复杂系统建模与仿真(英文)最新文献_第8页

Modeling and Analyzing of Breast Tumor Deterioration Process with Petri Nets and Logistic Regression 乳腺肿瘤恶化过程的Petri网和Logistic回归建模与分析

复杂系统建模与仿真(英文) Pub Date : 2022-09-30 DOI: 10.23919/CSMS.2022.0016

Xuyue Wang;Wangyang Yu;Zeyuan Ding;Xiaojun Zhai;Sangeet Saha

{"title":"Modeling and Analyzing of Breast Tumor Deterioration Process with Petri Nets and Logistic Regression","authors":"Xuyue Wang;Wangyang Yu;Zeyuan Ding;Xiaojun Zhai;Sangeet Saha","doi":"10.23919/CSMS.2022.0016","DOIUrl":"10.23919/CSMS.2022.0016","url":null,"abstract":"It is important to understand the process of cancer cell metastasis and some cancer characteristics that increase disease risk. Because the occurrence of the disease is caused by many factors, and the pathogenesis process is also complicated. It is necessary to use interpretable and visual modeling methods to characterize this complex process. Machine learning techniques have demonstrated extraordinary capabilities in identifying models and extracting patterns from data to improve medical prognostic decisions. However, in most cases, it is unexplainable. Using formal methods to model can ensure the correctness and understandability of prediction decisions in a certain extent, and can well visualize the analysis process. Coloured Petri Nets (CPN) is a powerful formal model. This paper presents a modeling approach with CPN and machine learning in breast cancer, which can visualize the process of cancer cell metastasis and the impact of cell characteristics on the risk of disease. By evaluating the performance of several common machine learning algorithms, we finally choose the logistic regression algorithm to analyze the data, and integrate the obtained prediction model into the CPN model. Our method allows us to understand the relations among the cancer cell metastasis and clearly see the quantitative prediction results.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 3","pages":"264-272"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9906545/09906550.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49561829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Evolutionary Adaptive System for Prediction of Strategy Influence: A Case Study of Government Regulation Guided Brand Innovation 战略影响预测的进化适应系统——以政府规制引导的品牌创新为例

复杂系统建模与仿真(英文) Pub Date : 2022-09-30 DOI: 10.23919/CSMS.2022.0011

Jiali Lin;Qiaomei Li;Guangsheng Lin;Zhihui He;Dazhi Jiang;Hao Liu

{"title":"An Evolutionary Adaptive System for Prediction of Strategy Influence: A Case Study of Government Regulation Guided Brand Innovation","authors":"Jiali Lin;Qiaomei Li;Guangsheng Lin;Zhihui He;Dazhi Jiang;Hao Liu","doi":"10.23919/CSMS.2022.0011","DOIUrl":"10.23919/CSMS.2022.0011","url":null,"abstract":"Decision making is one of the common human activities. But in complex, interactive, and dynamic systems, it is extremely important to make decisions scientifically because the influence of the behavior after decision making is generally irreversible. The predictability of behavior influence is an effective way to improve the scientific decision making. As a new branch of computing, computational experiment is an emerging management method for research on complex systems. In this paper, based on particle swarm intelligence, an evolutionary adaptive system model of brand innovation in the toy industry cluster is constructed. By imitating the evolution process of the complex adaptive system, this method is helpful to analyze the impact of the management behavior brought to simulation system, predict the management behavior in real world, and finally choose the best management strategy. This simulation tried to figure out the affection of government regulation strategies and provide corresponding assessments and recommendations, which gives a new solution to assist the government to effectively judge the influence of the macro policy, as well as provides a new way of thinking of the related intelligent decision making.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 3","pages":"197-212"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9906545/09906546.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43246331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Performance Prediction in Batch-Based Assembly System with Bernoulli Machines and Changeovers 含伯努利机和转换的批量装配系统动态性能预测

