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2021 2022
Articles

  • Review on key technologies of green power supply for port microgrid

    Guangdi Li, ... Boyu Liu
    Complex Eng Syst 2023;3:1. DOI: 10.20517/ces.2022.46
    Abstract
    With the development of ship electrification, the demand for energy in ports is increasing. The ... MORE
    With the development of ship electrification, the demand for energy in ports is increasing. The location and natural resources of ports also create conditions for the development of ship electrification. This paper firstly analyzes the current development status of floating solar power generation technology and offshore wind power generation technology, summarizes the obstacles facing the development of offshore power generation platforms, introduces the materials and structures that can be used for floating power generation platforms, and then introduces the port microgrid topology from three aspects of AC microgrid (AC), DC microgrid (DC) and AC/DC hybrid microgrid (AC/DC) hybrid structure, and compares the three structures. Then the existing control methods are reviewed from the perspective of port capacity planning and the application of distributed control in port energy planning is emphasized. Finally, port energy management strategies are introduced from the perspective of multiple time scales, and relevant cases are listed, and the advantages and disadvantages of management strategies under different time scales are compared. At the end of the paper, several advanced smart ports are given as examples, and the new energy used by each port and its development scale are analyzed, and the future clean and efficient ports are envisioned. LESS      Full article
    Review|Published on: 31 Jan 2023
    Full-Text | PDF-1.2M

  • Generation of high definition map for accurate and robust localization

    Zhengjie Huang, ... Shuanglin Wu
    Complex Eng Syst 2023;3:2. DOI: 10.20517/ces.2022.43
    Abstract
    This paper presents a framework for generating high-definition (HD) map, and then achieves accurate and ... MORE
    This paper presents a framework for generating high-definition (HD) map, and then achieves accurate and robust localization by virtue of the map. An iterative approximation based method is developed to generate a HD map in Lanelet2 format. A feature association method based on structural consistency and feature similarity is proposed to match the elements of the HD map and the actual detected elements. The feature association results from the HD map are used to correct lateral drift in the light detection and ranging odometry. Finally, some experimental results are presented to verify the reliability and accuracy of autonomous driving localization. LESS      Full article
    Research Article|Published on: 31 Jan 2023
    Full-Text | PDF-5.6M

  • Interpretable AI for bio-medical applications

    Anoop Sathyan, ... Kelly Cohen
    Complex Eng Syst 2022;2:18. DOI: 10.20517/ces.2022.41
    Abstract
    This paper presents the use of two popular explainability tools called Local Interpretable Model-Agnostic Explanations ... MORE
    This paper presents the use of two popular explainability tools called Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP) to explain the predictions made by a trained deep neural network. The deep neural network used in this work is trained on the UCI Breast Cancer Wisconsin dataset. The neural network is used to classify the masses found in patients as benign or malignant based on 30 features that describe the mass. LIME and SHAP are then used to explain the individual predictions made by the trained neural network model. The explanations provide further insights into the relationship between the input features and the predictions. SHAP methodology additionally provides a more holistic view of the effect of the inputs on the output predictions. The results also present the commonalities between the insights gained using LIME and SHAP. Although this paper focuses on the use of deep neural networks trained on UCI Breast Cancer Wisconsin dataset, the methodology can be applied to other neural networks and architectures trained on other applications. The deep neural network trained in this work provides a high level of accuracy. Analyzing the model using LIME and SHAP adds the much desired benefit of providing explanations for the recommendations made by the trained model. LESS      Full article
    Research Article|Published on: 28 Dec 2022
    Full-Text | PDF-799K

  • Stability analysis for highly nonlinear switched stochastic systems with time-varying delays

