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ieee symposium Series on computational intelligence (SSCI)

作者： Rui Shan Qiang Xing Jinyan Zhang Jun Wang Yaniiana Wang Baodi Liu College of Oceanography and Space Informatics China University of Petroleum(East China) Qingdao China Well Logging Company of Sinopec Shengli Petroleum Engineering Co. LTD Dongying China College of Control Science and Engineering China University of Petroleum(East China)) Qingdao China

ISBN: (纸本)9781728190495

The lithology identification plays a fundamental role for the fine characterization and comprehensive evaluation of complex reservoirs. Several methods so far have been proposed for lithology identification such as the analysis of sensitive conventional logging curves, intersection diagrams as well as geostatistical analysis. Though these methods can lead to improving accuracy of lithology recognition, they are either indirectly reflect lithology information or affected by handwork factors, thus the efficiency and accuracy are limited. Recently, in the image processing area, Inception convolutional neural network has become a powerful tool for expressing complex structures and extracting multi-scale feature information due to its parallel structure of convolutional kernel. To this end, in this paper, we propose to apply the Inception network for lithology identification based on high-resolution well-logging imaging. Different from the conventional Inception network, the proposed model is able to automatically extract the typical feature regions of different lithology categories from the raw Formation MicroScanner Image (FMI) data by parameter transfer strategy, which could improve the generalization performance and enhance the accuracy of lithology identification. To alleviate the problem of differences in the distribution of features, the improved Inception model adopts regularized loss function constrained full connection layer to extract high-level features and obtain more available and valuable information. Experimental results show that the network model has the advantages of fewer parameters and less computational load, and the accuracy of lithology identification can reach 97.32%.

关键词： Training computational modeling Imaging Feature extraction Transformers Reservoirs Data mining

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An End-to-end Foreground Category Attention Boosting Network

An End-to-end Foreground Category Attention Boosting Network

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ieee International symposium on Information (IT) in Medicine and Education, ITME

作者： Guangwei Zhao Yu Zhang Li Sun Jinfeng Gao Fang Liu Renzhi Zhang College of Computer and Artificial Intelligence Huanghuai University Zhumadian China Henan Provincial Key Laboratory of Smart Lighting Zhumadian China Henan International Joint Laboratory of Behavior Optimization Control for Smart Robots Zhumadian China

In this paper, we introduce a foreground category attention boosting (CAB) framework for coarse-to-fine image segmentation, which makes full use of the coarse category information in low resolution layers. Our contributions can be summarized as: Firstly, we introduce the category attention mechanism to build the CAB module, which realizes a new stronger learner by aggregating the coarse category information and the feature maps of the current layer. Secondly, we propose an end-to-end foreground category attention boosting (FAB) neural network, which fully utilizes the complementary effects among different resolution feature maps and enhances the contribution from low resolution layers to fine segmentation with low computational cost. Thirdly, Extensive experiments on public dataset show that our approach can achieve superior performance over the state-of-the-art methods.

关键词： Image segmentation Image resolution Semantics Education Artificial neural networks Boosting computational efficiency

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Cooperative Routing for an Air-Ground Vehicle Team-Exact Algorithm, Transformation Method, and Heuristics

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ieee TRANSACTIONS ON automation SCIENCE AND ENGINEERING 2020年第1期17卷 537-547页

作者： Manyam, Satyanarayana G. Sundar, Kaarthik Casbeer, David W. Infoscitex Corp Dayton OH 45431 USA Ctr Nonlinear Studies Los Alamos NM 87544 USA US Air Force Res Lab Control Sci Ctr Excellence Wright Patterson AFB OH 45433 USA

