This paper demonstrates the use of the multi-objective grey wolf algorithm to optimize a discrete Raman amplifier (DRA) in a P2O5-doped optical fiber. Specifically, the multi-objective grey wolf algorithm is combined ...
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This paper demonstrates the use of the multi-objective grey wolf algorithm to optimize a discrete Raman amplifier (DRA) in a P2O5-doped optical fiber. Specifically, the multi-objective grey wolf algorithm is combined with the DRA to carry out a process that seeks to maximize the gain and minimize the ripple. The P2O5-doped optical fiber employed in this study has a Raman gain coefficient spectrum with multiple peaks with different frequency shifts. This allows them to be combined in more complex ways than optical fibers with a single peak in the Raman gain spectrum. Consequently, the gain curve produced with this fiber has the potential to be more adjustable even when fewer pumps are used. Thus, this paper explores this fact to perform, to the best of our knowledge, the first specialized optimization process reported in the scientific literature of a wideband discrete Raman amplifier in a P2O5-doped optical fiber. With a different gain profile of this fiber compared to those of traditional standard optical fibers, it was possible to design a wideband DRA, going from 1530 nm to 1675 nm, covering C+L+U bands, maintaining a ripple of up to 8 dB with a net gain of 14 dB using only 3 pumps. Moreover, this work demonstrates for the first time, through a comparative analysis, that the multi-objective grey wolf algorithm performs better than the standard and well-known non-dominated sorting genetic optimization algorithm to optimize a DRA in a P2O5-doped optical fiber. The proposed DRA is a feasible, low-cost, and simple alternative for building fiber amplifiers for future high-bandwidth and wideband wavelength division multiplexing (WDM) communication systems, network infrastructures such as data centers, undersea cables, 5G and beyond, and cutting-edge research applications.
In order to obtain good geometry quality in the wire and arc additive manufacture, it is important to select the appropriate process parameters. Firstly, based on the 4-factor and 5-level experiments, the multi-object...
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In order to obtain good geometry quality in the wire and arc additive manufacture, it is important to select the appropriate process parameters. Firstly, based on the 4-factor and 5-level experiments, the multi-objective mathematical model of process parameters and geometry quality is established by response surface methodology. Secondly, an adaptive greywolfalgorithm for solving multi-objective problems is proposed. The algorithm introduces external Archive, adaptive hunting mechanism, and fusion polynomial mutation mechanism to improve the search ability of the greywolfalgorithm. Experiments show that the Pareto set obtained by the adaptive multi-objective grey wolf algorithm is more diverse and convergent than the other five well-known algorithms. Meanwhile, in order to obtain the desired geometry quality, the TOPSIS algorithm is used to analyze the Pareto set obtained to get the optimal process parameters.
In Internet of Things (IoT) application scenarios, the traditional method of prioritizing task offloading based on scalar information such as maximum tolerable latency fails to meet the processing requirements of urge...
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This article aims to enhance low-light images by proposing a novel algorithm called MoGDF. It departs from the traditional approach of using deep learning with low-light and normal images as training data. Instead, ex...
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This article aims to enhance low-light images by proposing a novel algorithm called MoGDF. It departs from the traditional approach of using deep learning with low-light and normal images as training data. Instead, exposure images at five different exposure scales are generated using a proposed model called EIPM, which consists of an improved Gamma function. Then it introduces a feature extraction network called FMEM, which leverages an improved PFPN structure to enhance the fusion of multi-scale information and strengthen the connection between high-level and low-level semantic information. Finally, it optimizes the fusion weights using an improved multiple-objectivegreywolf optimization algorithm with comprehensive improvements in the convergence factor updating strategy, adaptive inertia weight strategy, and individual position strategy. The experiments show that the MoGDF outperforms the current state-of-the-art algorithms in terms of color restoration and detail preservation, and has significant advantages in objective and subjective evaluation metrics, with improvements of 5.69%, 2.60%, 1.11%, and 6.67% in PSNR, SSIM, NIQE, and LPIPS, respectively.(c) 2023 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).
The surge in construction expenditures on the one hand and environmental pollution on the other hand have led to the suggestion of native structures in accordance, which is common in advanced countries. In this resear...
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The surge in construction expenditures on the one hand and environmental pollution on the other hand have led to the suggestion of native structures in accordance, which is common in advanced countries. In this research, the meta-heuristic method is used to select the optimal design based on the objective functions determined in four structural frames in the study area of Tabriz metropolis. The target functions in this research include the parameters of cost and construction time, CO2 emitted due to the production of materials and the weight of the structure, which was considered based on the type of performance and the effect of each of these functions in the studied frames. As a result, the minimum and maximum construction time is 20.95% and 30.19%, respectively, of the total construction time of all structures related to Intermediate Steel Moment-Resisting Frame and Intermediate Reinforced Concrete Moment-Resisting Frame, as well as Intermediate Steel Moment-Resisting Frame with Special Concentrically Braced Frame with a value of 20/36% The lowest amount of CO2 emission caused by the production of materials among the studied frames was allocated to it. It was determined based on the target functions and introduced as a green and environmentally friendly structure.
An improved multi-objective grey wolf algorithm with simulated annealing (MOGWO/SA) is proposed in this paper. Compared with origin algorithm, the new multi-objective grey wolf algorithm has combined with simulated an...
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ISBN:
(纸本)9783030005603;9783030005597
An improved multi-objective grey wolf algorithm with simulated annealing (MOGWO/SA) is proposed in this paper. Compared with origin algorithm, the new multi-objective grey wolf algorithm has combined with simulated annealing algorithm optimization and the new leading wolf selection mechanism, which makes the algorithm with stronger global searching ability and faster rate of convergence. The diversity of non-dominated solutions and ductility of MOGWO/SA are also improved. Finally, MOGWO/SA are applied to the ecological optimal operation of small hydropower stations for both the maximum output of generated energy and the maximum assurance rate of ecological water requirement.
When the pumped storage unit (PSU) operates in the low water heads, it is easy to enter the 'S' characteristic area, which leads to the chaotic phenomenon of the hydraulic transient of the PSU and makes the ad...
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When the pumped storage unit (PSU) operates in the low water heads, it is easy to enter the 'S' characteristic area, which leads to the chaotic phenomenon of the hydraulic transient of the PSU and makes the adjustment and control of the PSU under the no-load start-up condition extremely difficult. In this paper, a strategy of integrating three-stage guide vane opening law and fuzzy fractional-order proportion integration differentiation (PID) controller is proposed for the low water head start-up condition of PSU. Firstly, based on the mathematical model of pumped storage unit regulation system (PSURS), the mapping relationship between water head, no-load guide vane opening, the frequency switch point of the controller, and the number of rotational speed fluctuations is analyzed. Then a three-stage start-up optimal strategy based on a fuzzy fractional-order PID controller is proposed. On this basis, the multi-objective optimization method of control parameters for the three-stage start-up strategy is proposed by introducing the rotational speed overshoot and integrated time and absolute error (ITAE) index. Furthermore, to achieve efficient tuning of the high-dimensional control parameters for the multiobjective optimization method, a multi-objective grey wolf algorithm is proposed by introducing quantum space theory. Finally, numerical experiments are carried out to compare the start-up transition process under the three-stage start-up optimal strategy and conventional standard mode. The results indicate that compared with the conventional method, the proposed method has significant advantages in improving the dynamic stability and control quality of the low water head start-up of the PSU. The fluctuation times of the rotational speed of the PSU optimized and regulated by the novel method is 0 times, the regulation time is reduced by 34 s at most compared with the conventional method, and the steady-state error is only 0.003.
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