    Jing Sun, Hui Wang
    Complex Eng Syst 2022;2:17. DOI: 10.20517/ces.2022.48
    Abstract
    In this paper, we examine the stability of highly nonlinear switched stochastic systems (SSSs) with ... MORE
    In this paper, we examine the stability of highly nonlinear switched stochastic systems (SSSs) with time-varying delays, where the switching time instants are deterministic rather than stochastic. Herein, the boundedness of the global solution is first proven for highly nonlinear SSSs via the average dwell time (ADT) method and multiple Lyapunov function (MLF) approach. Then, the stability criteria for qth moment exponential stability and almost surely exponential stability are presented. The main difficulty lies in the presence of switching and time-varying delay terms, which prevents the validation of existing methods. New inequality techniques have been developed to counteract the effects of switching signals and time-varying delays. Finally, an example is provided to verify the effectiveness of the results. LESS      Full article
    Research Article|Published on: 27 Dec 2022
    Full-Text | PDF-2.6M

  • Pulsar identification based on generative adversarial network and residual network

    Zelun Bao, ... Xin Zheng
    Complex Eng Syst 2022;2:16. DOI: 10.20517/ces.2022.30
    Abstract
    The search for pulsars is an important area of study in modern astronomy. The amount ... MORE
    The search for pulsars is an important area of study in modern astronomy. The amount of collected pulsar data is increasing exponentially as the performance of modern radio telescopes improves, necessitating the improvement of the original pulsar search methods. Artificial intelligence techniques are currently being used in pulsar candidate identification tasks. However, improving the accuracy of pulsar candidate identification using artificial intelligence techniques remains a challenge. Because the amount of collected data is so large, the number of real pulsar samples is very limited, which leads to a serious sample imbalance problem. Many existing methods ignore this issue, making it difficult for the model to reach the optimal solution. A framework combining generative adversarial networks and residual networks is proposed to greatly alleviate the problem of sample inequality. The framework first generates stable pulsar images using generative adversarial networks and then designs a deep neural network model based on residual networks to identify pulsar candidates using intra-block and inter-block residual connectivity. The ResNet approach has a better ability to fit the data than the CNN approach and can achieve the extraction of features with more classification ability with a smaller dataset. Meanwhile, the data expanded by the high-quality simulated samples generated by the generative adversarial network can provide richer identification features and improve the identification accuracy for pulsar candidates. LESS      Full article
    Research Article|Published on:  8 Dec 2022
    Full-Text | PDF-549K

  • How to deal with the complexity in robotic systems?

    Hamid Reza Karimi
    Complex Eng Syst 2022;2:15. DOI: 10.20517/ces.2022.33
    Editorial|Published on: 30 Sep 2022
    Full-Text | PDF-252K
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Most Cited Papers In Last Two Years

  • Sampled-based bipartite tracking consensus of nonlinear multiagents subject to input saturation

    Luyang Yu, ... Yurong Liu
    Complex Eng Syst 2022;2:6. DOI: 10.20517/ces.2022.08
    Abstract
    This paper is concerned with the sampled-data bipartite tracking consensus problem for a class of ... MORE
    This paper is concerned with the sampled-data bipartite tracking consensus problem for a class of nonlinear multiagent systems (MASs) with input saturation. Both competitive and cooperative interactions coexist among agents in the concerned network. By resorting to Lyapunov stability theory and the linear matrix inequality (LMI) technique, several criteria are obtained to ensure that the considered MASs can achieve the bipartite tracking consensus. Besides, with the help of the decoupled method, the dimensions of LMIs are reduced for mitigation of the computation complexity so that the obtained results can be applied to large-scaled MASs. Furthermore, the controller gain matrix is explicitly expressed in terms of solutions to a set of LMIs. We also provide an estimate of elliptical attraction domain of bipartite tracking consensus. Finally, numerical simulation is exploited to support our theoretical analysis. LESS      Full article
    Research Article|Published on: 17 May 2022
    Full-Text | PDF-781K

  • Backstepping-based state estimation for a class of stochastic nonlinear systems

