Guest Editors
Prof. Zhengtian Wu, Suzhou University of Science and Technology, China
Prof. Michael V. Basin, the Autonomous University of Nuevo Leon, Mexico
Prof. Qing Gao, Beihang University, China
Summary
The research on intelligent decision and
intelligent control have promoted the development of smart city greatly.
Studies on these area have attracted engineers and scientists from various
disciplines such as control theory, mathematics, computer science,management,
and so on. This Special Issue will feature recent developments of intelligent
decision and intelligent control with applications in smart city. It aims to
provide a platform for sharing recent results and team experience to contribute
to the advancing of intelligent decision and intelligent control.
Potential
topics include but are not limited to the following:
l Combinatorial optimization of intelligent decision;
l Emergency management;
l Intelligent systems and control theory;
l Intelligent unmmaned systems;
l Advanced smart manufacturing;
l Smart city and smart grid;
l Intelligent Perceptual and Diagnosis of Equipment;
l Computer vision and its industrial applications;
l Integrated equipment design and validations;
l Robot design, control, and applications;
l Urban environment monitoring and emergency early warning;
l Pollution control policies and their social effects;
l Machine learning and deep learning.
Keywords
Intelligent decision; intelligent control; smart city; emergency management; smart manufacturing
Published Papers
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Open Access
ARTICLE
HVAC Optimal Control Based on the Sensitivity Analysis: An Improved SA Combination Method Based on a Neural Network
Lifan Zhao, Zetian Huang, Qiming Fu, Nengwei Fang, Bin Xing, Jianping Chen
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2741-2758, 2023, DOI:10.32604/cmes.2023.025500
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Aiming at optimizing the energy consumption of HVAC, an energy conservation optimization method was proposed for HVAC systems based on the sensitivity analysis (SA), named the sensitivity analysis combination method (SAC). Based on the SA, neural network and the related settings about energy conservation of HVAC systems, such as cooling water temperature, chilled water temperature and supply air temperature, were optimized. Moreover, based on the data of the existing HVAC system, various optimal control methods of HVAC systems were tested and evaluated by a simulated HVAC system in TRNSYS. The results show that the proposed SA combination method can reduce…
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Open Access
ARTICLE
MAQMC: Multi-Agent Deep Q-Network for Multi-Zone Residential HVAC Control
Zhengkai Ding, Qiming Fu, Jianping Chen, You Lu, Hongjie Wu, Nengwei Fang, Bin Xing
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2759-2785, 2023, DOI:10.32604/cmes.2023.026091
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract The optimization of multi-zone residential heating, ventilation, and air conditioning (HVAC) control is not an
easy task due to its complex dynamic thermal model and the uncertainty of occupant-driven cooling loads. Deep
reinforcement learning (DRL) methods have recently been proposed to address the HVAC control problem. However, the application of single-agent DRL for multi-zone residential HVAC control may lead to non-convergence or
slow convergence. In this paper, we propose MAQMC (Multi-Agent deep Q-network for multi-zone residential
HVAC Control) to address this challenge with the goal of minimizing energy consumption while maintaining
occupants’ thermal comfort. MAQMC is divided into MAQMC2 (MAQMC…
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Open Access
ARTICLE
Observer-Based Control for a Cable-Driven Aerial Manipulator under Lumped Disturbances
Li Ding, Yong Yao, Rui Ma
CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1539-1558, 2023, DOI:10.32604/cmes.2022.023003
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract With the increasing demand for interactive aerial operations, the application of aerial manipulators is becoming
more promising. However, there are a few critical problems on how to improve the energetic efficiency and pose
control of the aerial manipulator for practical application. In this paper, a novel cable-driven aerial manipulator used
for remote water sampling is proposed and then its rigid-flexible coupling dynamics model is constructed which
takes joint flexibility into account. To achieve high precision joint position tracking under lumped disturbances,
a newly controller, which consists of three parts: linear extended state observer, adaptive super-twisting strategy,
and fractional-order nonsingular terminal…
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Open Access
ARTICLE
A Road Segmentation Model Based on Mixture of the Convolutional Neural Network and the Transformer Network
Fenglei Xu, Haokai Zhao, Fuyuan Hu, Mingfei Shen, Yifei Wu
CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1559-1570, 2023, DOI:10.32604/cmes.2022.023217
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Convolutional neural networks (CNN) based on U-shaped structures and skip connections play a pivotal role in various image segmentation tasks. Recently, Transformer starts to lead new trends in the image segmentation task. Transformer layer can construct the relationship between all pixels, and the two parties can complement each other well. On the basis of these characteristics, we try to combine Transformer pipeline and convolutional neural network pipeline to gain the advantages of both. The image is put into the U-shaped encoder-decoder architecture based on empirical combination of self-attention and convolution, in which skip connections are utilized for local-global semantic feature…
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Open Access
ARTICLE
Optimal Joint Space Control of a Cable-Driven Aerial Manipulator
Li Ding, Rui Ma, Zhengtian Wu, Rongzhi Qi, Wenrui Ruan
CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 441-464, 2023, DOI:10.32604/cmes.2022.022642
