We present a novel approach to solving a specific type of quasilinear boundary value problem with p-Laplacian that can be considered an alternative to the classic approach based on the mountain pass theorem. We introd...
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We present a novel approach to solving a specific type of quasilinear boundary value problem with p-Laplacian that can be considered an alternative to the classic approach based on the mountain pass theorem. We introduce a new way of proving the existence of nontrivial weak solutions. We show that the nontrivial solutions of the problem are related to critical points of a certain functional different from the energy functional, and some solutions correspond to its minimum. This idea is new even for p = 2. We present an algorithm based on the introduced theory and apply it to the given problem. The algorithm is illustrated by numerical experiments and compared with the classic approach.
The paper uses parallel computation of grid and data grid as theoretical basis. The isomerism of each node and difference of communication rate under grid environment, and massive data query makes query operations of ...
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ISBN:
(纸本)9781479932795
The paper uses parallel computation of grid and data grid as theoretical basis. The isomerism of each node and difference of communication rate under grid environment, and massive data query makes query operations of database difficult. For the new structural characteristic, the paper proposes a parallel JOIN algorithm based on massive data, it fully uses parallelism and reduces transmission volume to shorten response time. The paper includes implementation and optimization of JOIN algorithm, fault-tolerant mechanism, RDMM, partition and transmission of massive data.
With the development of globalization and artificial intelligence,as well as the outbreak of COVID-19,unmanned vehicles have played an important role in cargo *** order to better analyze the research directions of unm...
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With the development of globalization and artificial intelligence,as well as the outbreak of COVID-19,unmanned vehicles have played an important role in cargo *** order to better analyze the research directions of unmanned vehicle distribution,this paper summarizes the models and algorithms of unmanned vehicle distribution *** research results show that most of the studies have established the goal of optimizing the total costs or travel *** researchers have begun to study multi-objective optimization problems,but there are certain limitations,so some studies convert these problems into single-objective optimization for solving,such as converting time and energy consumption into cost,waiting time into distance,and time delay into penalty *** the development of unmanned vehicle distribution technology,in future research,a multi-objective model with the lowest cost,the shortest distance and the best security should be established and *** studies have proposed heuristic algorithms for solving the unmanned vehicle distribution problem,and improved optimization solutions have been *** order to ensure the diversity of solution methods,and give consideration to solution time and solution quality,hybrid methods with other algorithms will be a future research direction,for example,the combination of heuristic algorithm and exact *** the gradual deepening of research,integrated distribution of multiple types of unmanned equipment will become the focus of future research.
It is very important to locate the short-circuit fault in a power system quickly and accurately. Electromagnetic time reversal (EMTR) has drawn increasing attention because of its clear physical background and excelle...
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It is very important to locate the short-circuit fault in a power system quickly and accurately. Electromagnetic time reversal (EMTR) has drawn increasing attention because of its clear physical background and excellent performance. This article studies the EMTR method for locating the short-circuit fault of transmission and distribution lines with or without branches, and introduces a simulated annealing algorithm to accelerate the calculation of an EMTR fault location. This algorithm is different from the traditional exhaustive method in that it solves the corresponding optimization problem, thus improving the location speed by up to an order of magnitude. With the help of graph theory, a method is proposed that automatically splits a complex line topology with branches into several one-dimensional (1-D) lines. The problem of short-circuit fault location in the branching lines is then transformed into several 1-D optimization problems, which are then solved by the optimization algorithm. This solves the problem of realizing rapid location in a power network with branches. Numerical experiments are carried out in a distribution network model to demonstrate the effectiveness of the method. Results under different conditions show the method works reliably and efficiently.
The aerodynamic optimization design of high-speed trains(HSTs)is crucial for energy conservation,environmental preservation,operational safety,and speeding *** study aims to review the current state and progress of th...
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The aerodynamic optimization design of high-speed trains(HSTs)is crucial for energy conservation,environmental preservation,operational safety,and speeding *** study aims to review the current state and progress of the aerodynamic multi-objective optimization of ***,the study explores the impact of train nose shape parameters on aerodynamic *** parameterization methods involved in the aerodynamic multiobjective optimization ofHSTs are summarized and classified as shape-based and disturbance-based ***,the advantages and limitations of each parameterizationmethod,aswell as the applicable scope,are briefly *** addition,the NSGA-II algorithm,particle swarm optimization algorithm,standard genetic algorithm,and other commonly used multi-objective optimization algorithms and the improvements in the field of aerodynamic optimization for HSTs are ***,this study investigates the aerodynamic multi-objective optimization technology for HSTs using the surrogate model,focusing on the Kriging surrogate models,neural network,and support vector ***,the construction methods of surrogate models are summarized,and the influence of different sample infill criteria on the efficiency ofmulti-objective optimization is ***,advanced aerodynamic optimization methods in the field of aircraft have been briefly introduced to guide research on the aerodynamic optimization of ***,based on the summary of the research progress of the aerodynamicmulti-objective optimization ofHSTs,future research directions are proposed,such as intelligent recognition technology of characteristic parameters,collaborative optimization of multiple operating environments,and sample infill criterion of the surrogate model.
