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Operational Requirements Analysis Method Based on Question Answering of WEKG 基于 WEKG 问题解答的运行需求分析方法
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-14 DOI: 10.23919/jsee.2024.000004
Zhiwei Zhang, Yajie Dou, Xiangqian Xu, Yufeng Ma, Jiang Jiang, Yuejin Tan
The weapon and equipment operational requirement analysis (WEORA) is a necessary condition to win a future war, among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering (QA) of weapons and equipment knowledge graph (WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.
武器装备作战需求分析(WEORA)是打赢未来战争的必要条件,其中武器装备知识的获取是一项巨大挑战。主要挑战在于现有武器装备数据无法进行结构化知识表示,基于自然语言的知识导航无法有效支持 WEORA。为解决上述问题,本研究提出了一种基于武器装备知识图谱(WEKG)问题解答(QA)的方法来构建和导航 WEORA 中的武器装备相关知识。该方法首先构建了武器装备知识图谱(WEKG),然后通过语义解析在WEKG上构建了一个基于中立网络的问答系统,用于知识导航。最后,对该方法进行了评估,并为 WEORA 开发了一个基于 QA 系统的聊天机器人。我们提出的方法在搜索目标知识的准确性和效率方面都有很好的表现,可以很好地辅助 WEORA。
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引用次数: 0
Belief Reliability: A Scientific Exploration of Reliability Engineering 信念可靠性可靠性工程的科学探索
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-14 DOI: 10.23919/jsee.2024.000029
Qingyuan Zhang, Xiaoyang Li, Tianpei Zu, Rui Kang
This paper systematically introduces and reviews a scientific exploration of reliability called the belief reliability. Beginning with the origin of reliability engineering, the problems of present theories for reliability engineering are summarized as a query, a dilemma, and a puzzle. Then, through philosophical reflection, we introduce the theoretical solutions given by belief reliability theory, including scientific principles, basic equations, reliability science experiments, and mathematical measures. The basic methods and technologies of belief reliability, namely, belief reliability analysis, function-oriented belief reliability design, belief reliability evaluation, and several newly developed methods and technologies are sequentially elaborated and overviewed. Based on the above investigations, we summarize the significance of belief reliability theory and make some prospects about future research, aiming to promote the development of reliability science and engineering.
本文系统地介绍和回顾了对可靠性的科学探索,即 "信念可靠性"。从可靠性工程的起源开始,将目前可靠性工程理论存在的问题归纳为一个疑问、一个困境和一个难题。然后,通过哲学思考,介绍了信念可靠性理论给出的理论解决方案,包括科学原理、基本方程、可靠性科学实验和数学计量。然后,依次阐述和综述了信念可靠性的基本方法和技术,即信念可靠性分析、面向功能的信念可靠性设计、信念可靠性评价以及几种新发展的方法和技术。在上述研究的基础上,我们总结了信念可靠性理论的意义,并对未来的研究作了一些展望,旨在促进可靠性科学与工程的发展。
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引用次数: 0
A Self-Organization Formation Configuration Based Assignment Probability and Collision Detection 基于分配概率和碰撞检测的自组织编队配置
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2024.000016
Wei Song, Tong Wang, Guangxin Yang, Peng Zhang
The formation control of multiple unmanned aerial vehicles (multi-UAVs) has always been a research hotspot. Based on the straight line trajectory, a multi-UAVs target point assignment algorithm based on the assignment probability is proposed to achieve the shortest overall formation path of multi-UAVs with low complexity and reduce the energy consumption. In order to avoid the collision between UAVs in the formation process, the concept of safety ball is introduced, and the collision detection based on continuous motion of two time slots and the lane occupation detection after motion is proposed to avoid collision between UAVs. Based on the idea of game theory, a method of UAV motion form setting based on the maximization of interests is proposed, including the maximization of self-interest and the maximization of formation interest is proposed, so that multi-UAVs can complete the formation task quickly and reasonably with the linear trajectory assigned in advance. Finally, through simulation verification, the multi-UAVs target assignment algorithm based on the assignment probability proposed in this paper can effectively reduce the total path length, and the UAV motion selection method based on the maximization interests can effectively complete the task formation.