    Xin Yin, Qichun Zhang
    Complex Eng Syst 2022;2:1. DOI: 10.20517/ces.2021.13
    Abstract
    The state estimation problem is investigated for a class of continuous-time stochastic nonlinear systems, where ... MORE
    The state estimation problem is investigated for a class of continuous-time stochastic nonlinear systems, where a novel filter design method is proposed based on backstepping design and stochastic differential equation. In particular, the structure of the filter is developed following the nonlinear system model, and then the estimation error dynamics can be described by a stochastic differential equation. Motivated by backstepping procedure, the nonlinear dynamics can be converted to an Ornstein–Uhlenbeck process via the control loop design. Thus, the estimation can be achieved once the estimation error is bounded and the variance of the error can be optimized. Since the ideal estimation error is a Brownian motion, the filter parameters can be selected following the Lyapunov stability theory and variance assignment method. Following the same framework, the multivariate stochastic systems can be handled with the block backstepping design. To validate the presented design approach, a numerical example is given as the simulation results to demonstrate the state estimation performance. LESS      Full article
    Research Article|Published on: 19 Jan 2022
    Full-Text | PDF-380K

  • Developments of digital twin technologies in industrial, smart city and healthcare sectors: a survey

    Daoguang Yang, ... Shen Yin
    Complex Eng Syst 2021;1:3. DOI: 10.20517/ces.2021.06
    Abstract
    Digitization and digitalization have already changed our world significantly. Further disruptions are imminent with the ... MORE
    Digitization and digitalization have already changed our world significantly. Further disruptions are imminent with the ongoing digital transformation, a major component of which is digital twins. As the big data techniques, Internet of Things, cloud computing, and artificial intelligence algorithms advance, the digital twin technology has entered a phase of rapid development. It has been stated to be one of the top ten most promising technologies. Although it is still in its early stages, digital twins are already being widely used in a variety of fields, especially in industry, smart cities, and smart health, which are points that attract most researchers to study. In the literature, there can be seen numerous articles and reviews on digital twins, published every year in these three fields. It is therefore timely, even necessary, to provide an analysis of the published work. This is the motivation behind this article, the focus of which is the major research and application areas of digital twins. The survey first analyzes the recent developments of digital twins, then summarizes the theoretical underpinnings of the technology, and finally concludes with specific developments in various application areas of digital twins. It also discusses the challenges that may be encountered in the future. LESS      Full article
    Review|Published on: 30 Sep 2021
    Full-Text | PDF-4.4M

  • Performance assessment of pantograph and overhead system based on a vertical coupling dynamics model of the railway system

    Yang Song, Fuchuan Duan
    Complex Eng Syst 2022;2:9. DOI: 10.20517/ces.2022.09
    Abstract
    The increase of train speed leads to a violent vibration of the pantograph and overhead ... MORE
    The increase of train speed leads to a violent vibration of the pantograph and overhead system. To evaluate the interaction performance of the pantograph and overhead system, a whole railway dynamics model including the track, vehicle, pantograph, and overhead system is established. The overhead system is represented by the finite element approach using the analytical formulas of nonlinear cable and truss elements. The vehicle is modeled by a multi-rigid-body system with a pantograph installed on its roof. A beam element with elastic foundations is used to model the track, which possesses harmonic and random irregularities. An iterative algorithm is implemented to solve the nonlinear behavior of the coupling model. The nonlinearities in the deformation of overhead system, the contact of the pantograph and contact line, and the contact of the vehicle-track are properly considered. Several numerical simulations are implemented to systematically investigate the influence of the vehicle-track vibration on the dynamic behavior of pantograph and overhead system. The results indicate that the vehicle-track vibration induced by the rail irregularities with large amplitude or certain wavelength can significantly aggravate the interaction performance of pantograph and overhead system. LESS      Full article
    Research Article|Published on: 16 Jun 2022
    Full-Text | PDF-3.5M
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About The Journal

  • ISSN

    2770-6249 (Online)

    Publisher

    OAE Publishing Inc.

    Article Processing Charges

    $1200

    Journal Flyer

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  • Editor-in-Chief

    Hamid Reza Karimi

    Publishing Model

    Gold Open Access

    Copyright

    Copyright is retained by author(s)

  • Publication Frequency

    Quarterly

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    Total publications: 30

    Total article views: 32,270

    Total article downloads: 5,001

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