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Now showing items 171-180 of 181
Next-generation energy systems for sustainable smart cities: Roles of transfer learning
(
Elsevier
, 2022 , Article Review)
Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while improving grid stability and meeting service demand. This is possible by adopting next-generation energy systems, which leverage ...
LEARNING-BASED CONTROL OF CANCER CHEMOTHERAPY TREATMENT
(
Elsevier B.V.
, 2017 , Article)
The increasing threat of cancer to human life and the improvement in survival rate of this disease due to effective treatment has promoted research in various related fields. This research has shaped clinical trials and ...
Data-Driven Koopman Operator Based Cyber-Attacks for Nonlinear Control Affine Cyber-Physical Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
This paper studies the data-driven implementation of stealthy cyber-attacks for a class of nonlinear cyber-physical systems (CPS). In particular, we consider and study zero dynamics and covert cyber-attacks. By utilizing ...
Data-driven sensor fault detection and isolation of nonlinear systems: Deep neural-network Koopman operator
(
John Wiley and Sons Inc
, 2023 , Article)
This paper proposes a data-driven sensor fault detection and isolation approach for the general class of nonlinear systems. The proposed method uses deep neural network architecture to obtain an invariant set of basis ...
Security Analysis of Merging Control for Connected and Automated Vehicles
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Conference Paper)
Securing traffic flows in internet of vehicles (IoV) environments for connected and automated vehicles (CAVs) is a critical task as it should be done in real-time to allow vehicles' controllers engagement on time. In this ...
Data-driven fault detection and isolation of nonlinear systems using deep learning for Koopman operator
(
ISA - Instrumentation, Systems, and Automation Society
, 2023 , Article)
This paper proposes a data-driven actuator fault detection and isolation approach for the general class of nonlinear systems. The proposed method uses a deep neural network architecture to obtain an invariant set of basis ...
Neural network-based model predictive control system for optimizing building automation and management systems of sports facilities
(
Elsevier Ltd
, 2022 , Article)
Sports facilities are considered complex buildings due to their high energy demand and occupancy profiles. Therefore, their management and optimization are crucial for reducing their energy consumption and carbon footprint ...
Modified Particle Filters for Detection of False Data Injection Attacks and State Estimation in Networked Nonlinear Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Networked control systems which transfer data over communication networks may suffer from malicious cyber attacks by injecting false data to the transferred information. Such attacks can cause performance degradation of ...
Performance and energy optimization of building automation and management systems: Towards smart sustainable carbon-neutral sports facilities
(
Elsevier Ltd
, 2022 , Other)
Sports facilities (SFs) consume massive energy given their unique demand profiles and operation requirements. Intelligent and effective solutions are necessary to tackle the matter of facilities’ sustainability and efficiency. ...
An efficient component map generation method for prediction of gas turbine performance
(
American Society of Mechanical Engineers (ASME)
, 2014 , Conference Paper)
Improving efficiency, reliability and availability of gas turbines have become more than ever one of the main areas of interest in gas turbine research. This is mainly due to the stringent environmental regulations that ...