A promising technology that is projected to be implemented in the future is quantum computing, which is utilized to solve complicated problems using the useful features of quantum states. Numerous complex issues relating to computation mechanics may be resolved with the efficient use of quantum computing phenomena. Some of the benefits of quantum computing may include cost savings, the elimination of laboratory testing, and human and animal testing situations. Additionally, there are benefits associated with trade analysis and prospective benefits related to financial industries such as banking and business analytics. On the other side, quantum cybernetics studies the effects and principles underlying classical systems, quantum physics, and sophisticated computer systems.
Artificial intelligence methods and machine learning techniques are being applied to many fields, one of which is quantum cybernetics. Moreover, quantum systems aid in developing an upgraded version of the neural network's decision-making principles and applications. Furthermore, complicated quantum models contribute to achieving aerial data intelligence via drone implementations, quantum cybernetics, and artificial intelligence models. The Internet of Things models might be strengthened by using cooperative control applications in conjunction with quantum systems, which address security and privacy concerns through the parallelism inherent in quantum communication systems. The coordinated control connected with the deployment of multi-agent robotics and the environment may be related to quantum computing models and complicated quantum computing systems.
The applications mentioned above might be combined with quantum cybernetics or complicated quantum control systems to analyze vast and complex data sets using quantum inspired processes and algorithms capable of rapidly addressing difficult issues. The data analytics and privacy protection connected with IoT data may be efficiently controlled via quantum cybernetics since collecting data include numerous sensor environments and inputs. The combination of quantum cybernetics and AI models may develop new encryption techniques for countering cyber security threats. Thus, some of the anticipated applications of quantum cybernetics and complex quantum systems include the integration of artificial intelligence and deep learning models such as neural networks. Thus, key applications such as design, cybersecurity, financial systems, weather forecasting, and logistics optimization might be realized using sophisticated quantum computing systems and linked quantum cybernetics.
This special issue discusses the benefits of cybersecurity models, quantum computing, and complicated quantum control systems. Thus, researchers and academics might include a variety of combinational techniques linked with quantum systems to improve data analytics and solve challenging computational challenges.
List of Topics:
Deployment of quantum cybernetics in the evolutionary computing associated with complex data analytics
Intelligent interaction models associated with information visualization and machine to machine interaction with quantum cybernetics
Enhanced knowledge-base systems for data analytics and association represented along with complex quantum systems
Optimized pattern analysis and modeling associated with quantum computing models and methods
Quantum machine learning models with swarm intelligence in solving business data analytics
Incorporation of machine learning models with quantum computing in solving complex medical analysis
Deployment of quantum computing models in biometrics and bioinformatics associated with deep neural networks
Trends in application of complex quantum models to the industry 4.0
Deep transfer learning models for the evolutionary computing and financial analytics
Intelligent edge computing and real-world application monitoring combined with heuristic algorithm
