implementation(such as filtering, edge detection, etc.) are implemented using Verilog hardware language, Control these image processing modules through Sopc, realize the corresponding image processing function. And the part that is difficult to realize in the hardware, use NiosII in Sopc system to realize.
A three-dimensional objective space (3DOS) optimization strategy using an enhanced multi-objective artificial bee colony (ABC) algorithm for the design optimization of layered radar absorbing material (LRAM) is presen...
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A three-dimensional objective space (3DOS) optimization strategy using an enhanced multi-objective artificial bee colony (ABC) algorithm for the design optimization of layered radar absorbing material (LRAM) is presented in this study. The multi-objective exploitation ability of ABC is improved with regard to the convergence and diversity by integrating a pioneer Pareto (PP) solution to the onlooker bee phase, which is selected from the Pareto optimal set. Initially, the performance of PP-ABC is successfully verified by a comparison with ABC and the well-known multi-objective counterparts like particle swarm optimization (PSO) and differential evolution (DE) algorithms. The comparison is carried out through five multi-objective benchmark functions with respect to three favorable and reliable multi-objective indicators such as hypervolume (HV), HV ratio and Pareto sets proximity (PSP). The employed three objective functions to be the dimensions of 3DOS are weighted bandwidth-based total reflection coefficient involving sub-reflection waves of a wide oblique incident angular range 0 degrees-75 degrees, the total thickness and the number of layers. By using PP-ABC, a 3D designed LRAM operating at a large frequency band of 2-18 GHz is then designed for synchronously minimizing the three objective vectors by finding out the design variables: thickness and material types. Meanwhile, the material types of the proposed LRAM are optimally picked up from a composite material database with 51 specimens from 9 previously reported studies (51 /9#database). In order to point out the effectiveness of the proposed 3DOS optimization strategy, three LRAMs are also compared with respective reported designs whose material type is selected from a database with 6 specimens (6/1#database). The results show that the proposed LRAMs are hence the global optimal designs in terms of all objective functions thanks to the proposed 3DOS optimization strategy based on PP-ABC. (C) 2020 Elsevier B.V
Because traditional collaborative filtering algorithm does not consider the influence of time on user's interests, taking equal consideration with different user's interests in different time leads to the neig...
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ISBN:
(纸本)9780769536866
Because traditional collaborative filtering algorithm does not consider the influence of time on user's interests, taking equal consideration with different user's interests in different time leads to the neighbors may not be the similar neighbors set. For solving the problem, the enhanced algorithm endows each score with a time weight which declines gradually as time going, and uses the weighted score to search the nearest neighbors. Experiments of Movielens dataset show that the enhanced algorithm added time weight improves quality of recommendation system.
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