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Defects Inspection in Polycrystalline Solar Cells Electroluminescence Images Using Deep Learning
摘要： This paper proposes a novel bi-velocity discrete particle swarm optimization (BVDPSO) approach and extends its application to the nondeterministic polynomial (NP) complete multicast routing problem (MRP). The main contribution is the extension of particle swarm optimization (PSO) from the continuous domain to the binary or discrete domain. First, a novel bi-velocity strategy is developed to represent the possibilities of each dimension being 1 and 0. This strategy is suitable to describe the binary characteristic of the MRP, where 1 stands for a node being selected to construct the multicast tree, whereas 0 stands for being otherwise. Second, BVDPSO updates the velocity and position according to the learning mechanism of the original PSO in the continuous domain. This maintains the fast convergence speed and global search ability of the original PSO. Experiments are comprehensively conducted on all of the 58 instances with small, medium, and large scales in the Operation Research Library (OR-library). The results confirm that BVDPSO can obtain optimal or near-optimal solutions rapidly since it only needs to generate a few multicast trees. BVDPSO outperforms not only several state-of-the-art and recent heuristic algorithms for the MRP problems, but also algorithms based on genetic algorithms, ant colony optimization, and PSO.
关键词： Steiner tree problem (STP),particle swarm optimization (PSO),Communication networks,multicast routing problem (MRP)
更新于2025-09-23 15:21:01
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A coaxial alignment method for large aircraft component assembly using distributed monocular vision
摘要： The assembly of large component in out-field is an important part for the usage and maintenance of aircrafts, which is mostly manually accomplished at present, as the commonly used large-volume measurement systems are usually inapplicable. This paper aims to propose a novel coaxial alignment method for large aircraft component assembly using distributed monocular vision.
关键词： Posture evaluation,Particle swarm optimization (PSO),Aircraft assembly,Monocular vision,Coaxial alignment
更新于2025-09-23 15:21:01
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Performance comparison of recent optimization algorithm Jaya with particle swarm optimization for digital image watermarking in complex wavelet domain
摘要： Nowadays copyright protection is mandatory in the field of image processing to removes the illegitimate utilization and imitation of digital images. The digital image watermarking is one of the most reliable methods for protecting the illegal validation of data. In this paper, singular value decomposition based digital image watermarking scheme is proposed in complex wavelet transform (CWT) domain using intelligence algorithms like particle swarm optimization (PSO) and recently proposed Jaya algorithm. The watermark image is embedded into high frequency CWT subband of cover image. At the time of watermark embedding and extraction, optimization algorithms Jaya and PSO are applied to improve the robustness and imperceptibility by assessing the fitness function. The perceptual quality of watermarked image and robustness of extracted watermark image are verified under the filtering, rotation, scaling, Gaussian noise and JPEG compression attacks. From the comparative analysis it is proved that Jaya algorithm is better as compared to PSO algorithm under most types of attacks with higher magnitudes whereas identical under the lower magnitude of applied attacks. Moreover, using variety of cover images, it is found that, the elapse time and value of fitness function given by Jaya algorithm are also better as compared to PSO.
关键词： Particle swarm optimization,Singular value decomposition,Jaya algorithm,Complex wavelet domain watermarking,Fitness function,Elapse time
更新于2025-09-23 15:21:01
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Quantum Particle Swarm Optimization for Synthesis of Non-uniformly Spaced Linear Arrays with Broadband Frequency Invariant Pattern
摘要： This paper describes a method using Quantum Particle Swarm Optimization to obtain a broadband frequency invariant pattern for synthesis of nonuniformly spaced linear array of isotropic antennas. Two cases related to this work using QPSO have been studied, namely, in the first case, the generated frequency invariant far-field pattern is broadside in the vertical plane and in the second case, the far-field frequency invariant pattern is scanned in a particular direction. An effort is made such that the side lobe level and first null beam widths of the patterns are made similar to their related desired values. The two cases are presented in this paper to show the effectiveness of the proposed method in achieving the desired specifications. Even though, the developed method is utilized here for a linear array of isotropic antennas; it can be extended to other type of arrays. The performance of this algorithm is validated by duly comparing it with firefly algorithm.
关键词： firefly algorithm,quantum particle swarm optimization,frequency invariant pattern,side lobe level,first null beam width,Broadband array
更新于2025-09-23 15:21:01
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Crosstalk reduction of integrated optical waveguides with nonuniform subwavelength silicon strips
摘要： Suppression of the crosstalk between adjacent waveguides is important yet challenging in the development of compact and dense photonic integrated circuits (PICs). During the past few years, a few of excellent approaches have been proposed to achieve this goal. Here, we propose a novel strategy by introducing nonuniform subwavelength strips between adjacent waveguides. In order to determine the widths and positions of nonuniform subwavelength strips, the particle swarm optimization (PSO) algorithm is utilized. Numerical results demonstrate that the coupling length between adjacent waveguides is increased by three (five) orders of magnitude in comparison with the case of uniform (no) subwavelength strips. Our method greatly reduces crosstalk and is expected to achieve a highly compact integrated density of PICs.
关键词： crosstalk reduction,particle swarm optimization,integrated optical waveguides,photonic integrated circuits,nonuniform subwavelength silicon strips
更新于2025-09-23 15:19:57
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Laser transmission welding of thermoplastic with beam wobbling technique using particle swarm optimization
摘要： Laser transmission welding is growing day by day with an increase of the uses of thermoplastic materials. This article presents the effect of various process parameters on weld strength and weld seam width obtained. The transparent polycarbonate and black carbon filled PMMA, each of 2.8 mm thickness have been joined by using low power laser. Here, effect of wobble frequency and wobble width are studied along with other process parameters. It is observed that weld seam width much depends upon the wobble width and the effect of wobble frequency is minimum. It has been observed that laser beam wobbling provides the greater weld strength by enlargement of joint area. Moreover, Beam wobbling plays a significant role to achieve better weld strength and weld width. Response surface methodology has been used to model the laser welding process parameters and responses of welding through regression analysis. The results of ANOVA reveal that the models formed appropriately predict the responses within the range of process parameters. A confirmation experiment has also been conducted to validate the results. A multi objective optimization has been used to find the optimum solution by Particle swarm optimization technique.
