IEEE Systems, Man, and Cybernetics Magazine最新文献

GRATP Model Based on Comprehensive Training Cost: Solving Collaboration Problems in Real-World Scenarios 基于综合培训成本的 GRATP 模型：解决现实世界场景中的协作问题

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2023.3236491

Xiangjun Liu, Shiyu Wu, Ruisi Yang, Libo Zhang

{"title":"GRATP Model Based on Comprehensive Training Cost: Solving Collaboration Problems in Real-World Scenarios","authors":"Xiangjun Liu, Shiyu Wu, Ruisi Yang, Libo Zhang","doi":"10.1109/MSMC.2023.3236491","DOIUrl":"https://doi.org/10.1109/MSMC.2023.3236491","url":null,"abstract":"As an extension of group role assignment (GRA), GRA with a training plan (GRATP) is proposed to find the optimal assignment and training plan by maximizing the total benefit. The training plan indicates the training program of each agent, thereby enhancing its corresponding role-playing abilities and further affecting the role assignment. However, only the downtime loss is considered in the existing GRATP models, while the cost of training program is ignored. Moreover, the capability improvement brought about by training is related to the agent’s familiarity with the role, which is also neglected by the existing GRATP models. Therefore, we formulate the training-related role assignment problem while taking into account the comprehensive training cost, which is composed of the downtime loss and the cost of training program. In the formalized problem, different training programs are attached with different costs. Specifically, the cost of a training program is related to the weight and the team’s performance in the corresponding role. In addition, the capability improvement function is set to be positively correlated with the agent’s familiarity with the role. Furthermore, the agent will not be trained if its initial ability value exceeds a certain threshold, which is in line with actual scenarios. The effectiveness of the proposed model is verified by experiments.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"42 5","pages":"14-21"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141713101","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Proportional Fuzzy Elimination and Choice Translating Reality II Method for Multicriteria Decision-Making Problems: A Robust New Methodology for Practical Applications 多标准决策问题的比例模糊消除和选择转换现实 II 方法：适用于实际应用的稳健新方法

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2023.3241426

Jing Guo, Xianjun Zhu, Kun You, Zhenzhen Wang, Qianqian Wang, Hui Li, Xianzhong Zhou

{"title":"A Proportional Fuzzy Elimination and Choice Translating Reality II Method for Multicriteria Decision-Making Problems: A Robust New Methodology for Practical Applications","authors":"Jing Guo, Xianjun Zhu, Kun You, Zhenzhen Wang, Qianqian Wang, Hui Li, Xianzhong Zhou","doi":"10.1109/MSMC.2023.3241426","DOIUrl":"https://doi.org/10.1109/MSMC.2023.3241426","url":null,"abstract":"As a result of the complexity of practical problems and the limitations of knowledge, it is often tricky for decision-makers (DMs) to give accurate information. How to accurately and effectively convey the evaluation information of DMs affects multicriteria decision-making (MCDM). Therefore, linguistically hesitant fuzzy sets can express people’s evaluations with greater flexibility and resemblance to human thought than exact numbers, particularly during highly complex decision-making processes. This article proposes the proportional interval term set (PITS) inspired by hesitant fuzzy sets to indicate more significant uncertainty. To more effectively compare two PITSs, the number of elements in each set must be identical. So the standardization of the PITS is presented for this purpose. The standardization improves the distance and possibility degree of two PITSs. Moreover, considering the more vital capability of the symmetrical interval term set to handle uncertain information, an integrated elimination and choice translating reality (ELECTRE) II method for addressing MCDM issues is proposed. The first phase aggregates the PITS opinions of experts on each alternative and criterion and determines the weights of the criteria with the aid of distance theory. Then, using possibility degrees, the method introduces three PITS outranking sets (concordance, indifferent, and discordance sets) and defines strong and weak outranking relations. Further, a dominance matrix ranks alternatives. Finally, applying the pilot study can fruitfully demonstrate and signify the practicality and feasibility of the proposed decision-making approach.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"321 1","pages":"22-30"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141708485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fixed-Time Consensus for Multiagent Systems Under Switching Topology: A Distributed Zeroing Neural Network-Based Method 切换拓扑下多代理系统的固定时间共识：基于分布式清零神经网络的方法

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2024.3358050

Lin Xiao, Jiajie Luo, Jichun Li, Lei Jia, Jiguang Li

{"title":"Fixed-Time Consensus for Multiagent Systems Under Switching Topology: A Distributed Zeroing Neural Network-Based Method","authors":"Lin Xiao, Jiajie Luo, Jichun Li, Lei Jia, Jiguang Li","doi":"10.1109/MSMC.2024.3358050","DOIUrl":"https://doi.org/10.1109/MSMC.2024.3358050","url":null,"abstract":"The zeroing neural network (ZNN) has been utilized in various control applications, such as tracking and motion control. While ZNN has been widely employed, its utilization in consensus control schemes is rarely reported. In this study, we propose a novel distributed fixed-time ZNN (DFTZNN) scheme designed to achieve fixed-time and robust consensus in multiagent systems operating under a switching topology. Theoretical analysis is provided to establish the fixed-time stability and robustness of the proposed scheme in the presence of bounded noises. To highlight the superiority of the proposed method, we introduce an example demonstrating the estimation of the upper bound of a settling-time function. Theoretical analysis and a novel upper-bound estimation method are subsequently validated through numerical experiments, including a practical application in formation control. The comprehensive theoretical and simulation results demonstrate the superior performance of the DFTZNN scheme under both fixed and switching topologies, establishing it as a novel and systematic framework for designing consensus control schemes.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"55 S9","pages":"44-55"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141697912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Teleoperation Control of Autonomous Underwater Vehicle Toward Human on the Loop: Needs, Analyses, and Solutions 面向环路上的人类的自主潜水器远程操作控制：需求、分析和解决方案

