With a large number of adjustable loads and new energy sources connected. Distribution networks are increasingly in the form of active distribution networks. This situation introduces more stochasticity and uncertaint...
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ISBN:
(纸本)9798350377477;9798350377460
With a large number of adjustable loads and new energy sources connected. Distribution networks are increasingly in the form of active distribution networks. This situation introduces more stochasticity and uncertainty into the active distribution network load equivalence modeling problem. At the same time, in the case of high stochasticity and time- varying, the method of constructing the load equivalence model needs to consider multiple influencing factors. Therefore, this paper proposes a multi-objective reinforcement learning active distribution grid load equivalent modeling method based on evidential reasoning. This method is divided into five steps. First, a multi-attribute analysis is performed to identify the set of evaluation indicators, the set of candidate solutions, the set of evaluation ratings, and the set of evaluation criteria set, candidate solution set, and evaluation level set. The confidence evaluation vector is subsequently obtained. In the second step, multi-evidence fusion is performed after obtaining confidence evaluation vectors of candidate solutions. The approximate degree of superiority of the candidate solutions can subsequently be obtained. In the third step, utility analysis is used to compare the average utility values of different candidate solutions and select the final candidate. In the fourth step, the active distribution network load equivalence modelingprocess is modeled as a Markov decision process. In the fifth step, the scenarios determined in the third step are brought into the fourth step to solve for the key parameters of the isotropic model. Simulation results show that the method proposed in this paper can obtain the required load equivalence model for active distribution networks.
Chemical plants require reliable systems for pollutant abatement. These processes often operate under cyclic abatement and regeneration cycles over extended periods of time. Throughout this period, the abatement syste...
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Chemical plants require reliable systems for pollutant abatement. These processes often operate under cyclic abatement and regeneration cycles over extended periods of time. Throughout this period, the abatement systems experience a multitude of phenomena that may degrade performance in a fashion that is challenging to predict by first-principle models. These complex phenomena offer an opportunity to leverage data-driven models. To improve their predictive ability, data driven models can be complemented with physics -based information that constrains modeling results. In this contribution, we describe a hybrid modeling approach where physics -derived features are developed to enable data -driven models to effectively predict the performance of real pollutant abatement systems in the Dow Chemical Company.
The importance of flavor in foods cannot be overstated, as it plays a crucial role in consumer preferences and choices. Gas Chromatography-Mass Spectrometry (GC-MS) has emerged as a vital tool in food flavor character...
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Communication-Based Train control (CBTC) Systems, consisting of ground equipment and onboard equipment, used to control the speed of train operation, ensure safe and efficient operation of trains, and is the core of u...
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ISBN:
(纸本)9798350385113;9798350385106
Communication-Based Train control (CBTC) Systems, consisting of ground equipment and onboard equipment, used to control the speed of train operation, ensure safe and efficient operation of trains, and is the core of urban rail transit. When the train control system is attacked by information, the safety and continuity of train operation will be affected to a certain extent. The paper fully combines the safety redundancy structure and "fault-safety" characteristics of the train control system, and establishes a risk assessment model for the train control system based on the Analytic Hierarchy process (AHP) method. The fuzzy comprehensive evaluation method is used to assess the risk of the train control system, accurately reflecting the risk level of the train control system. Provide certain reference for information security analysis of train control systems.
data Pipeline plays an indispensable role in tasks such as modeling machine learning and developing data products. With the increasing diversification and complexity of data sources, as well as the rapid growth of dat...
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With the development of Internet information technology in China, the construction industry also began to abandon the traditional manual drawing, calculation and design methods and use the 3D courtyard landscape model...
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Over the last fifteen years, various frameworks for data-aware process modelling have been proposed, several of which provide a set of evaluation criteria but which differ in their focus, the terminology used, the lev...
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ISBN:
(纸本)9783031342400;9783031342417
Over the last fifteen years, various frameworks for data-aware process modelling have been proposed, several of which provide a set of evaluation criteria but which differ in their focus, the terminology used, the level of detail used to describe their criteria and how these are evaluated. In addition, there are well-established evaluation frameworks of a more general nature that can be applied to data-centric process modelling too. A comprehensive and unbiased evaluation framework for (multi-)modelling approaches that also caters for more general aspects such as understandability, ease of use, model quality, etc., does not yet exist and is therefore the research gap addressed in this paper. This paper addresses this gap by using existing evaluation frameworks and developing a taxonomy that is used to categorise all the criteria from existing evaluation frameworks. The results are then discussed and related to the challenges and concerns identified by practitioners.
Microstructure-sensitive materials design has become popular among materials engineering researchers in the last decade because it allows the control of material performance through the design of microstructures. In t...
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Microstructure-sensitive materials design has become popular among materials engineering researchers in the last decade because it allows the control of material performance through the design of microstructures. In this study, the microstructure is defined by an orientation distribution function. A physics-informed machine learning approach is integrated into microstructure design to improve the accuracy, computational efficiency, and explainability of microstructure-sensitive design. When data generation is costly and numerical models need to follow certain physical laws, machine learning models that are domain-aware perform more efficiently than conventional machine learning models. Therefore, a new paradigm called the physics-informed neural network (PINN) is introduced in the literature. This study applies the PINN to microstructure-sensitive modeling and inverse design to explore the material behavior under deformation processing. In particular, we demonstrate the application of PINN to small-data problems driven by a crystal plasticity model that needs to satisfy the physics-based design constraints of the microstructural orientation space. For the first problem, we predict the microstructural texture evolution of copper during a tensile deformation process as a function of initial texturing and strain rate. The second problem aims to calibrate the crystal plasticity parameters of the Ti-7Al alloy by solving an inverse design problem to match the PINN-predicted final texture prediction and the experimental data.
The data-driven execution of object-centric processes in information systems requires powerful access control concepts that allow controlling, for example, which attributes of a business object a particular user (role...
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ISBN:
(纸本)9783031609992;9783031610004
The data-driven execution of object-centric processes in information systems requires powerful access control concepts that allow controlling, for example, which attributes of a business object a particular user (role) may read or write at a given point in time during process execution. In practice, it is crucial to be able to check whether the implementation of a fine-grained access control in an information system (i.e., the actual permissions) conforms with corporate requirements (e.g., compliance and security rules). If the execution of business processes is recorded in an event log, the actual access data can be compared with the specified permissions. Such a permission analysis includes the identification of both similarities and discrepancies between corporate requirements and actual implementation. This paper presents an approach for identifying, comparing, analyzing, evaluating, and classifying permissions in object-centric processes based on event logs.
This paper search for the understanding of the general behavior of users of the Learning Management System of the University of Cordoba (Monteria-Colombia), using web usage mining of log files. For this purpose, it wa...
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ISBN:
(纸本)9798350358568
This paper search for the understanding of the general behavior of users of the Learning Management System of the University of Cordoba (Monteria-Colombia), using web usage mining of log files. For this purpose, it was necessary to carry out a process of exploration of the data stored in the virtual campus in the access reference files, through usage mining. Exploratory mining techniques were implemented, with which the way to approach the data obtained was identified, then the results were consolidated, which allowed for their contrast with the descriptive analysis and the results of the web data mining. It should be noted that the behavior suggested by the model in the grouping of data is like that of the users in the descriptive part of the analysis. It could be concluded that the generation of predictive models using web mining techniques can be a tool of great importance for the knowledge of the patterns and behavior of the users of the virtual platform of the University of Cordoba, as well as the possibility of using this as support for a future process of updating and analysis of these patterns and behaviors.
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