Data-driven evolutionary optimization has witnessed great success in solving complex real-world optimization problems. However, existing data-driven optimization algorithms require that all data are centrally stored, ...
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This paper investigates the effective computational resource allocation for large-scale fully-separable problems under the framework of a cooperative co-evolutionary algorithm called MLSoft. According to different sub...
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ISBN:
(数字)9781728185262
ISBN:
(纸本)9781728185279
This paper investigates the effective computational resource allocation for large-scale fully-separable problems under the framework of a cooperative co-evolutionary algorithm called MLSoft. According to different subgroup sizes of the problems, we allocate different numbers of iterations to the subproblems in all the cycles. For high-dimensional subproblems, more iterations are needed during the optimization process; while for low-dimensional subproblems, fewer iterations will be assigned. The experimental results reveal that the proposed resource allocation scheme is simple but effective, which can enhance the performance of MLSoft in solving large-scale fully-separable problems. In addition, we conduct a group of experiments to evaluate the results if a higher weight is assigned to more recent performance in MLSoft. The results show that introducing weight to the latest reward affects very little on the performance of MLSoft.
In order to solve the problems of poor real-time performance and single display method in traditional unmanned aerial vehicle(UAV) orthographic image mosaic, this paper proposes a real-time updating technology of loca...
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In order to solve the problems of poor real-time performance and single display method in traditional unmanned aerial vehicle(UAV) orthographic image mosaic, this paper proposes a real-time updating technology of local area orthoimages based on 3D digital earth, which can be widely used in the fields of emergency rescue, environmental monitoring and military *** technology is that in the process of UAV aerial photography, the server receives sequence aerial image in real time and synchronously completes orthographic image splicing, then automatically cuts them into regular image tiles and transmits the regular image tiles to the display terminal in an incremental manner. The display terminal software constructs a 3D digital earth based on quadtree LOD algorithm, and updates the terrain texture of the target range with the received high-definition orthographic image tiles, so as to realize real-time coverage monitoring of key areas. In this paper, the above work is verified by real aerial images, and the results prove the feasibility and effectiveness of the work.
Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety...
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Smart manufacturing is critical in improving the quality of the process industry. In smart manufacturing, there is a trend to incorporate different kinds of new-generation information technologies into process- safety analysis. At present, green manufacturing is facing major obstacles related to safety management, due to the usage of large amounts of hazardous chemicals, resulting in spatial inhomogeneity of chemical industrial processes and increasingly stringent safety and environmental regulations. Emerging informa- tion technologies such as arti cial intelligence (AI) are quite promising as a means of overcoming these dif culties. Based on state-of-the-art AI methods and the complex safety relations in the process industry, we identify and discuss several technical challenges associated with process safety: ① knowledge acquisition with scarce labels for process safety;② knowledge-based reasoning for process safety;③ accurate fusion of heterogeneous data from various sources;and ④ effective learning for dynamic risk assessment and aided decision-making. Current and future works are also discussed in this context.
In this paper, we investigate the state estimation problem over multiple Markovian packet drop channels. In this problem setup, a remote estimator receives measurement data transmitted from multiple sensors over indiv...
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The ethylene cracking furnace system convert a variety of hydrocarbon feeds into products such as ethylene and propylene in parallel. During the cracking process, the coke produced by the cracking will degrade the per...
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ISBN:
(数字)9781728158556
ISBN:
(纸本)9781728158563
The ethylene cracking furnace system convert a variety of hydrocarbon feeds into products such as ethylene and propylene in parallel. During the cracking process, the coke produced by the cracking will degrade the performance of the cracking furnace, so the furnace should be cleaned periodically. Scheduling of the cracking furnace system involves various raw materials, multiple furnaces, and multiple constraints, so it is a difficult mathematic programming problem. Previous studies have simplified the optimization model to obtain a corresponding mixed integer nonlinear programming (MINLP) model. In order to make the scheduling more suitable for the actual process, this paper develops the transfer-line exchanger (TLE) model, fuel consumption model, and super-high pressure steam (SS) model by using the actual plant data. A case study is put forward to demonstrate the effectiveness of the proposed method.
This paper is concerned with the sampled-data stabilization problem for a class of linear systems. Different from the input-delay approach that has been widely used in analyzing the stabilization problem of sampled-da...
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ISBN:
(纸本)9781665436601
This paper is concerned with the sampled-data stabilization problem for a class of linear systems. Different from the input-delay approach that has been widely used in analyzing the stabilization problem of sampled-data systems, an extended form of the celebrated Halanay inequality is developed for sampled-data systems so as to study the stabilization problem of linear systems under aperiodic sampled-data control. Based on the extended Halanay inequality, the stabilization problem is solved for linear sampled-data systems, where it is required that the gain should be strictly less than the decay rate and then the upper bound of the sampling intervals can be estimated. In order to enlarge the upper bound of the sampling intervals, a further extension of the developed Halanay inequality is made. Then some new conditions are derived to ensure the exponential stability of linear sampleddata systems, where the upper bound of the sampling intervals is allowed to violate the condition of the Halanay inequality. Subsequently, the obtained results are applied to deal with the consensus problem of linear multi-agent systems.
The steam system is an important part of the utility systems in process industry. The energy consumption and operation cost of the existing plant were increased due to the inefficient configuration of the steam system...
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Industrial gas leakage in chemical plants presents a high risk to health and safety, also makes a huge waste of production materials. In this paper, we propose an automatic gas segmentation method for optical gas imag...
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ISBN:
(数字)9781728176871
ISBN:
(纸本)9781728176888
Industrial gas leakage in chemical plants presents a high risk to health and safety, also makes a huge waste of production materials. In this paper, we propose an automatic gas segmentation method for optical gas imaging (OGI) videos, which can not only indicate the existence of leakage in frames but also show the precise locations and shapes of gas plumes. Specifically, we propose a novel video segmentation network that stacks 2D spatial convolutions, 1D temporal convolutions and 3D spatial-temporal convolutions together within an encoder-decoder structure, termed 2.5D-Unet. Stacking mixed convolutions increases the representation ability of network for leakage's appearance and motion. More importantly, stacking mixed convolutions facilitates pre-training of model using still images of smoke, which is especially useful when lacking of labeled videos of leaked gas. Experimental results show, for OGI video-based gas leakage segmentation, our method outperforms existing video segmentation methods.
In this paper, a novel real-time online UAV image mosaic algorithm is proposed to meet the real-time, robustness and accuracy requirements of practical application. First, the algorithm adopts GPS and track planning i...
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In this paper, a novel real-time online UAV image mosaic algorithm is proposed to meet the real-time, robustness and accuracy requirements of practical application. First, the algorithm adopts GPS and track planning information to locate the adjacent images. Instead of the 8-DOF(degrees of freedom) homography transformation, the 4-DOF similarity transformation is estimated to more robustly register the UAV images and reduce their perspective errors. Second, a new method of local registration is developed to reduce the cumulative errors and calculation costs. Meanwhile, the real-time mosaic process is used to register images and update the panoramic image. Finally, the effectiveness of the proposed approach is evaluated by a group of experiments on 4 K images taken by quadrotor drones. According to the comparison of experiments, the proposed algorithm is robust to cumulative errors and obtains high-quality panorama. Additionally, through the analysis on stitching time and practical application, frame-by-frame mosaic synthesis is online updated in real-time.
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