This paper considers a cooperative vehicle routing problem for an intelligence, surveillance, and reconnaissance mission in the presence of communication constraints between the vehicles. The proposed framework uses a ground vehicle and an unmanned aerial vehicle (UAV) that travel cooperatively and visit a set of targets while satisfying the communication constraints. The problem is formulated as a mixed-integer linear program, and a branch-and-cut algorithm is developed to solve the problem to optimality. Furthermore, a transformation method and a heuristic are also developed for the problem. The effectiveness of all the algorithms is corroborated through extensive computational experiments on several randomly generated instances. Note to Practitioners-This paper is motivated by an intelligence, surveillance, and reconnaissance mission involving a single unmanned aerial vehicle (UAV) and a ground vehicle, where the vehicles must coordinate their activity in the presence of communication constraints. The combination of a small UAV and a ground vehicle is an ideal platform for such missions, since small UAVs can fly at low altitudes and can avoid obstacles or threats that would be problematic for the ground vehicle alone. This paper addresses the coordinated routing problem involving these two vehicles and presents an algorithm to obtain an optimal solution for this problem, fast heuristics to obtain good feasible solutions, and also a transformation method to transform any instance of this cooperative vehicle routing problem to an instance of the one-in-a-set traveling salesman problem.

关键词： Branch-and-cut communication constraints cooperative vehicle routing heuristics mixed-integer linear program path planning unmanned aerial vehicles (UAVs)

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Predictive control of processes with utilization of artificial intelligence elements 31

Predictive control of processes with utilization of artifici...

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31st International DAAAM Virtual symposium "Intelligent Manufacturing and automation"

作者： Blahova, Marta Mach, Vaclav Valouch, Jan

ISBN: (纸本)9783902734297

Predictive process control is a method of regulation suitable for controlling various types of systems, which is based on the idea of using the prediction of future system behavior and its optimization. Normally, a system model is used to predict behavior, and therefore it is necessary for the correct function of predictive control to make its correct selection and determine its parameters so that the controlled system is described as accurately as possible. Another advantage of predictive control is the possibility of including signal restrictions directly in the controller. The result is the application of some elements of artificial intelligence in suitable areas of predictive control, especially the use of simple evolutionary algorithms in optimization and neural networks as nonlinear models. One of the chapters of the article describes the possibilities of using these elements. It is proved that in addition to classical optimization algorithms, it is also possible to use simple evolutionary algorithms for optimization of prediction, while the computational complexity can be comparable depending on the type of solved problem and settings. The article describes a suitable selection of model systems with slow dynamics, their derivation, and the creation of nonlinear models in the form of scalable neural networks. The potential advantage of this approach for the control of systems that are difficult to describe or for the control of systems whose mathematical-physical description is not known. The chapter of the article also deals with the possibility of using the found models on real systems and determining the necessary conditions and requirements for their application. © 2020 Danube Adria Association for automation and Manufacturing, DAAAM. All rights reserved.

关键词： Evolutionary algorithms

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A Simple Fixed Point Iteration-Based Digital Noise Filter for control Applications 19

A Simple Fixed Point Iteration-Based Digital Noise Filter fo...

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ieee Joint 19th International symposium on computational intelligence and Informatics / 7th International Conference on Recent Achievements in Mechatronics, automation, Computer Sciences and Robotics

作者： Varga, Arpad Eigner, Gyorgy Tar, Jozsef K. Obuda Univ Doct Sch Appl Inf & Appl Math Budapest Hungary Obuda Univ Physiol Controls Res Ctr Budapest Hungary Obuda Univ ABC Ctr Intelligent Robot Budapest Hungary