复杂系统建模与仿真(英文) Pub Date : 2022-09-30 DOI: 10.23919/CSMS.2022.0015

Zunjun Wang;Zhiyang Jia;Xiuxuan Tian;Jingchuan Chen;Bei Pan

{"title":"Dynamic Performance Prediction in Batch-Based Assembly System with Bernoulli Machines and Changeovers","authors":"Zunjun Wang;Zhiyang Jia;Xiuxuan Tian;Jingchuan Chen;Bei Pan","doi":"10.23919/CSMS.2022.0015","DOIUrl":"10.23919/CSMS.2022.0015","url":null,"abstract":"Worldwide competition and diverse demand of customers pose great challenges to manufacturing enterprises. How to organize production to achieve high productivity and low cost becomes their primary task. In the mean time, the rapid pace of technology innovation has contributed to the development of new types of flexible automation. Hence, increasing manufacturing enterprises convert to multi-product and small-batch production, a manufacturing strategy that brings increased output, reduced costs, and quick response to the market. A distinctive feature of small-batch production is that the system operates mainly in the transient states. Transient states may have a significant impact on manufacturing systems. It is therefore necessary to estimate the dynamic performance of systems. As the assembly system is a typical class of production systems, in this paper, we focus on the problem of dynamic performance prediction of the assembly systems that produce small batches of different types of products. And the system is assumed to be characterized with Bernoulli reliability machines, finite buffers, and changeovers. A mathematical model based on Markovian analysis is first derived and then, the analytical formulas for performance evaluation of three-machine assembly systems are given. Moreover, a novel approach based on decomposition and aggregation is proposed to predict dynamic performance of large-scale assembly systems that consist of multiple component lines and additional processing machines located downstream of the assemble machine. The proposed approach is validated to be highly accurate and computationally efficient when compared to Monte Carlo simulation.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 3","pages":"224-237"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9906545/09906886.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41913783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Dynamic Scheduling Algorithm Based on Evolutionary Reinforcement Learning for Sudden Contaminant Events Under Uncertain Environment 不确定环境下突发污染事件的进化强化学习动态调度算法

复杂系统建模与仿真(英文) Pub Date : 2022-09-30 DOI: 10.23919/CSMS.2022.0014

Chengyu Hu;Rui Qiao;Zhe Zhang;Xuesong Yan;Ming Li

引用次数: 1

A Discrete Artificial Bee Colony Algorithm for Stochastic Vehicle Scheduling 随机车辆调度的离散人工蜂群算法

复杂系统建模与仿真(英文) Pub Date : 2022-09-30 DOI: 10.23919/CSMS.2022.0012

Yuanyuan Li;Yindong Shen;Jingpeng Li

引用次数: 0

Large-Scale Expensive Optimization with a Switching Strategy 具有切换策略的大规模昂贵优化

复杂系统建模与仿真(英文) Pub Date : 2022-09-30 DOI: 10.23919/CSMS.2022.0013

Mai Sun;Chaoli Sun;Xiaobo Li;Guochen Zhang;Farooq Akhtar

引用次数: 0

Optimal Design of Flexible Job Shop Scheduling Under Resource Preemption Based on Deep Reinforcement Learning 基于深度强化学习的资源抢占下柔性车间调度优化设计

复杂系统建模与仿真(英文) Pub Date : 2022-06-01 DOI: 10.23919/CSMS.2022.0007

Zhen Chen;Lin Zhang;Xiaohan Wang;Pengfei Gu

{"title":"Optimal Design of Flexible Job Shop Scheduling Under Resource Preemption Based on Deep Reinforcement Learning","authors":"Zhen Chen;Lin Zhang;Xiaohan Wang;Pengfei Gu","doi":"10.23919/CSMS.2022.0007","DOIUrl":"10.23919/CSMS.2022.0007","url":null,"abstract":"With the popularization of multi-variety and small-batch production patterns, the flexible job shop scheduling problem (FJSSP) has been widely studied. The sharing of processing resources by multiple machines frequently occurs due to space constraints in a flexible shop, which results in resource preemption for processing workpieces. Resource preemption complicates the constraints of scheduling problems that are otherwise difficult to solve. In this paper, the flexible job shop scheduling problem under the process resource preemption scenario is modeled, and a two-layer rule scheduling algorithm based on deep reinforcement learning is proposed to achieve the goal of minimum scheduling time. The simulation experiments compare our scheduling algorithm with two traditional metaheuristic optimization algorithms among different processing resource distribution scenarios in static scheduling environment. The results suggest that the two-layer rule scheduling algorithm based on deep reinforcement learning is more effective than the meta-heuristic algorithm in the application of processing resource preemption scenarios. Ablation experiments, generalization, and dynamic experiments are performed to demonstrate the excellent performance of our method for FJSSP under resource preemption.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 2","pages":"174-185"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9841527/09841531.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42448649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Laparoscopic Cholecystectomy Simulation Using a Particle-Based Physical System 基于粒子物理系统的腹腔镜胆囊切除术实时仿真

