This article develops a gradient-based search algorithm for selective harmonic elimination (SHE) to address the problems of high-computational cost, low-convergence speed, modulation index error, and slow-dynamic resp...
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This article develops a gradient-based search algorithm for selective harmonic elimination (SHE) to address the problems of high-computational cost, low-convergence speed, modulation index error, and slow-dynamic response often associated with SHE algorithms. First, the dimension of the search space is reduced by deriving intuitive equations to increase the search speed. Second, the desired modulation index is achieved by applying the proposed constraints. Third, gradient equations are modified to move and hold points in the reduced search space. Extensive comparative simulation studies show that, compared to conventional SHE methods, the proposed algorithm is highly efficient in producing smooth switching angle curves with minimal fluctuations over the entire modulation index range. The proposed method minimizes execution time and modulation index error, even with unbalanced dc input voltages. These superior characteristics are also experimentally verified on cascaded H-bridge inverters with different number of stages up to 25.
With the continuous expansion of the translation market, users ' demand for translation tools such as computer software is also increasing, resulting in various machine translation technologies and methods. Japane...
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With the continuous expansion of the translation market, users ' demand for translation tools such as computer software is also increasing, resulting in various machine translation technologies and methods. Japanese translation, as one of the important components of Chinese publicity work, has strong professionalism and complexity. In practice, how to effectively improve the translation quality of Japanese translation models using computer technology has always been a research issue of great concern. Based on this, we propose a game search algorithm and use it as a prototype to improve the algorithm. Then, a data mining model was established that can effectively improve search performance. This model solves the above problems by introducing genetic algorithms and dynamic programming theory. At the same time, in order to further improve the efficiency of existing data mining algorithms, we need to explore more efficient methods and strategies. After experimental verification, the four data mining models proposed in this article perform the best in numerical fitting. Overall, in Japanese multi context translation systems, the use of data mining techniques based on computer game search algorithms can provide more accurate and matching related translations. Compared to traditional Japanese translation software, it has higher quality and efficiency.
Because a significant number of algorithms in computational science include search challenges and a large number of algorithms that can be transformed into search problems have garnered significant attention, especial...
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Because a significant number of algorithms in computational science include search challenges and a large number of algorithms that can be transformed into search problems have garnered significant attention, especially the time rate and accuracy of search, a quantum walk search algorithm on hypergraphs,whose aim is to reduce time consumption and increase the readiness and controllability of search, is proposed in this paper. First, the data points are divided into groups and then isomorphic to the permutation set. Second, the element coordinates in the permutation set are adopted to mark the position of the data points. search the target data by the controllable quantum walk with multiparticle on the ring. By controlling the coin operator of quantum walk, it is determined that search algorithm can increase the accuracy and controllability of search. It is determined that search algorithm can reduce time consumption by increasing the number of search particles. It also provides a new direction for the design of quantum walk algorithms, which may eventually lead to entirely new algorithms.
Fiber Reinforced Polymer (FRP) plates are widely used to strengthen structural members, but their potential is limited by plate end debonding failure. Existing models that are developed to address plate end debonding ...
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Fiber Reinforced Polymer (FRP) plates are widely used to strengthen structural members, but their potential is limited by plate end debonding failure. Existing models that are developed to address plate end debonding failure considered only few parameters and primarily based on fracture mechanics or shear strength of beams. Following study aims to develop a Back Propagation Neural Network (BPNN) model optimized by a quantum-computations and multi-strategy enhanced Sparrow search algorithm (QMESSA) to effectively forecast the plate end debonding load of externally bonded FRP plates. Where the model utilized complex nonlinear relationship between all the prominent governing parameters and the debonding load. Optimization accuracy and generalization is hindered by local minima problem in BPNN. Incorporating QMESSA significantly reduced the local minima problem in BPNN substantiated by an increased testing data sets regression value from 0.82 to 0.98. Reliability analysis showed that the model outperformed the existing international codes and shear-based model in terms of accuracy and stability. Results from the correlation analysis of parameters revealed that the web reinforcement ratio is the most influential parameter for debonding prediction. Therefore, QMESSA optimized BPNN model can be used as an effective tool for designing FRP to prevent FRP plate end debonding.
The current scenario sees the potential emergence of challenges such as power imbalances and energy dissipation upon the incorporation of distributed photovoltaic (PV) systems into distribution networks, impacting pow...
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The current scenario sees the potential emergence of challenges such as power imbalances and energy dissipation upon the incorporation of distributed photovoltaic (PV) systems into distribution networks, impacting power quality and economic viability. To address these identified risks, this study introduces an innovative combinatorial search algorithm designed to autonomously derive optimal planning strategies for distribution networks. The process begins by establishing distinct planning models for distributed PVs and distribution network systems, followed by the application of the search algorithm to align these models and generate relevant Pareto datasets and multi-objective positioning criteria. By strategically combining and optimizing existing solutions to bolster the distribution network's load-carrying capacity, the optimal strategy is progressively refined under the guidance of multiple objective constraints. Subsequent multiphase simulation experiments validate the efficacy of our approach in minimizing energy losses when compared to analogous methodologies. The distribution network integration planning strategies derived through our method showcase outstanding performance in reducing energy losses, conducting steady-state voltage safety assessments, optimizing installation capacity utilization rates, and enhancing economic returns, thus emphasizing the substantial potential of our approach in facilitating the seamless integration of distributed PVs into distribution networks.
