A review of artificial intelligence applications in high-speed railway systems

In recent years,the global surge of High-speed Railway(HSR)revolutionized ground transportation,providing secure,comfortable,and punctual services.The next-gen HSR,fueled by emerging services like video surveillance,emergency communication,and real-time scheduling,demands advanced capabilities in real-time perception,automated driving,and digitized services,which accelerate the integration and application of Artificial Intelligence(AI)in the HSR system.This paper first provides a brief overview of AI,covering its origin,evolution,and breakthrough applications.A comprehensive review is then given regarding the most advanced AI technologies and applications in three macro application domains of the HSR system:mechanical manufacturing and electrical control,communication and signal control,and transportation management.The literature is categorized and compared across nine application directions labeled as intelligent manufacturing of trains and key components,forecast of railroad maintenance,optimization of energy consumption in railroads and trains,communication security,communication dependability,channel modeling and estimation,passenger scheduling,traffic flow forecasting,high-speed railway smart platform.Finally,challenges associated with the application of AI are discussed,offering insights for future research directions.

INTELLIGENT INTEGRATION CONTROL OF ROTATING DISK VIBRATION

The rotating disk is a basic machine part that is u sed widely in industry. The motion equation is transformed into the dynamic equa tion in real modal space. The personating intelligent integration is introduced to improve the existing control method. These modes that affect the transverse vibration mainly are included to simulate the vibration of rotating disk, and two methods are applied separately on condition that the sensor and the ac tuator are collocated and non collocated. The results obtained by all sided si mulations show that the new method can obtain better control effect, especially when the sensor and the actuator are non collocated.

Application of Distributed Intelligent Power Supply Technology in Expressway Tunnels

With the coordinated development of today's social economy with science and technology,various advanced technologies are being used in highway engineering,especially the distributed intelligent power supply technology in expressway tunnels,which has a very significant advantage.In order to realize the effective application of this technology and promote the power supply effect in expressway tunnel,this study analyzes the advantages of this technology and its application in expressway tunnel,hoping to provide scientific reference for the application of distributed intelligent power supply technology and the engineering development of expressway tunnels.

Design of Clustering Techniques in Cognitive Radio Sensor Networks

In recent decades,several optimization algorithms have been developed for selecting the most energy efficient clusters in order to save power during trans-mission to a shorter distance while restricting the Primary Users(PUs)interfer-ence.The Cognitive Radio(CR)system is based on the Adaptive Swarm Distributed Intelligent based Clustering algorithm(ASDIC)that shows better spectrum sensing among group of multiusers in terms of sensing error,power sav-ing,and convergence time.In this research paper,the proposed ASDIC algorithm develops better energy efficient distributed cluster based sensing with the optimal number of clusters on their connectivity.In this research,multiple random Sec-ondary Users(SUs),and PUs are considered for implementation.Hence,the pro-posed ASDIC algorithm improved the convergence speed by combining the multi-users clustered communication compared to the existing optimization algo-rithms.Experimental results showed that the proposed ASDIC algorithm reduced the node power of 9.646%compared to the existing algorithms.Similarly,ASDIC algorithm reduced 24.23%of SUs average node power compared to the existing algorithms.Probability of detection is higher by reducing the Signal-to-Noise Ratio(SNR)to 2 dB values.The proposed ASDIC delivers low false alarm rate compared to other existing optimization algorithms in the primary detection.Simulation results showed that the proposed ASDIC algorithm effectively solves the multimodal optimization problems and maximizes the performance of net-work capacity.

Model of Production Planning and Scheduling in Shop Floor Based on Collaboration and Competition

The planning and scheduling in real shop floor is actually achieved by coordination between different persons. In this process, cooperation is mainstream, but competition also exists, for example, the competition between different groups, operators with the same skill, etc. In multi-agent based shop floor management and control system, this competition and cooperation relation must be embodied. The general process of shop floor production planning and scheduling is studied, and a colored Petri-net model for the competition and cooperation process of three main agents in such system to achieve shop floor production planning and scheduling is presented. The evaluating method of bids in bidding process that especially embodies the competition relationship is also presented. This colored Petri-net model gives a clear illustration of this complex coordination process to system designers, effectively promotes the cooperative development.

A Grid as Smart as the Internet

A new era of electricity is dawning that combines the decarbonization of the grid with the extensive electrification of all sectors of society.A grid as smart as the internet is needed to harness the full potential of renewables,accommodate technology disruptions,embrace the rise of prosumers,and seamlessly integrate nano-,mini-,and micro-grids.The internet is built upon a layered architecture that facilitates technology innovations,and its intelligence is distributed throughout a hierarchy of networks.Fundamental differences between data flows and power flows are examined.The current operating paradigm of the grid is based on the conviction that a centralized grid operator is necessary to maintain instantaneous power balance on the grid.A new distributed paradigm can be realized by distributing this responsibility to sub-grids and requiring each sub-grid to maintain its net power balance.A grid as smart as the internet based on this new paradigm,as well as a hierarchical network structure and a layered architecture of operating principles,is presented.

Towards an Internet-like Power Grid

The great challenges faced by modern power systems require a fresh look at the conventional operation paradigm. The significant challenges faced by modern power systems require an innovative method for the conventional operation paradigm. We claim that the decarbonization of the power grid and extensive electrification of numerous sectors of human activity can only be fostered by a self-adaptable and smart power grid that manifests similar qualities to those of the Internet. The Internet is constructed on a layered architecture that facilitates technology innovations and its intelligence is distributed throughout a hierarchy of networks. In this paper, the fundamental differences between the network data flows and power flows are examined, and the basic requirements for an innovative operation paradigm are highlighted. The current power grid is operated in a highly inflexible, centralized manner to meet increased security goals. A new highly flexible, distributed architecture can be realized by distributing the operation responsibility in smaller areas or even in grid components that can make autonomous decisions. The characteristics of such a power grid are presented, and the key features and advances for the on-going transition to a sustainable power system are identified. Finally, a case study on distributed voltage control is presented and discussed.

Hyper-Distributed Hyper-Parallel Self-Organizing Dynamic Scheduling Based on Solitary Wave

This paper presents a new soliton approach to hyper-distributed hyper-parallel self-organizing dynamic scheduling for task allocations among rational autonomous agents in a multi-agent system (MAS). This approach can overcome many drawbacks of other mechanisms currently used for coalition formation and cooperation in MAS. The thorny problems, such as overabundant bid, social behaviors, colony intelligence, variable neighbors, and interdepen-dency, can easily be treated by using the proposed approach, whereas they are very difficult for other conventional approaches. The simulation on a distributed transport scheduling sys-tem shows the soliton approach featured by hyper-parallelism, effectiveness, openness, dynamic alignment and adaption.

Iterative Learning Control for Discrete Parabolic Distributed Parameter Systems

In this paper, iterative learning control(ILC) technique is applied to a class of discrete parabolic distributed parameter systems described by partial difference equations. A P-type learning control law is established for the system. The ILC of discrete parabolic distributed parameter systems is more complex as 3D dynamics in the time, spatial and iterative domains are involved.To overcome this difficulty, discrete Green formula and analogues discrete Gronwall inequality as well as some other basic analytic techniques are utilized. With rigorous analysis, the proposed intelligent control scheme guarantees the convergence of the tracking error. A numerical example is given to illustrate the effectiveness of the proposed method.