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2023.3275770

Jing Yan, Tianming Gao, Xian Yang, Cailian Chen, Xinping Guan

{"title":"Teleoperation Control of Autonomous Underwater Vehicle Toward Human on the Loop: Needs, Analyses, and Solutions","authors":"Jing Yan, Tianming Gao, Xian Yang, Cailian Chen, Xinping Guan","doi":"10.1109/MSMC.2023.3275770","DOIUrl":"https://doi.org/10.1109/MSMC.2023.3275770","url":null,"abstract":"The autonomous underwater vehicle (AUV) has been regarded as a rapidly deployable tool for in situ sensing and monitoring of marine activities. However, because of the harsh marine environment, full autonomy to fulfill complex marine tasks is still unreachable. In this context, a human operator can make up this deficiency by bringing his or her experience and intelligence to the closed-loop control system. For an underwater grasping task, this article develops an underwater teleoperation system toward human on the loop (HOTL), which mainly includes an AUV, a surface buoy, a human operator, and a communication network. With acoustic and Wi-Fi communications, the surface buoy plays the role of communication hub between the human operator and the AUV. Then, a learning-based teleoperation control strategy is designed to achieve the grasping task for the AUV. Field tests are presented to verify the effectiveness of our developed underwater teleoperation system. Nevertheless, the theoretical framework of the underwater teleoperation system is still in the construction phase, and the related research suffers from many urgent problems. For that reason, we discuss and provide future directions for implementation in the more complex marine environment.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"63 13","pages":"2-13"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141714805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Collective Intelligence for Preventing Pandemic Crises: A Model-Centralized Organizational Framework 预防大流行病危机的集体智慧：集权式组织框架模型

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2024.3352850

Xiao-Kun Wu, Ke-Qing Deng, Tian-Fang Zhao, Wei-Neng Chen

{"title":"Collective Intelligence for Preventing Pandemic Crises: A Model-Centralized Organizational Framework","authors":"Xiao-Kun Wu, Ke-Qing Deng, Tian-Fang Zhao, Wei-Neng Chen","doi":"10.1109/MSMC.2024.3352850","DOIUrl":"https://doi.org/10.1109/MSMC.2024.3352850","url":null,"abstract":"Pandemic propagation, a highly nonlinear and complicated process, is difficult to understand, predict, and prevent in reality. The explosive growth of mass data and intelligent technologies poses new insights for solving this challenge. From a systematic perspective, this article proposes an organizational framework for pandemic crisis control. As a result, a model as a core component serves as a pandemic simulation and analog control. The collective data are sourced from realistic dynamics and feed the model after parameterization processing. Some advanced intelligent technologies are adopted to optimize simulation results and assist policymaking. To enhance the applicability of the framework, four typical routes and three levels of examples are provided. The routes contain diverse fields such as computer science, epidemiology, biomedicine, and social science. The examples are in relation to the few, regular, and rich levels of data information. Finally, this article paves the way for intelligent pandemic crises prevention and yields a fresh application paradigm in the field of collective intelligence (CI).","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"313 6","pages":"31-43"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141691576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

E-CARGO/RBC Research Guide: A Road Map for Researchers E-CARGO/RBC 研究指南：研究人员路线图

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2024.3377181

Haibin Zhu, Dongning Liu, Hua Ma, Yin Sheng, Libo Zhang, Qian Jiang

引用次数: 0

Biobjective Parallel Disassembly Line Balancing: A Problem Considering Government Benefit Workers 生物目标平行拆卸线平衡：考虑政府福利工人的问题

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-07-01 DOI: 10.1109/MSMC.2024.3371421

Shujin Qin, Jiacun Wang, Liang Qi, Xiwang Guo, Jiawei Li

引用次数: 0

Transformer-Based Forecasting for Sustainable Energy Consumption Toward Improving Socioeconomic Living: AI-Enabled Energy Consumption Forecasting 基于变压器的可持续能源消耗预测，改善社会经济生活：人工智能支持的能源消耗预测

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-04-01 DOI: 10.1109/MSMC.2023.3334483

Gautham Sreekumar, John Paul Martin, S. Raghavan, Christina Terese Joseph, S. P. Raja