多无人机编队控制一直是研究热点。在直线轨迹的基础上,提出了一种基于分配概率的多无人机目标点分配算法,以较低的复杂度实现多无人机整体编队路径最短,并降低能耗。为了避免无人机在编队过程中发生碰撞,引入了安全球的概念,提出了基于两个时隙连续运动的碰撞检测和运动后的占道检测来避免无人机之间的碰撞。基于博弈论思想,提出了基于利益最大化的无人机运动形态设定方法,包括自身利益最大化和编队利益最大化,使多架无人机在事先分配好的线性轨迹下快速合理地完成编队任务。最后,通过仿真验证,本文提出的基于分配概率的多无人机目标分配算法能有效减少总路径长度,基于利益最大化的无人机运动选择方法能有效完成任务编队。
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引用次数: 0
Design and Pricing of Maintenance Service Contract Based on Nash Non-Cooperative Game Approach 基于纳什非合作博弈法的维护服务合同设计与定价
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2024.000010
Chun Su, Kui Huang
Nowadays manufacturers are facing fierce challenge. Apart from the products, providing customers with multiple maintenance options in the service contract becomes more popular, since it can help to improve customer satisfaction, and ultimately promote sales and maximize profit for the manufacturer. By considering the combinations of corrective maintenance and preventive maintenance, totally three types of maintenance service contracts are designed. Moreover, attractive incentive and penalty mechanisms are adopted in the contracts. On this basis, Nash non-cooperative game is applied to analyze the revenue for both the manufacturer and customers, and so as to optimize the pricing mechanism of maintenance service contract and achieve a win-win situation. Numerical experiments are conducted. The results show that by taking into account the incentive and penalty mechanisms, the revenue can be improved for both the customers and manufacturer. Moreover, with the increase of repair rate and improvement factor in the preventive maintenance, the revenue will increase gradually for both the parties.
如今,制造商面临着激烈的挑战。除了产品之外,在服务合同中为客户提供多种维护选项也越来越受欢迎,因为这有助于提高客户满意度,最终促进销售,为制造商带来最大利润。考虑到纠正性维护和预防性维护的组合,我们设计了三种类型的维护服务合同。此外,合同中还采用了具有吸引力的激励和惩罚机制。在此基础上,运用纳什非合作博弈分析制造商和客户的收益,从而优化维修服务合同的定价机制,实现双赢。本文进行了数值实验。结果表明,考虑到激励和惩罚机制,客户和制造商的收益都能得到提高。此外,随着维修率和预防性维护改进系数的提高,双方的收益也会逐渐增加。
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引用次数: 0
Overview of Radar Detection Methods for Low Altitude Targets in Marine Environments 海洋环境中低空目标雷达探测方法概述
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2024.000026
Yong Yang, Boyu Yang
In this paper, a comprehensive overview of radar detection methods for low-altitude targets in maritime environments is presented, focusing on the challenges posed by sea clutter and multipath scattering. The performance of the radar detection methods under sea clutter, multipath, and combined conditions is categorized and summarized, and future research directions are outlined to enhance radar detection performance for low-altitude targets in maritime environments.
本文全面概述了海洋环境中低空目标的雷达探测方法,重点关注海杂波和多径散射带来的挑战。本文对雷达探测方法在海杂波、多径散射和综合条件下的性能进行了分类和总结,并概述了未来的研究方向,以提高海上环境中低空目标的雷达探测性能。
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引用次数: 0
Requirements Ranking Based on Crowd-Sourcing High-End Product USs 基于众包高端产品 US 的需求排序
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2023.000164
Yufeng Ma, Yajie Dou, Xiangqian Xu, Qingyang Jia, Yuejin Tan
Based on the characteristics of high-end products, crowd-sourcing user stories can be seen as an effective means of gathering requirements, involving a large user base and generating a substantial amount of unstructured feedback. The key challenge lies in transforming abstract user needs into specific ones, requiring integration and analysis. Therefore, we propose a topic mining-based approach to categorize, summarize, and rank product requirements from user stories. Specifically, after determining the number of story categories based on pyLDAvis, we initially classify “I want to” phrases within user stories. Subsequently, classic topic models are applied to each category to generate their names, defining each post-classification user story category as a requirement. Furthermore, a weighted ranking function is devised to calculate the importance of each requirement. Finally, we validate the effectiveness and feasibility of the proposed method using 2 966 crowd-sourced user stories related to smart home systems.