In this paper, the multiple-rendezvous trajectory optimization problem is studied, which refers to optimizing rendezvous epochs for a single spacecraft to service multiple targets. It is found that the problem has mul...
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In this paper, the multiple-rendezvous trajectory optimization problem is studied, which refers to optimizing rendezvous epochs for a single spacecraft to service multiple targets. It is found that the problem has multiple properties, such as a predictable trough number in each dimension. A novel Lambert property-based swarm search algorithm (LPSSA) that incorporates this problem-specific knowledge is proposed to improve efficiency. The design aims to improve the global search capability in the prophase and the local search capability in the anaphase. The algorithm has two different branches and is switched by a proposed complexity index. When the index is relatively large, the initial variables are distributed in some priority trough regions, and the update mechanism is divided into three stages. When the index is relatively small, the initial variables are first distributed to all trough regions and then selected. Multiple subpopulations search independently in the iterative process, and an annexation mechanism is introduced. An improved method for handling boundary conditions is applied in both branches. Besides, the improved mechanisms can also be combined with other swarm search algorithms. Numerical simulations show that the proposed method has a more stable convergence performance and a more optimal solution than the conventional algorithms.
This paper presents a quick search algorithm of the fracture angle of inter-fiber fracture (IFF) criterion and a progressive damage model considering the dynamic fracture toughness effect. The fracture angle determina...
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This paper presents a quick search algorithm of the fracture angle of inter-fiber fracture (IFF) criterion and a progressive damage model considering the dynamic fracture toughness effect. The fracture angle determination of the IFF criterion is necessary and time-consuming, which has limited its practicality. Therefore, to accurately calculate stress exposure factors under various combinations of stress states, a highly efficient algorithm is needed. In this paper, a novel algorithm using stress tractions on the fracture plane and the golden section search (GSS) is promoted. Through a series of simulation tests, this novel algorithm has been proven to be exact and efficient compared with other two common algorithms, which saves an average of 63.2 % and 28.1 % of the time in 1 million calculations and 2 h 2 min 4 sec and 39 min 2 sec in simulations. Additionally, fracture toughness, which controls material damage evolution process, also has strain-rate effect like elastic modulus and strength. Hence, a new progressive damage model considering the dynamic fracture toughness effect is proposed. The results of dynamic compression and ballistic impact tests and simulations demonstrate the fidelity of the novel damage model.
Shenvi et *** proposed a quantum algorithm based on quantum walking called Shenvi-Kempe-Whaley(SKW)algorithm,but this search algorithm can only search one target state and use a specific search target state ***,when t...
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Shenvi et *** proposed a quantum algorithm based on quantum walking called Shenvi-Kempe-Whaley(SKW)algorithm,but this search algorithm can only search one target state and use a specific search target state ***,when there are more than two target nodes in the search space,the algorithm has certain *** though a multiobjective SKW search algorithm was proposed later,when the number of target nodes is more than two,the SKW search algorithm cannot be mapped to the same quotient *** addition,the calculation of the optimal target state depends on the number of target states *** previous studies,quantum computing and testing algorithms were used to solve this *** these solutions require more Oracle calls and cannot get a high accuracy ***,to solve the above problems,we improve the multi-target quantum walk search algorithm,and construct a controllable quantum walk search algorithm under the condition of unknown number of target *** dividing the Hilbert space into multiple subspaces,the accuracy of the search algorithm is improved from p_(c)=(1/2)-O(1/n)to p_(c)=1-O(1/n).And by adding detection gate phase,the algorithm can stop when the amplitude of the target state becomes the maximum for the first time,and the algorithm can always maintain the optimal number of iterations,so as to reduce the number of unnecessary iterations in the algorithm process and make the number of iterations reach t_(f)=(π/2)(?).
The intelligent home decoration design platform is more and more popular with the deepening of artificial intelligent. Room search is a key step of a design platform, which determines the flexibility, real-time and ac...
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ISBN:
(纸本)9798350381269;9798350381276
The intelligent home decoration design platform is more and more popular with the deepening of artificial intelligent. Room search is a key step of a design platform, which determines the flexibility, real-time and accuracy. What's more, an intelligent platform should allows any users even an unprofessional user to design home decoration easily. However, some existing algorithms of platform cannot meet the requirements, especially, when there are bridges and overhangs in the 2D floor plan. In this paper, based on the minimum cycle theory, we propose an algorithm to search all the rooms of any given or drawn graph real-time and correctly. This algorithm can deal with the graph containing Bridges and overhangs effectively, and search accurately to find the minimum cycle(that is, the room) where they are located. The algorithm is tested well in practice.
Concepts in search theory have developed since World War *** study of search plans has found considerable interest among searchers due to its wide applications in our *** for lost targets either located or moved is of...
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Concepts in search theory have developed since World War *** study of search plans has found considerable interest among searchers due to its wide applications in our *** for lost targets either located or moved is often a time-critical issue,especially when the target is very *** many commercial and scientific missions at sea,it is of crucial importance to find lost targets *** illustrate a technique known as coordinated search,that completely characterizes the search for a randomly located target on a *** idea is to avoid wasting time looking for a missing *** searchers or robots start from the center of a circle to search out a lost target,the first searcher looks for the target on the right side of the circular area,and the second one looks for it on the left *** time taken to detect the target is obtained by assuming the target’s position has a symmetric *** procedures to facilitate the detection of the target are presented as an algorithm and as a *** application demonstrates the applicability of this search technique and the associated decrease in search *** effectiveness is illustrated by numerical results,which indicates considerable promise.
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