The power oscillation has a bad impact on the safety and economy of power plants and power grids, and the causes and solutions of the power oscillation problem of secondary reheat units are not mature. In order to qui...
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ISBN:
(纸本)9798350377477;9798350377460
The power oscillation has a bad impact on the safety and economy of power plants and power grids, and the causes and solutions of the power oscillation problem of secondary reheat units are not mature. In order to quickly solve the power oscillation problem of the secondary reheat unit, a simulation and analysis method of the power oscillation of the secondary reheat unit considering the characteristics of the valve adjustment was proposed. By analyzing the influence of operating parameters and adjusting parameters on the characteristics of the valve, the modular modeling of the secondary reheat unit is carried out, and the power model considering the secondary reheating process and the actuator model considering the adjusting characteristics of the valve are proposed, then the optimized adjusting parameters are proposed based on this. The simulation analysis was carried out with reference to the actual power oscillation case, which verified the correctness of the theoretical analysis and the effectiveness of the proposed method are provided an effective decision-making reference for the cause finding of the power oscillation of the secondary reheat unit.
With the continuous spread and globalization of infectious diseases, infectious disease prevention and control has become an important task for both countries and the world. Traditional infectious disease monitoring m...
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ISBN:
(纸本)9798350385113;9798350385106
With the continuous spread and globalization of infectious diseases, infectious disease prevention and control has become an important task for both countries and the world. Traditional infectious disease monitoring methods often rely on manual collection and analysis of data, which is inefficient and easily limited by human errors. However, the development of artificial intelligence and big data technology has provided new opportunities for infectious disease prevention and control. This article introduces the application of artificial intelligence in infectious disease monitoring. By using artificial intelligence algorithms and models, real-time monitoring and analysis of infectious disease data can be carried out, predicting the spread trend and risk of infectious diseases. This helps to detect and report infectious disease outbreaks, thus taking corresponding prevention and control measures and reducing the spread and impact of the epidemic. At the same time, this article explores the application of big data in infectious disease prevention and control. By using big data technology, in-depth mining and analysis of patient case data, virus gene sequences, transmission chain information, and other data can be carried out to discover the characteristics and patterns of infectious diseases, and be used to build an infectious disease warning system to predict and prevent the occurrence of infectious diseases in advance. Finally, this article discusses the application cases of artificial intelligence and big data in infectious disease prevention and control. By combining artificial intelligence and big data technology, the entire process of monitoring and management of infectious diseases can be achieved.
Business process simulation (BPS) is a versatile technique for estimating process performance across various scenarios. Traditionally, BPS approaches employ a control-flow-first perspective by enriching a process mode...
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ISBN:
(纸本)9798350365030
Business process simulation (BPS) is a versatile technique for estimating process performance across various scenarios. Traditionally, BPS approaches employ a control-flow-first perspective by enriching a process model with simulation parameters. Although such approaches can mimic the behavior of centrally orchestrated processes, such as those supported by workflow systems, current control-flow-first approaches cannot faithfully capture the dynamics of real-world processes that involve distinct resource behavior and decentralized decision-making. Recognizing this issue, this paper introduces AgentSimulator, a resource-first BPS approach that discovers a multi-agent system from an event log, modeling distinct resource behaviors and interaction patterns to simulate the underlying process. Our experiments show that AgentSimulator achieves state-of-the-art simulation accuracy with significantly lower computation times than existing approaches while providing high interpretability and adaptability to different types of process-execution scenarios.
In this article, a learning-based controller is proposed to realize motion policy learning based on intuitive human demonstrations. The position, velocity, and force data during the demonstration are collected as inpu...
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In this article, a learning-based controller is proposed to realize motion policy learning based on intuitive human demonstrations. The position, velocity, and force data during the demonstration are collected as input features without any physical contact with the human demonstrator, and an algorithm is designed to automatically label the data in combination with motion and force data. After the learning process, the robot can complete the assembly according to the human demonstrations, and the proposed controller will generate different angular acceleration commands as control inputs to help finish the manipulation well. Finally, a comprehensive analysis, including Lyapunov stability and Lipschitz constraint, is also provided to guarantee the stability and security of this learning-based controller. Sufficient experiments based on the real robot system verify the effectiveness of the proposed method.
This study undertakes a comprehensive analysis of topic modeling techniques-N on-negative Matrix Factorization (NMF), Latent Dirichlet Allocation (LDA), and Correlation Explanation (Corex) enhanced by BERT's depth...
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On the basis of a component-level approach, mathematical and simulation models are created for various modules to examine the operation of the APU (Auxiliary Power Unit) and the ATS (Air Turbine Starter) in civil airc...
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The ongoing transition from a linear (produce-use-dispose) to a circular economy poses significant challenges to current state-of-the-art information and communication technologies. In particular, the derivation of in...
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The functionalities of AI-powered mobile apps or systems heavily depend on the given training dataset. The challenge, in this case, is that a learning system will change its behavior due to a slight change in the data...
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ISBN:
(纸本)9798350365054
The functionalities of AI-powered mobile apps or systems heavily depend on the given training dataset. The challenge, in this case, is that a learning system will change its behavior due to a slight change in the dataset. Current alternative approaches for evaluating these apps either focus on individual performance measurements such as accuracy, etc. Inspired by principles of the decision tree test method in software engineering, this paper provides a tutorial discussion on intelligent AI test modeling chat systems including basic concepts, validation process, testing scopes, approaches, and needs. The report is about an intelligent AI test modeling chatbot system that is built and implemented based on an innovative 3D AI test model for AI-powered functions in intelligent mobile apps to support model-based AI function testing, test data generation, auto test scripting and execution, and adequate test coverage analysis.
The Behavioral Toolbox is a collection of Matlab functions for modeling, analysis, and design of dynamical systems using the behavioral approach to systems theory and control. It implements newly emerged direct data-d...
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The Behavioral Toolbox is a collection of Matlab functions for modeling, analysis, and design of dynamical systems using the behavioral approach to systems theory and control. It implements newly emerged direct data-driven methods as well as classical parametric representations of linear time-invariant systems. At the core of the toolbox is a nonparameteric representation of the finitehorizon behavior by an orthonormal basis. The current version has education and research goals and isn't intended for handling "big data". The paper presents five problems-checking systems equality, interconnection of systems, errors-in-variables least-squares smoothing, missing input estimation, and data-driven forecasting-and describes their solution by the methods in the toolbox.
Business processmodeling enable smoother and more efficient decision making in the organizations as it achieve consistency and standardization of their operations, facilitate communication and collaboration between d...
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