{"title":"Transformer-Based Forecasting for Sustainable Energy Consumption Toward Improving Socioeconomic Living: AI-Enabled Energy Consumption Forecasting","authors":"Gautham Sreekumar, John Paul Martin, S. Raghavan, Christina Terese Joseph, S. P. Raja","doi":"10.1109/MSMC.2023.3334483","DOIUrl":"https://doi.org/10.1109/MSMC.2023.3334483","url":null,"abstract":"Smart energy management encompasses energy consumption prediction and energy data analytics. Energy consumption prediction or electric load forecasting leverages autoregressive and moving-average models. Recently, there has been a lot of traction in data-driven models for energy consumption prediction. In this article, a self-attention-based Transformer model is proposed. The deep-learning model captures long-term dependencies in the data sequence and can be used for long-term prediction. The proposed model is compared with autoregressive integrated moving average (ARIMA) and long short-term memory network (LSTM) models. The different models were applied to the load consumption data from a house located in Sceaux, Paris, France. The prediction windows of 24, 100, and 200 h were considered. To evaluate the performance, the mean absolute prediction error (MAPE) and root-mean-square error (RMSE) were considered as the metrics. The Transformer and LSTM models performed significantly better than ARIMA. Even though Transformer and LSTM performed on par, the load forecasted using Transformer was closer to the previous data in the dataset, which proves the better efficiency of the model. Since the Transformer model has transfer learning ability, it can be used as a pretrained model for training of other time-series datasets and, hence, the model can be potentially applied in other related prediction scenarios also, where time-series data are involved.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"1105 ","pages":"52-60"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140761285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Spam Text Detection Over Social Media Usage: A Supervised Sampling Approach for the Social Web of Things 社交媒体使用中的垃圾文本检测：针对社交物联网的监督抽样方法

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-04-01 DOI: 10.1109/MSMC.2023.3343950

Haewon Byeon, Sameer Jha, Ismail Keshta, Mohammed Wasim Bhatt, P. Singh, Latika Jindal, T. R. Vijaya Lakshmi

{"title":"Spam Text Detection Over Social Media Usage: A Supervised Sampling Approach for the Social Web of Things","authors":"Haewon Byeon, Sameer Jha, Ismail Keshta, Mohammed Wasim Bhatt, P. Singh, Latika Jindal, T. R. Vijaya Lakshmi","doi":"10.1109/MSMC.2023.3343950","DOIUrl":"https://doi.org/10.1109/MSMC.2023.3343950","url":null,"abstract":"A downsampling strategy based on negative selection density clustering (NSDC-DS) is proposed to improve classifier performance while employing random downsampling for unbalanced communication text. The discovery of self-anomalies via negative selection enhances traditional clustering. The detector and self-set are the sample center point and the sample to be clustered, respectively; anomalous matching is performed on the two; and the NSDC technique analyzes sample similarity. To improve on the traditional downsampling method, we use the Naïve Bayes Support Vector Machine (NBSVM) classifier to identify garbage in sampled communication samples, use principal component analysis (PCA) to evaluate sample information content, propose an improved PCA-signed directed graph (SGD) algorithm to optimize model parameters, and complete semisupervised communication spam text recognition over the Social Web of Things. Several datasets, including unbalanced communication text, were used to compare the improved approach against NSDC, NSDC-DS, PCA-SGD, and standard models. According to the trials, the improved model has a quicker and more consistent convergence speed.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"8 10","pages":"32-39"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140765407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multiobjective Human–Robot Collaborative Disassembly Sequence Planning: Considering the Properties of Components 多目标人机协作拆卸序列规划：考虑组件属性

IEEE Systems, Man, and Cybernetics Magazine Pub Date : 2024-04-01 DOI: 10.1109/MSMC.2023.3234172

Shujin Qin, Chong Li, Jiacun Wang, Shixin Liu, Ziyan Zhao, Xiwang Guo, Liang Qi

{"title":"Multiobjective Human–Robot Collaborative Disassembly Sequence Planning: Considering the Properties of Components","authors":"Shujin Qin, Chong Li, Jiacun Wang, Shixin Liu, Ziyan Zhao, Xiwang Guo, Liang Qi","doi":"10.1109/MSMC.2023.3234172","DOIUrl":"https://doi.org/10.1109/MSMC.2023.3234172","url":null,"abstract":"With the improvement of modern human living standards, the speed of product renewal is accelerating, and the classification and recycling of waste products and the reuse of resources have received great attention from scholars and industry. The disassembly of used products plays an important role in the implementation of the work. Considering the difference between the component values of a product and the disassembling complexity of each component, this article studies human–robot collaborative disassembly and investigates multiobjective disassembly sequence planning (DSP). Mathematical models are established with the optimization goals of maximizing profit and minimizing working time. The well-known optimizer CPLEX is used to verify the correctness of the mathematical model, and the gray wolf optimization algorithm (GWOA) is adopted to find the optimal solution. By comparing it with non-dominated sorting genetic algorithm III (NSGAIII) and multi-objective evolutionary algorithms based on decomposition with a collaborative resource allocation strategy (MOEAD-CRA), the adaptability of the algorithm to the proposed mathematical model is proved.","PeriodicalId":516814,"journal":{"name":"IEEE Systems, Man, and Cybernetics Magazine","volume":"111 ","pages":"15-23"},"PeriodicalIF":0.0,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140768926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0