ISBN: (纸本)9781728156255

In various control applications as robotics, chemistry, life sciences, etc., the controllers need feedback terms that contain various integer or fractional order time-derivatives of the variables that describe the physical state of the controlled system as well as certain properties of the "nominal trajectory" that has to be precisely tracked. Normally these derivatives cannot be directly measured by dedicated sensors, so they numerically must be estimated by other, normally noise-burdened sensor signals. The higher the relative order of the control task is the higher the control method's sensitivity to the sensor noises is. To improve the situation the sensor signals and especially the time-derivatives calculated by the use of the sensor signals have to be "filtered" to reduce the undesirable consequence of the measurement noises. Filtering normally happens by somehow "averaging" a few past signals therefore it inevitably introduces "delay"-like effect that can degrade the controller's operation. Physically the act of filtering can be interpreted as the insertion of a dynamically coupled physical subsystem into the controlled engine + controller system. Electronic and electrical engineers developed various filters made of constant and passive elements as resistors, inductors, capacitors that can be described by differential equations. For these linear, time-invariant systems the use of the frequency domain became prevailing. In the case of digital controllers more primitive, fictitious models can be applied without physical realization. These subsystems can be even strongly nonlinear. In this paper a primitive noise-filtering technique for digital controllers is suggested. It has two simple, tunable parameters. Its operation is illustrated in the Fixed Point Iteration-based adaptive control of a propeller-driven pendulum.

关键词： Fixed Point Iteration-based Adaptive control Noise Filtering Propeller-driven Pendulum

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A Parallel Medical Diagnostic and Treatment System for Chronic Diseases

A Parallel Medical Diagnostic and Treatment System for Chron...

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Chinese automation Congress (CAC)

作者： Wang, Jing Wang, Xiao Guo, Yuanyuan Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Qingdao Acad Intelligent Ind Qingdao Peoples R China Qingdao Acad Intelligent Ind Inst Smart Healthcare Syst Qingdao Peoples R China

ISBN: (纸本)9781728176871

In order to improve the accuracy of diagnosis and the effectiveness of treatment on chronic diseases, a parallel medical diagnostic and treatment system for chronic diseases is proposed in this paper. The system consists of the artificial system, computational experiments and parallel execution. Generally, the actual medical system includes real doctors, real patients, and the process of real doctors diagnosing and creating a treatment plan. Based on the components in actual medical system, the virtual doctors and virtual patients are created in artificial system. The computational experiments are to exhaustively explore and evaluate reasonable diagnoses and treatment options, so that the most accurate diagnosis and the best treatment plan are configured. The parallel execution between the artificial and the actual system includes the interaction between virtual doctors and real doctors as well as that between the virtual patients and actual patients. The parallel execution, on the doctors' end, is to ensure the precise diagnosis of diseases and the effectiveness of the treatment plan. On the other hand, the parallel execution, on the patients' end, is to provide patients with more personal guidance on following the treatment and to assist sending feedback to the system regarding the treatment effectiveness. As the chronic diseases generally require a long-term treatment, this parallel system can better accommodate the process by continuously monitoring the treatment and sending feedback to the model so as to actively optimize the treatment plan.

关键词： parallel intelligence smart health intelligent diagnosis and treatment chronic diseases

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Parallel Vision and Learning for Intelligent Perception in Smart Driving

Parallel Vision and Learning for Intelligent Perception in S...

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Digital Twins and Parallel intelligence (DTPI), ieee International Conference on

作者： Hui Zhang Yidong Li Xuan Li Fei-Yue Wang Beijing Jiaotong University Beijing China Peng Cheng Laboratory Shenzhen China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Modern vision models are built upon large-scale diversified dataset, which is labor-intensive and cost-ineffective to collect and label. They are usually effective under simple constrained conditions, while the performance gets worse under actual traffic scenes. To address aforementioned problems, we propose a visual analysis framework based on parallel vision and learning for intelligent perception in smart driving. Specifically, our framework first generate and select data exploiting artificial image system. Then, computational experiments are conducted with predictive learning for model design, learning, and evaluation. Our framework is powered with virtual-actual interactive ability through parallel execution, integrating information from different scenes. The difficulty of the visual model in the actual scene can be applied to guide the model training in the artificial scene. We also carried out a case study to preliminarily demonstrate the effectiveness of the proposed framework.

关键词： Training Learning systems Visualization computational modeling Digital twin Conferences Learning (artificial intelligence)

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Network-Design of Virtual Drum Boiler Feedwater control System 7

Network-Design of Virtual Drum Boiler Feedwater Control Syst...