根据高端产品的特点,众包用户故事可以被视为收集需求的一种有效手段,它可以让大量用户参与进来,并产生大量非结构化反馈。关键的挑战在于如何将抽象的用户需求转化为具体的需求,这需要整合和分析。因此,我们提出了一种基于主题挖掘的方法,对用户故事中的产品需求进行分类、总结和排序。具体来说,在基于 pyLDAvis 确定故事类别的数量后,我们首先对用户故事中的 "我要 "短语进行分类。随后,对每个类别应用经典的主题模型来生成其名称,并将每个分类后的用户故事类别定义为需求。此外,我们还设计了一个加权排名函数来计算每个需求的重要性。最后,我们使用 2 966 个与智能家居系统相关的众包用户故事验证了所提方法的有效性和可行性。
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引用次数: 0
DCEL: Classifier Fusion Model for Android Malware Detection DCEL:用于安卓恶意软件检测的分类器融合模型
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2024.000018
Xiaolong Xu, Shuai Jiang, Jinbo Zhao, Xinheng Wang
The rapid growth of mobile applications, the popularity of the Android system and its openness have attracted many hackers and even criminals, who are creating lots of Android malware. However, the current methods of Android malware detection need a lot of time in the feature engineering phase. Furthermore, these models have the defects of low detection rate, high complexity, and poor practicability, etc. We analyze the Android malware samples, and the distribution of malware and benign software in application programming interface (API) calls, permissions, and other attributes. We classify the software's threat levels based on the correlation of features. Then, we propose deep neural networks and convolutional neural networks with ensemble learning (DCEL), a new classifier fusion model for Android malware detection. First, DCEL preprocesses the malware data to remove redundant data, and converts the one-dimensional data into a two-dimensional gray image. Then, the ensemble learning approach is used to combine the deep neural network with the convolutional neural network, and the final classification results are obtained by voting on the prediction of each single classifier. Experiments based on the Drebin and Malgenome datasets show that compared with current state-of-art models, the proposed DCEL has a higher detection rate, higher recall rate, and lower computational cost.
移动应用程序的快速增长、安卓系统的普及及其开放性吸引了许多黑客甚至犯罪分子,他们正在制造大量的安卓恶意软件。然而,目前的安卓恶意软件检测方法在特征工程阶段需要花费大量时间。此外,这些模型还存在检测率低、复杂度高、实用性差等缺陷。我们分析了安卓恶意软件样本,以及恶意软件和良性软件在应用程序编程接口(API)调用、权限和其他属性方面的分布。我们根据特征的相关性对软件的威胁等级进行分类。然后,我们提出了深度神经网络和卷积神经网络与集合学习(DCEL)--一种用于安卓恶意软件检测的新型分类器融合模型。首先,DCEL 对恶意软件数据进行预处理以去除冗余数据,并将一维数据转换为二维灰度图像。然后,利用集合学习方法将深度神经网络与卷积神经网络结合起来,通过对每个单一分类器的预测结果进行投票来获得最终分类结果。基于 Drebin 和 Malgenome 数据集的实验表明,与目前最先进的模型相比,所提出的 DCEL 具有更高的检测率、更高的召回率和更低的计算成本。
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引用次数: 0
An Extended State Observer with Adjustable Bandwidth for Measurement Noise 带宽可调的测量噪声扩展状态观测器
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2023.000166
Shihua Zhang, Xiaohui Qi, Sen Yang
In this paper, a bandwidth-adjustable extended state observer (ABESO) is proposed for the systems with measurement noise. It is known that increasing the bandwidth of the observer improves the tracking speed but tolerates noise, which conflicts with observation accuracy. Therefore, we introduce a bandwidth scaling factor such that ABESO is formulated to a 2-degree-of-freedom system. The observer gain is determined and the bandwidth scaling factor adjusts the bandwidth according to the tracking error. When the tracking error decreases, the bandwidth decreases to suppress the noise, otherwise the bandwidth does not change. It is proven that the error dynamics are bounded and converge in finite time. The relationship between the upper bound of the estimation error and the scaling factor is given. When the scaling factor is less than 1, the ABESO has higher estimation accuracy than the linear extended state observer (LESO). Simulations of an uncertain nonlinear system with compound disturbances show that the proposed ABESO can successfully estimate the total disturbance in noisy environments. The mean error of total disturbance of ABESO is 15.28% lower than that of LESO.
