Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and ...
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Reinforcement learning(RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming(ADP) within the control community. This paper reviews recent developments in ADP along with RL and its applications to various advanced control fields. First, the background of the development of ADP is described, emphasizing the significance of regulation and tracking control problems. Some effective offline and online algorithms for ADP/adaptive critic control are displayed, where the main results towards discrete-time systems and continuous-time systems are surveyed, ***, the research progress on adaptive critic control based on the event-triggered framework and under uncertain environment is discussed, respectively, where event-based design, robust stabilization, and game design are reviewed. Moreover, the extensions of ADP for addressing control problems under complex environment attract enormous attention. The ADP architecture is revisited under the perspective of data-driven and RL frameworks,showing how they promote ADP formulation ***, several typical control applications with respect to RL and ADP are summarized, particularly in the fields of wastewater treatment processes and power systems, followed by some general prospects for future research. Overall, the comprehensive survey on ADP and RL for advanced control applications has d emonstrated its remarkable potential within the artificial intelligence era. In addition, it also plays a vital role in promoting environmental protection and industrial intelligence.
Out-of-distribution detection is one of the most critical issue in the deployment of machine learning. The data analyst must assure that data in operation should be compliant with the training phase as well as underst...
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Globally, biomass usage as a supply of non-depletable resources materials used in the production of energy at their rawest state is an issue. Pyrolysis is a method of thermally treating biomass that as a consequence i...
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The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as...
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ISBN:
(数字)9798350377170
ISBN:
(纸本)9798350377187
The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment.
In emerging consumer healthcare, high-performance and robust medical image segmentation methods are essential for personalized diagnosis and treatment. Thus, early screening of aneurysms reduces the risk of aneurysm r...
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In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays...
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Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune...
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Learning behavior in legged robots presents a significant challenge due to its inherent instability and complex constraints. Recent research has proposed the use of a large language model (LLM) to generate reward func...
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We have been witnessing a rapid growth in quantum computing research over the years, with the emergence of demonstrable quantum computers of moderate size. The major issues that are faced to run a quantum algorithm re...
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Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in Io...
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Applications of internet-of-things(IoT)are increasingly being used in many facets of our daily life,which results in an enormous volume of *** computing and fog computing,two of the most common technologies used in IoT applications,have led to major security *** are on the rise as a result of the usage of these technologies since present security measures are *** artificial intelligence(AI)based security solutions,such as intrusion detection systems(IDS),have been proposed in recent *** technologies that require data preprocessing and machine learning algorithm-performance augmentation require the use of feature selection(FS)techniques to increase classification accuracy by minimizing the number of features *** the other hand,metaheuristic optimization algorithms have been widely used in feature selection in recent *** this paper,we proposed a hybrid optimization algorithm for feature selection in *** proposed algorithm is based on grey wolf(GW),and dipper throated optimization(DTO)algorithms and is referred to as *** proposed algorithm has a better balance between the exploration and exploitation steps of the optimization process and thus could achieve better *** the employed IoT-IDS dataset,the performance of the proposed GWDTO algorithm was assessed using a set of evaluation metrics and compared to other optimization approaches in 2678 CMC,2023,vol.74,no.2 the literature to validate its *** addition,a statistical analysis is performed to assess the stability and effectiveness of the proposed *** results confirmed the superiority of the proposed approach in boosting the classification accuracy of the intrusion in IoT-based networks.
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