Homomorphic filtering (HF) is a methodology that separates an image into two components: illumination and reflectance. Through the processing of these components, it is possible to significantly improve the contrast o...
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Homomorphic filtering (HF) is a methodology that separates an image into two components: illumination and reflectance. Through the processing of these components, it is possible to significantly improve the contrast of the low-frequency components while preserving the edges and sharp features of the image. The parameter values of the filter that produces the best possible contrast enhancement depends on the image conditions for each image. However, finding the optimal parameters for the filter can be challenging, often involves a trial-and-error process, and can be prone to errors due to human factors. In this paper, we consider the problem of identifying the filter parameters as an optimization problem. Under such conditions, the cluster chaotic optimization (CCO) method is used to efficiently explore the parameter space by evaluating an objective function that assesses the contrast quality of an enhanced image. The experimental results show that the proposed method produces competitive results in terms of quality, stability, and accuracy compared with other methods on various datasets. Different metrics were evaluated to demonstrate the quality of the results of our method compared with the other algorithms.
In medical imaging processing, image fusion is the process of combining complementary information from different or multimodality images to obtain a high-quality and informative fused image in order to improve clinica...
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In medical imaging processing, image fusion is the process of combining complementary information from different or multimodality images to obtain a high-quality and informative fused image in order to improve clinical diagnostic accuracy. In this paper, we propose a novel variational fusion model based on contrast and gradient features, the weight images and the fused images are constrained by the total variation regularization. The salient contrast features and clear soft tissue structure information of source CT and MR images can be preserved in the fused images. The variational problem is solved by a fast split optimization algorithm. In the numerical experiments, the proposed method is compared with seven state-of-the-art methods, and the comparison metrics MI, Q(W) and Q(G) are calculated for assessment. The proposed method shows a comprehensive advantage in preserving the contrast features as well as texture structure information, not only in visual effects but also in objective assessments.
Active vehicle suspension systems play a crucial role in isolating vibration between the car body and pavement. In this article, based upon Takagi-Sugeno (T-S) fuzzy model, a novel optimization control algorithm is fi...
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Active vehicle suspension systems play a crucial role in isolating vibration between the car body and pavement. In this article, based upon Takagi-Sugeno (T-S) fuzzy model, a novel optimization control algorithm is first proposed to furthest improve driving comfort level for fuzzy suspension systems compared with traditional existing approach. First, sufficient criteria for designing non parallel distribution compensation (non-PDC) fuzzy controller to improve driving comfort level and guarantee corresponding suspension constrained requirements are presented. Then, in the context of ensuring stability of studied systems, considering the feasible areas of member-ship functions (MFs) of non-PDC controller, a new MFs online optimization strategy is built for fuzzy suspension systems for the first time. By this proposed novel optimization algorithm, the values of controller MFs (CMFs) can be updated in real-time so as to obtain a better driving comfort level while improv-ing suspension-constrained requirements. Sufficient criteria is obtained to guarantee the convergence of the designed cost function with the help of the Lyapunov stability theory. In the end, the usefulness, as well as superiority of the proposed online optimization strategy, are illustrated by contrastive verification.
High-performance concrete performs better than normal concrete because of using additional components than usual concrete components. Several artificially based analytics were used to evaluate the compressive strength...
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High-performance concrete performs better than normal concrete because of using additional components than usual concrete components. Several artificially based analytics were used to evaluate the compressive strength (CS) of high-performance concrete (HPC) made with fly ash and blast furnace slag. In the present research, the Aquila optimizer (AO) was used to find the best values for the determinants of the adaptive neuro-fuzzy inference system (ANFIS), and radial basis function neural network (RBFNN) that may be changed to enhance performance. The suggested approaches were established using 1030 tests, eight inputs (a primary component of mix designs, admixtures, aggregates, and curing age), and the CS as the forecasting objective. The results of the outperformed model were then contrasted with those found in the existing scientific literature. Calculation results point to the potential benefit of combining AO-RBFNN and AO-ANFIS study. The AO-ANFIS demonstrated significantly higher R-2 (Train: 0.9862, Test: 0.9922) and lower error metrics (such as: RMSE at 2.1434 (train) and 1.2763 (Test)) when compared to the AO-RBFNN and previously published articles. In summation, the proposed method for determining the CS of HPC supplemented with blast furnace slag and fly ash may be established using the suggested AO-ANFIS analysis.
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