本文针对存在测量噪声的系统提出了带宽可调扩展状态观测器(ABESO)。众所周知,增加观测器的带宽可以提高跟踪速度,但对噪声的容忍度却与观测精度相冲突。因此,我们引入了一个带宽缩放因子,使 ABESO 适用于 2 自由度系统。观测器增益确定后,带宽缩放因子会根据跟踪误差调整带宽。当跟踪误差减小时,带宽减小以抑制噪声,否则带宽不变。实验证明,误差动态是有界的,并在有限时间内收敛。给出了估计误差上限与缩放因子之间的关系。当缩放因子小于 1 时,ABESO 比线性扩展状态观测器(LESO)具有更高的估计精度。对带有复合扰动的不确定非线性系统的仿真表明,所提出的 ABESO 能在噪声环境中成功估计总扰动。ABESO 的总扰动平均误差比 LESO 低 15.28%。
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引用次数: 0
Robust Design of Sliding Mode Control for Airship Trajectory Tracking with Uncertainty and Disturbance Estimation 具有不确定性和扰动估计的飞艇轨迹跟踪滑模控制鲁棒设计
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2024.000017
Muhammad Wasim, Ahsan Ali, Mohammad Ahmad Choudhry, Inam Ul Hasan Shaikh, Faisal Saleem
The robotic airship can provide a promising aerostatic platform for many potential applications. These applications require a precise autonomous trajectory tracking control for airship. Airship has a nonlinear and uncertain dynamics. It is prone to wind disturbances that offer a challenge for a trajectory tracking control design. This paper addresses the airship trajectory tracking problem having time varying reference path. A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters. It uses extended Kalman filter (EKF) for uncertainty and disturbance estimation. The estimated parameters are used by sliding mode controller (SMC) for ultimate control of airship trajectory tracking. This comprehensive algorithm, EKF based SMC (ESMC), is used as a robust solution to track airship trajectory. The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies. The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis. The simulation results show that the proposed method efficiently tracks the desired trajectory. The method solves the stability, convergence, and chattering problem of SMC under model uncertainties and wind disturbances.
机器人飞艇可以为许多潜在应用提供一个前景广阔的航空静态平台。这些应用需要对飞艇进行精确的自主轨迹跟踪控制。飞艇具有非线性和不确定的动力学特性。它容易受到风的干扰,这给轨迹跟踪控制设计带来了挑战。本文探讨了具有时变参考路径的飞艇轨迹跟踪问题。针对分布式参数,本文选择了一种在模型不确定性和风干扰下的集合参数估计方法。它使用扩展卡尔曼滤波器(EKF)进行不确定性和干扰估计。滑动模态控制器(SMC)利用估算的参数对飞艇轨迹跟踪进行最终控制。基于 EKF 的 SMC(ESMC)这一综合算法被用作跟踪飞艇轨迹的稳健解决方案。所提出的估算器可估算风扰动以及质量矩阵变化和空气动力学模型误差导致的模型不确定性。利用 Lyapunov 稳定性分析研究了所提方法的稳定性和收敛性。仿真结果表明,提出的方法能有效地跟踪所需的轨迹。该方法解决了 SMC 在模型不确定性和风扰动下的稳定性、收敛性和颤振问题。
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引用次数: 0
Method for Triangular Fuzzy Multiple Attribute Decision Making Based on Two-Dimensional Density Operator Method 基于二维密度算子法的三角模糊多属性决策方法
IF 2.1 3区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Pub Date : 2024-03-12 DOI: 10.23919/jsee.2024.000019
Youliang Lin, Wu Li, Gang Liu, Dong Huang
Aiming at the triangular fuzzy (TF) multi-attribute decision making (MADM) problem with a preference for the distribution density of attribute (DDA), a decision making method with TF number two-dimensional density (TFTD) operator is proposed based on the density operator theory for the decision maker (DM). Firstly, a simple TF vector clustering method is proposed, which considers the feature of TF number and the geometric distance of vectors. Secondly, the least deviation sum of squares method is used in the program model to obtain the density weight vector. Then, two TFTD operators are defined, and the MADM method based on the TFTD operator is proposed. Finally, a numerical example is given to illustrate the superiority of this method, which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.
针对偏好属性分布密度(DDA)的三角模糊(TF)多属性决策(MADM)问题,基于密度算子理论,为决策者(DM)提出了一种带有 TF 数二维密度(TFTD)算子的决策方法。首先,提出了一种简单的 TF 向量聚类方法,该方法考虑了 TF 数的特征和向量的几何距离。其次,在程序模型中使用最小偏差平方和法获得密度权重向量。然后,定义了两个 TFTD 算子,并提出了基于 TFTD 算子的 MADM 方法。最后,举例说明了该方法的优越性,该方法不仅能优先解决 DDA 的 TF MADM 问题,还能帮助 DM 进行综合比较。
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引用次数: 0
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Journal of Systems Engineering and Electronics
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