Computational Linguistics emphasizes the real-time consequences of modeling the utility of human languages. Applied Computational Linguistics can be utilized for several purposes in today's domain of scientific re...
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To improve the therapeutic effect of the rehabilitation hand exoskeleton robot, this paper analyzes the movable range of each index finger joint based on the structure of the newly proposed rehabilitation hand exoskel...
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To guarantee high-quality and trustworthy data, we first highlight the need of preprocessing. The dataset is prepared for analysis by using standard methods such as data cleansing, normalization, and feature engineeri...
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data science projects often involve various machine learning (ML) methods that depend on data, code, and models. One of the key activities in these projects is the selection of a model or algorithm that is appropriate...
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The design of antenna systems poses a significant challenge due to stringent performance requirements dictated by contemporary applications and the high computational costs associated with models, particularly full-wa...
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ISBN:
(纸本)9783031637742;9783031637759
The design of antenna systems poses a significant challenge due to stringent performance requirements dictated by contemporary applications and the high computational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter stage is especially critical as rigorous numerical optimization becomes essential for achieving optimal performance. In an increasing number of instances, global parameter tuning is necessary. Unfortunately, the use of nature-inspired algorithms, the prevalent choice for global design, is hindered by their poor computational efficiency. This article presents an innovative approach to cost-efficient global optimization of antenna input characteristics. Our methodology leverages response feature technology, ensuring inherent regularization of the optimization task by exploring the nearly-linear dependence between the coordinates of feature points and the antenna's dimensions. The optimization process is structured as a machine learning (ML) procedure, utilizing a kriging surrogate model rendering response features to generate promising candidate designs (infill points). This model is iteratively refined using accumulated EM simulation data. Further acceleration is achieved by incorporating multi-fidelity EM analysis, where initial sampling and surrogate model construction use low-fidelity EM simulations, and the ML optimization loop employs high-fidelity EM analysis. The multi-fidelity EM simulation data is blended into a single surrogate using co-kriging. Extensive verification of the presented algorithm demonstrates its remarkable computational efficiency, with an average running cost not exceeding ninety EM simulations per run and up to a seventy percent relative speedup over the single-fidelity procedure.
A Distributed control System is a concept of Network control Systems whose applications range from industrial control systems to the control of large physical experiments such as the ALICE experiment at CERN. The desi...
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A Distributed control System is a concept of Network control Systems whose applications range from industrial control systems to the control of large physical experiments such as the ALICE experiment at CERN. The design phase of the Distributed control Systems implementation brings several challenges, such as predicting the throughput and response of the system in terms of data-flow. These parameters have a significant impact on the operation of the Distributed control System, and it is necessary to consider them when determining the distribution of software/hardware resources within the system. This distribution is often determined experimentally, which may be a difficult, iterative process. This paper proposes a methodology for modeling Distributed control Systems using a combination of Finite-State Automata and Petri nets, where the resulting model can be used to determine the system's throughput and response before its final implementation. The proposed methodology is demonstrated and verified on two scenarios concerning the respective areas of ALICE detector control system and mobile robotics, using the MATLAB/Simulink implementation of created models. The methodology makes it possible to validate various distributions of resources without the need for changes to the physical system, and therefore to determine the appropriate structure of the Distributed control System.
Complex high-rise steel structures have many design variables. Through sensitivity analysis of grouping of different types of components, it can be determined that optimizing the form, quantity and arrangement of stee...
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Complex high-rise steel structures have many design variables. Through sensitivity analysis of grouping of different types of components, it can be determined that optimizing the form, quantity and arrangement of steel braces can effectively reduce the maximum inter-story drift, which is the controllingwind response of the structure, so as to save the time cost of optimization. Adjusting the form, quantity and arrangement of steel braces to achieve the ideal steel consumption on the premise of satisfying the limit of maximum inter-story drift is a process of re-analyzing the modified results and guiding the next modification until the results converge. An effective re-analysis method can also reduce the calculation times and save the time cost of optimization. In the optimization process, sensitivity analysis and reanalysis are indispensable. In this paper, high-rise braced steel frame structure is taken as the research object and the steel braces are divided into groups according to different vertical zones and different plane positions, to analyze the sensitivity of maximum inter-story drift under wind load to different groups of steel braces, and to study the reanalysismethod of specific steel structure system, specific design constraints, and specific optimization variables, so as to achieve rapid and efficient optimization design. Finally, a 150 m high-rise steel structure residence is taken as an engineering case to verify the correctness of sensitivity analysis results of high-rise steel structure for wind vibration stiffness performance control, and the effectiveness and practicability of re-analysis method in optimization design.
Aiming at the complexity of abnormal risk identification of active customers' safe power consumption, this paper proposed a clustering analysis method for abnormal risk identification of active customers' safe...
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Today's real time computers activities and applications required data services in the distributed platform where real time applications have been needed for databases, in which data and operations have special cha...
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With the continuous development and expansion of the power system, the transformer as an important part of it, its stability and reliability is crucial to the operation of the entire power system. Transformer bus plat...
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