复杂系统建模与仿真(英文) Pub Date : 2022-06-01 DOI: 10.23919/CSMS.2022.0009

Hongyu Wu;Fan Ye;Yang Gao;Yu Cong;Aimin Hao

{"title":"Real-Time Laparoscopic Cholecystectomy Simulation Using a Particle-Based Physical System","authors":"Hongyu Wu;Fan Ye;Yang Gao;Yu Cong;Aimin Hao","doi":"10.23919/CSMS.2022.0009","DOIUrl":"10.23919/CSMS.2022.0009","url":null,"abstract":"Laparoscopic cholecystectomy is used to treat cholecystitis and cholelithiasis. Because the high risk of the surgery prevents novice doctors from practicing it on real patients, VR-based surgical simulation has been developed to simulate surgical procedures to train surgeons without patients, cadavers, or animals. In this study, we propose a real-time system designed to provide plausible visual and tactile simulation of the main surgical procedures. To achieve this, the physical properties of organs are modeled by particles, and cluster-based shape matching is used to simulate soft deformation. The haptic interaction between tools and soft tissue is modeled as a collision between a capsule and particles. Constraint-based haptic rendering is used to generate feedback force and the non-penetrating position of the virtual tool. The proposed system can simulate the major steps of laparoscopic cholecystectomy, such as the anatomy of Calot's triangle, clipping of the cystic duct and biliary artery, disjunction of the cystic duct and biliary artery, and separation of the gallbladder bed. The experimental results show that haptic rendering can be performed at a high frequency (> 900 Hz), whereas mesh skinning and graphics rendering can be performed at 60 frames per second (fps).","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 2","pages":"186-196"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9841527/09841530.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47061598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Q-Learning-Based Teaching-Learning Optimization for Distributed Two-Stage Hybrid Flow Shop Scheduling with Fuzzy Processing Time 基于q学习的模糊处理时间下分布式两阶段混合流水车间调度的教-学优化

复杂系统建模与仿真(英文) Pub Date : 2022-06-01 DOI: 10.23919/CSMS.2022.0002

Bingjie Xi;Deming Lei

{"title":"Q-Learning-Based Teaching-Learning Optimization for Distributed Two-Stage Hybrid Flow Shop Scheduling with Fuzzy Processing Time","authors":"Bingjie Xi;Deming Lei","doi":"10.23919/CSMS.2022.0002","DOIUrl":"10.23919/CSMS.2022.0002","url":null,"abstract":"Two-stage hybrid flow shop scheduling has been extensively considered in single-factory settings. However, the distributed two-stage hybrid flow shop scheduling problem (DTHFSP) with fuzzy processing time is seldom investigated in multiple factories. Furthermore, the integration of reinforcement learning and metaheuristic is seldom applied to solve DTHFSP. In the current study, DTHFSP with fuzzy processing time was investigated, and a novel Q-learning-based teaching-learning based optimization (QTLBO) was constructed to minimize makespan. Several teachers were recruited for this study. The teacher phase, learner phase, teacher's self-learning phase, and learner's self-learning phase were designed. The Q-learning algorithm was implemented by 9 states, 4 actions defined as combinations of the above phases, a reward, and an adaptive action selection, which were applied to dynamically adjust the algorithm structure. A number of experiments were conducted. The computational results demonstrate that the new strategies of QTLBO are effective; furthermore, it presents promising results on the considered DTHFSP.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 2","pages":"113-129"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9841527/09841529.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43454572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Distributed Flexible Job-Shop Scheduling Problem Based on Hybrid Chemical Reaction Optimization Algorithm 基于混合化学反应优化算法的分布式柔性作业车间调度问题

复杂系统建模与仿真(英文) Pub Date : 2022-06-01 DOI: 10.23919/CSMS.2022.0010

Jialei Li;Xingsheng Gu;Yaya Zhang;Xin Zhou

{"title":"Distributed Flexible Job-Shop Scheduling Problem Based on Hybrid Chemical Reaction Optimization Algorithm","authors":"Jialei Li;Xingsheng Gu;Yaya Zhang;Xin Zhou","doi":"10.23919/CSMS.2022.0010","DOIUrl":"10.23919/CSMS.2022.0010","url":null,"abstract":"Economic globalization has transformed many manufacturing enterprises from a single-plant production mode to a multi-plant cooperative production mode. The distributed flexible job-shop scheduling problem (DFJSP) has become a research hot topic in the field of scheduling because its production is closer to reality. The research of DFJSP is of great significance to the organization and management of actual production process. To solve the heterogeneous DFJSP with minimal completion time, a hybrid chemical reaction optimization (HCRO) algorithm is proposed in this paper. Firstly, a novel encoding-decoding method for flexible manufacturing unit (FMU) is designed. Secondly, half of initial populations are generated by scheduling rule. Combined with the new solution acceptance method of simulated annealing (SA) algorithm, an improved method of critical-FMU is designed to improve the global and local search ability of the algorithm. Finally, the elitist selection strategy and the orthogonal experimental method are introduced to the algorithm to improve the convergence speed and optimize the algorithm parameters. In the experimental part, the effectiveness of the simulated annealing algorithm and the critical-FMU refinement methods is firstly verified. Secondly, in the comparison with other existing algorithms, the proposed optimal scheduling algorithm is not only effective in homogeneous FMUs examples, but also superior to existing algorithms in heterogeneous FMUs arithmetic cases.","PeriodicalId":65786,"journal":{"name":"复杂系统建模与仿真(英文)","volume":"2 2","pages":"156-173"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/9420428/9841527/09841532.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47043042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1