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract This article proposes a novel method for maintaining the trajectory of an aerial manipulator by utilizing a fast nonsingular terminal sliding mode (FNTSM) manifold and a linear extended state observer (LESO). The developed control method applies an FNTSM to ensure the tracking performance’s control accuracy, and an LESO to estimate the system’s unmodeled dynamics and external disturbances. Additionally, an improved salp swarm algorithm (ISSA) is employed to parameter tune the suggested controller by integrating the salp swarm technique with a cloud model. This approach also uses a model-free scheme to reduce the complexity of controller design without relying on complex…
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Open Access
ARTICLE
Robot Zero-Moment Control Algorithm Based on Parameter Identification of Low-Speed Dynamic Balance
Saixuan Chen, Jie Yang, Guohua Cui, Fuzhou Niu, Baiqiang Yao, Yu Zhang
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2021-2039, 2023, DOI:10.32604/cmes.2022.022669
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract This paper proposes a zero-moment control torque compensation technique. After compensating the gravity and
friction of the robot, it must overcome a small inertial force to move in compliance with the external force. The
principle of torque balance was used to realise the zero-moment dragging and teaching function of the lightweight
collaborative robot. The robot parameter identification based on the least square method was used to accurately
identify the robot torque sensitivity and friction parameters. When the robot joint rotates at a low speed, it can
approximately satisfy the torque balance equation. The experiment uses the joint position and the…
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Open Access
ARTICLE
Retrieval and Regional Distribution Analysis of Ammonia, Sulfur Dioxide and Nitrogen Dioxide in the Urban Environment Using Ultraviolet DOAS Algorithm
Hao Chen, Jie Xu, Yibo Hu, Fuzhou Niu, Zhiyan Li, Dan Wang, Guizhong Fu, Chuanxin Li
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1251-1262, 2023, DOI:10.32604/cmes.2022.022279
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Aiming at the in situ and mobile observation of urban environmental air pollution, a portable instrument using ultraviolet spectrum retrieval algorithm was developed based on the basis of Differential Optical Absorption Spectroscopy (DOAS) and multiple-pass cell technique. Typical trace gas pollutants, NH
3, SO
2, and NO
2, were explored using their optical spectral characteristics in deep ultraviolet wavelength range from 210 to 215 nm. The gas concentration was retrieved by Lambert-Beer's law and nonlinear least square method. With an optimized optical alignment, the detection limits of NH
3, SO
2, NO
2 were estimated to be 2.2, 2.3, and 36.2 ppb, respectively. The system was…
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Open Access
ARTICLE
Research on Leak Location Method of Water Supply Pipeline Based on MVMD
Qiansheng Fang, Haojie Wang, Chenlei Xie, Jie Chen
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 1237-1250, 2023, DOI:10.32604/cmes.2022.021131
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract At present, the leakage rate of the water distribution network in China is still high, and the waste of water resources
caused by water distribution network leakage is quite serious every year. Therefore, the location of pipeline leakage
is of great significance for saving water resources and reducing economic losses. Acoustic emission technology is
the most widely used pipeline leak location technology. The traditional non-stationary random signal de-noising
method mainly relies on the estimation of noise parameters, ignoring periodic noise and components unrelated
to pipeline leakage. Aiming at the above problems, this paper proposes a leak location method for water…
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Open Access
ARTICLE
A Fixed-Point Iterative Method for Discrete Tomography Reconstruction Based on Intelligent Optimization
Luyao Yang, Hao Chen, Haocheng Yu, Jin Qiu, Shuxian Zhu
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 731-745, 2023, DOI:10.32604/cmes.2022.020656
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Discrete Tomography (DT) is a technology that uses image projection to reconstruct images. Its reconstruction
problem, especially the binary image (0–1 matrix) has attracted strong attention. In this study, a fixed point iterative
method of integer programming based on intelligent optimization is proposed to optimize the reconstructed model.
The solution process can be divided into two procedures. First, the DT problem is reformulated into a polyhedron
judgment problem based on lattice basis reduction. Second, the fixed-point iterative method of Dang and Ye is used
to judge whether an integer point exists in the polyhedron of the previous program. All the…
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Open Access
ARTICLE
Interpreting Randomly Wired Graph Models for Chinese NER
Jie Chen, Jiabao Xu, Xuefeng Xi, Zhiming Cui, Victor S. Sheng
CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.1, pp. 747-761, 2023, DOI:10.32604/cmes.2022.020771
（This article belongs to this Special Issue:
Advanced Intelligent Decision and Intelligent Control with Applications in Smart City)
Abstract Interpreting deep neural networks is of great importance to understand and verify deep models for natural language
processing (NLP) tasks. However, most existing approaches only focus on improving the performance of models
but ignore their interpretability. In this work, we propose a Randomly Wired Graph Neural Network (RWGNN)
by using graph to model the structure of Neural Network, which could solve two major problems (word-boundary
ambiguity and polysemy) of Chinese NER. Besides, we develop a pipeline to explain the RWGNN by using Saliency
Map and Adversarial Attacks. Experimental results demonstrate that our approach can identify meaningful and
reasonable interpretations for…
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