关键词： Polycarbonate,Acrylic,Low power laser,Weld strength,Beam wobbling,Particle swarm optimization
更新于2025-09-23 15:19:57
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A measurement method for calibrating kinematic parameters of industrial robots with point constraint by a laser displacement sensor
摘要： This paper proposes a novel calibration method for robot kinematic parameters by constraining a command point with only one single laser displacement sensor. Then, a kinematic error model including both the robot parameter errors and the errors between the robot base frame and the measurement frame is established. An identification algorithm comprising the least square method and the Particle Swarm Optimization algorithm is developed. Comparison simulations are carried out with the proposed method, a least square method, and the traditional identified method. Experiments show that the estimated compensation results are significant with the mean reduced from 10.259mm to 0.845 mm. A verification experiment shows the mean of the relative deviations is decreased from1.674 mm to 0.538 mm.
关键词： algorithm,point constraint,least square method,laser displacement sensor,Robotic kinematic calibration,Particle Swarm Optimization (PSO)
更新于2025-09-23 15:19:57
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Simulation and experimental validation of fast adaptive particle swarm optimization strategy for photovoltaic global peak tracker under dynamic partial shading
摘要： The P–V characteristics of PV array has one peak under uniformly distributed irradiances. Whereas, there are many peaks in the P–V curve when the irradiance is not uniformly distributed over the PV array which is called “partial shading conditions (PSCs)”. Due to its robustness in tracking the global peak (GP) of many applications, metaheuristic techniques are used as maximum power point tracker (MPPT) for the PV system under PSCs. Particle swarm optimization (PSO) has been used in this paper for this purpose. Three problems associated with the PSO have been solved in this paper using a novel fast adaptive PSO (APSO) strategy. The problem of long convergence time has been solved by updating starting values of the duty ratio of the DC-DC boost converter to be at the anticipated places of peaks. This modification reduces the convergence time and avoids the premature convergence. The problem of stored GP in the memory will prevent the PSO from capturing the current GP in case of it is lower than the stored one. This problem is solved in this paper by updating the memorized GP with the current maximum power when it is not changed for two successive iterations. The third problem of sudden change in PSCs is solved by using the updated values of duty ratio at anticipated peaks as initial values for particles. To the best of the authors’ knowledge, these problems have not been discussed or solved before in the literature. A comparison to the state-of-the-art random initialization PSO strategy shows the superiority of the proposed APSO technique in terms of tracking speed and dynamic GP tracking. The results obtained from the simulation of this strategy proved its superiority in always tracking the GP under dynamic PSCs change.
关键词： Partial shading conditions,Photovoltaic,Dynamic irradiance change,Maximum power point tracker,Global peak,Adaptive particle swarm optimization
更新于2025-09-23 15:19:57
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New binary particle swarm optimization on dummy sequence insertion method for nonlinear reduction in optical direct-detection orthogonal frequency division multiplexing system
摘要： In the paper, a novel new binary particle swarm optimization method based on dummy sequence insertion is proposed and experimentally demonstrated in the IM-DD optical orthogonal frequency division multiplexing (OOFDM) system. This technique can mitigate nonlinearity of OOFDM system without any channel side information. Experimental results demonstrate that compared to the original scheme, the improvement in the receiver sensitivity by the proposed scheme is 1.9 dB and 3.2 dB with launch powers of 2 dBm and 8 dBm, respectively, at the BER of FEC 3.8 × 10^{-3} after transmission over 100-km standard single-mode fiber. At a complementary cumulative distribution function of 10^{-4}, the PAPR of OFDM signal can be reduced about 2.8 dB by using the proposed scheme, while the receiver-side hardware is the same as the origin.
关键词： Optical fiber communication,Particle swarm optimization (PSO),Dummy sequence insertion (DSI),Orthogonal frequency division multiplexing (OFDM)
更新于2025-09-19 17:15:36
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Holistic and local patch framework for 6D object pose estimation in RGB-D images
摘要： 6D object pose estimation is a challenging problem of great importance arising in computer vision and many practical applications. In this paper, we present a novel framework for 6D object pose estimation in RGB-D images. By contrast with recent holistic or local patch-based method, we combine holistic and local patches together to fulfill this task. The proposed method has three stages, including holistic patch extraction, local patch regression and 6D pose refinement. In the first stage, we employ an existing convolutional neural network to roughly predict the location of target object and extract holistic patches, which is trained with synthetic rendering data. In the second stage, an improved Convolutional Auto-Encoder (CAE) is employed to learn the condensed feature representation of local patch, and coarse 6D object pose can be estimated by the regression of feature voting. Finally, we utilize Particle Swarm Optimization (PSO) to refine 6D object pose. The proposed method is evaluated on three challenging public datasets which can test the performance under background clutter, foreground occlusion as well as multiple-instance conditions. Moreover, we provide extensive experiments on the various parameters of the framework such as the dimension of local patch feature and some parameters in PSO. Several experimental results demonstrate that the proposed method outperforms some other state-of-the-art methods.
关键词： Convolutional neural network,Particle swarm optimization,Local patch,6D object pose estimation,Holistic patch,RGB-D images
更新于2025-09-19 17:15:36