The deep neural network is a reliable technical support for cloud computing and edge computing. It has excellent nonlinear approximation and generalization capabilities, making it suitable for classifying and predicti...
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The paper’s main focus is on speech-based emotion detection in Malayalam phone call records, including emergency calls [(emergency response support system (ERSS)] and elicited *** emotions taken into consideration ar...
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In this article, we solve the fast finite-time stabilization as well as adaptive neural control design issues for a class uncertain stochastic nonlinear systems. By employing the mean value theorem, the pure-feedback ...
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To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidize...
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To address the pressing need for intelligent and efficient control of circulating fluidized bed(CFB)units,it is crucial to develop a dynamic model for the key operating parameters of supercritical circulating fluidized bed(SCFB)***,data-knowledge-driven dynamic model of bed temperature,load,and main steam pressure of the SCFB unit has been ***,a knowledge-driven method is employed to develop a dynamic model for key operating parameters of SCFB *** model parameters are determined based on the operating data of the unit and continuously optimized in real ***,Bidirectional Long Short-Term Memory combined with Convolutional Neural Network and Attention Mechanism is utilized to build the dynamic model of bed temperature,load,and main steam ***,a collaboration and integration method based on the critic weight method and the variation coefficient method is proposed to establish data-knowledge-driven model of key operating parameters for SCFB *** model displays great accuracy and fitting ability compared with other methods and effectively captures the dynamic characteristics,which can provide a research basis for the design of intelligent flexible control mode of SCFB unit.
This paper addresses the issue of adaptive fixed-time tracking control (FTTC) for a category of parametric nonlinear systems characterized by unknown nonlinear control coefficient (UNCC) and unknown external disturban...
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The widespread dissemination of misinformation and propaganda has become a crucial issue in societal conversations. This study presents an innovative framework to counter propaganda within information warfare using a ...
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The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic ***,concerns have been raised over th...
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The application of artificial intelligence technology in Internet of Vehicles(lov)has attracted great research interests with the goal of enabling smart transportation and traffic ***,concerns have been raised over the security and privacy of the tons of traffic and vehicle *** this regard,Federated Learning(FL)with privacy protection features is considered a highly promising ***,in the FL process,the server side may take advantage of its dominant role in model aggregation to steal sensitive information of users,while the client side may also upload malicious data to compromise the training of the global *** existing privacy-preserving FL schemes in IoV fail to deal with threats from both of these two sides at the same *** this paper,we propose a Blockchain based Privacy-preserving Federated Learning scheme named BPFL,which uses blockchain as the underlying distributed framework of *** improve the Multi-Krum technology and combine it with the homomorphic encryption to achieve ciphertext-level model aggregation and model filtering,which can enable the verifiability of the local models while achieving ***,we develop a reputation-based incentive mechanism to encourage users in IoV to actively participate in the federated learning and to practice *** security analysis and performance evaluations are conducted to show that the proposed scheme can meet the security requirements and improve the performance of the FL model.
State observers for nonlinear systems are often designed for a canonical form of this system. However, this form may possess singular points, where the vector field is not defined or a Lipschitz condition is not fulfi...
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In this contribution we discuss the design of functional observers for polynomial systems. Our approach is based on a high gain design employing an embedded observer. The functional to be estimated is generated from t...
The adaptive practical prescribed-time (PPT) neural control is studied for multiinput multioutput (MIMO) nonlinear systems with unknown nonlinear functions and unknown input gain matrices. Unlike existing PPT design s...
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