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7th International Conference on Information, Cybernetics, and computational Social Systems, ICCSS 2020

作者： Feng, Xingle Hu, Wenshan Zhou, Hong Guan, Shiqi Xue, Liwei Wuhan University Department of Artificial Intelligence and Automation Wuhan China

ISBN: (纸本)9781728162461

To solve the difficult problem of the thermal process experiment in education and training, this paper develops a drum boiler feedwater control system based on the Networked control System Laboratory (NCSLab). The task of automatic control of the feed water of the drum boiler is to adapt the water supply of the boiler to the evaporation capacity of the boiler to maintain the water level of the drum within the specified range while maintaining a stable feedwater flow. For both supercritical and ultra-supercritical units, the boiler is The once-through boiler has no steam drum, but there will be a steam-water separator, which is equivalent to a drum. NCSLab is a Web-based platform for remote control of physical devices and virtual devices. At present, the remote virtual drum feedwater control experiment on NCSLab provides a feasible online solution for the thermal process control experiment and also provides technical support for the more complex thermal process control system in the future. © 2020 ieee.

关键词： Networked control systems

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Parking Lot Exploration Strategy 19

Parking Lot Exploration Strategy

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ieee Joint 19th International symposium on computational intelligence and Informatics / 7th International Conference on Recent Achievements in Mechatronics, automation, Computer Sciences and Robotics

作者： Adam, Anna Barbara Kocsany, Laszlo Szadeczky-Kardoss, Emese Gincsaine Tihanyi, Viktor Budapest Univ Technol & Econ Dept Control Engn & Informat Technol Budapest Hungary Budapest Univ Technol & Econ Dept Automot Technol Budapest Hungary Budapest Univ Technol & Econ Budapest Hungary

ISBN: (纸本)9781728156255

This paper presents methods of parking lot exploration with an autonomous vehicle. Parking lot exploration is a subsystem of an autonomous parking system which performs the exploration of the parking lot, the parking space detection and the parking maneuver itself. The first task is to go around the parking lot until a free parking space is found. In this paper, the parking lot exploration is presented in details and the basics of parking space detection with the help of a LiDAR (Light Detection and Ranging) sensor are given. Firstly, the trapezoidal cell decomposition based method is detailed. This method consists of cell decomposition with traditional image processing, creating the adjacency matrix that describes the adjacency graph and finally determining graph traversal from the adjacency graph. After that, Voronoi diagram based method is also presented and the two methods are compared in several aspects. Finally, the second subsystem of the autonomous parking system is discussed, where a parking space detection method is also presented.

关键词： trapezoidal cell decomposition intelligent vehicle Voronoi diagram LiDAR autonomous parking path planning

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computational design of energy-efficient legged robots: Optimizing for size and actuators

Computational design of energy-efficient legged robots: Opti...

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ieee International Conference on Robotics and automation (ICRA)

作者： G. Fadini T. Flayols A. Del Prete N. Mansard P. Souères LAAS-CNRS Université de Toulouse CNRS Toulouse France University of Trento Artifical and Natural Intelligence Toulouse Insitute (ANITI)

This paper presents a computational framework for the design of high-performance legged robotic systems. The framework relies on the concurrent optimization of hardware parameters and control trajectories to find the best robot design for a given task. In particular, we focus on energy efficiency, presenting novel electro-mechanical models to account for the losses of the actuators due to friction and Joule effects. Thanks to a bi-level optimization scheme, featuring a genetic algorithm in the outer loop, our framework can also optimize for the duration of the motion, the actuators, and the size of the robot. We present a novel approach to scale both the actuators and the robot structure in a way that ensures structural integrity by maintaining constant the normalized deflection of the links. We validated our approach by designing a two-joint monoped robot to execute a jumping task. Our simulation results show that our framework can lead to remarkable energy savings (up to 60%) thanks to the concurrent optimization of robot size, motion duration, and actuators.

关键词： Legged locomotion Actuators Simulation Energy efficiency Hardware Trajectory Task analysis

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