This paper presents a new tuning method based on model parameters identified in closed-loop. For classical controllers such as PI(D) controllers a large number of simple tuning methods for various application areas ex...
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ISBN:
(纸本)9781849192521
This paper presents a new tuning method based on model parameters identified in closed-loop. For classical controllers such as PI(D) controllers a large number of simple tuning methods for various application areas exist. However, when it comes to designing a generalised predictive controller (GPC) four parameters have to be specified. To choose those parameters is not a trivial task since they are not directly related to control or regulation performance. The presented tuning method exploits model-parameters to select suitable controller parameters. Additionally, a Rhinehart filter is incorporated in the design to decrease the impact of noise, therefore, a fifth parameter has to be optimised. The proposed method has been tested in simulation and on a real system.
In this paper, a method of high order IIR filter design is proposed in which the coefficients in the canonical binary number system representation are searched by the simulated annealing algorithm. The high-quality II...
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The paper, basing on analysis of the Monte-Carlo Tree Search (MCTS) method and specific features of its behavior for various cases of usage, proposes a new variant of the method, which was called as Monte-Carlo Tree S...
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ISBN:
(纸本)9781509030071
The paper, basing on analysis of the Monte-Carlo Tree Search (MCTS) method and specific features of its behavior for various cases of usage, proposes a new variant of the method, which was called as Monte-Carlo Tree Search with Tree Shape Control (MCTS-TSC) and which uses original Depth-Width Criteria (DWCs) for both tree shape estimation and control during search and for estimation and selection of potentially better options for search continuation. Proposed Tree Shape Control (TSC) technique can be used with some other tuning, pruning, and learning techniques. Besides, it can provide better scheduling of MCTS parallelization.
Neural networks are used in many tasks today. One of them is the images processing. Autoencoder is very popular neural networks for such problems. Denoising autoencoder is an important autoencoder because some tasks w...
ISBN:
(数字)9781728199573
ISBN:
(纸本)9781728199580
Neural networks are used in many tasks today. One of them is the images processing. Autoencoder is very popular neural networks for such problems. Denoising autoencoder is an important autoencoder because some tasks we need a preprocessed image to get less noisy result. This research describes ways to analyze noisy images produced by a physically-based render engine and how to reduce that noise. The results showed that the algorithms are logarithmic.
This paper presents a new tuning method based on model parameters identified in closed-loop. For classical controllers such as PI(D) controllers a large number of simple tuning methods for various application areas ex...
This paper presents a new tuning method based on model parameters identified in closed-loop. For classical controllers such as PI(D) controllers a large number of simple tuning methods for various application areas exist. However, when it comes to designing a generalised predictive controller (GPC) four parameters have to be specified. To choose those parameters is not a trivial task since they are not directly related to control or regulation performance. The presented tuning method exploits model-parameters to select suitable controller parameters. Additionally, a Rhinehart filter is incorporated in the design to decrease the impact of noise, therefore, a fifth parameter has to be optimised. The proposed method has been tested in simulation and on a real system.
The paper deals with the development of the method of activity and the realization of the intelligent agent (IA) for semantic analysis of the natural language software requirements. This IA performs the analysis of th...
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ISBN:
(纸本)9781728140704
The paper deals with the development of the method of activity and the realization of the intelligent agent (IA) for semantic analysis of the natural language software requirements. This IA performs the analysis of the requirements, determines the number and percentage of missing indicators for determining the metrics of complexity and quality of software, displays which indicators are missing for each metric, and also forms the real ontology of the domain "Software Engineering" (part "Quality and complexity of software. Metric analysis"). During an experiment, which is conducted with the help of the realized IA, the semantic analysis of requirements for the Internet of Things (IoT)-system was performed. Such analysis provides an increase of the volume and ensures of the sufficiency of metric information in the software requirements, which, in turn, provides an improvement in the quality of the software of IoT-system.
Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second ve...
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Several instances of pneumonia with no clear etiology were recorded in Wuhan,China,on December 31,*** world health organization(WHO)called it COVID-19 that stands for“Coronavirus Disease 2019,”which is the second version of the previously known severe acute respiratory syndrome(SARS)Coronavirus and identified in short as(SARSCoV-2).There have been regular restrictions to avoid the infection spread in all countries,including Saudi *** prediction of new cases of infections is crucial for authorities to get ready for early handling of the virus ***:Analysis and forecasting of epidemic patterns in new SARSCoV-2 positive patients are presented in this research using metaheuristic optimization and long short-term memory(LSTM).The optimization method employed for optimizing the parameters of LSTM is Al-Biruni Earth Radius(BER)***:To evaluate the effectiveness of the proposed methodology,a dataset is collected based on the recorded cases in Saudi Arabia between March 7^(th),2020 and July 13^(th),*** addition,six regression models were included in the conducted experiments to show the effectiveness and superiority of the proposed *** achieved results show that the proposed approach could reduce the mean square error(MSE),mean absolute error(MAE),and R^(2)by 5.92%,3.66%,and 39.44%,respectively,when compared with the six base *** the other hand,a statistical analysis is performed to measure the significance of the proposed ***:The achieved results confirm the effectiveness,superiority,and significance of the proposed approach in predicting the infection cases of COVID-19.
The paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits freq...
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