Improving the quality of conceptual modeling using cognitive mapping techniques

Conceptual modeling involves the understanding and communication between system analysts and end-users. Many factors may affect the quality of conceptual modeling processes as well as the models per se. Human cognition plays a pivotal role in understanding these factors and cognitive mapping techniques are effective tools to elicit and represent human cognition. In this paper, we look at the use of cognitive mapping techniques to improve the quality of conceptual modeling. We review frameworks on quality in conceptual modeling and examine the role of human cognition in conceptual modeling. The paper also discusses how human cognition is related to quality in conceptual modeling, the various cognitive mapping techniques, and how these cognitive mapping techniques can be used in conceptual modeling. Through a case study, the paper describes ways of incorporating cognitive mapping techniques to a popular systems development methodology—Soft Systems Methodology—to improve the quality of conceptual modeling.     

多架构体系建模与仿真联合平台

现代作战体系中通常涉及来自多个领域的复杂系统,因而体系设计时会采用到多个不同的建模工具与仿真工具,导致体系建模工具之间异构数据难以共享、体系建模工具与仿真工具联动困难等不足.为解决上述问题,提出了一种新型的多架构体系建模与仿真联合平台,形成了"元模型设计-体系建模-仿真验证"的全覆盖设计能力.在此基础上,以空地协同防御体系中的人机协同防御场景为例,验证了该平台对体系设计的有效性.具体来说,采用该平台设计了与案例场景相对应的元模型、建立了作战视图体系模型,并对作战任务中的战机行为进行了仿真,为战机出战方案设计提供了理论依据.     

水中对抗仿真系统实体模型管理问题的研究

水中对抗作战仿真系统是模拟水中武器对抗作战的网上仿真演练系统。对于大规模的仿真演练,必然要求开发有效的、功能完善的模型管理系统。该文介绍了开发仿真实体模型管理系统过程中的方法：首先从系统仿真建模工作开始进行分析和研究,采用层次化、模块化建模并将仿真模型与仿真实验平台有效分离,规范了建模过程,分析了采用DLL技术在模型实现中的应用,并根据模型的特点,分析了采用模型库与模型管理系统对仿真模型进行管理的方法。     

MODELING AND ARTIFICIAL INTELLIGENCE

The field of artificial intelligence ( AI) is concerned with improving the understanding of the nature of concepts such as knowledge, intelligence, and consciousness. In the development of the field, modeling the environment has emerged as a central task. Modeling in this sense is a broad term embracing three evolutionary levels: an early stage of biochemical structures, a middle stage in which neural systems emerge, and the later conceptual stage characterized by the use of symbolic structures such as language, interpreted images, and signs. Although AI is particularly concerned with specific area of symbolic knowledge processing, that of logical and relational knowledge, central efforts in this field are also directed at integrating all forms of symbolic modeling into effective solutions for knowledge processing on computers. Thus, methods from computer science are of major importance. This paper illustrates the integration of various forms of modeling within the field of AI. It also shows how a broad concept of modeling enriches AI, and how AI, in turn, brings a new emphasis and understanding of the concept of modeling into science.     

An interface for hierarchical modeling in object-oriented simulation

A graphical interface for a new simulation development environment is presented. This interface is described in relation to information hiding and visual layers. In the simulation development environment distinct types of entities may easily be modeled. This results in simulation models which are good representations of real world systems. We introduce two nodes which facilitate discrete event simulation modeling. Sequences of tasks may be assigned to various entities in a queue/server node. A multi-queues/multi-servers node permits the modeler to formulate server selection rules and queue selection rules for each type of entity. Servers may also have a queue selection rule.     

Conceptual and ontological modeling in information systems

Conceptual modeling of a subject domain, which produces its conceptual model, is an important stage in designing information systems. In recent years, much attention in the development of such systems has been given to reusing information resources and to providing access to them at the semantic level. Methods and technologies of ontological modeling have lately been under intensive development. In this paper, problems and preconditions of conceptual modeling of the subject domain in database technologies and information systems are discussed. Various approaches to conceptual modeling, conceptual modeling languages, and the respective tools are considered, various interpretations of the role of the conceptual model of the subject domain are discussed, and the current state of conceptual modeling tools produced by software industry is assessed. The relationships between the conceptual schemas of the subject domain and ontologies are analyzed and their similarities and differences are described. Terminological issues and the directions of research in the field of conceptual and ontological modeling are considered. An extensive list of references is given.     

Robust graph neural network method for target entity type recognition in a battlefield environment北大核心CSCD

With the rise of new combat styles, such as information and algorithmic warfare, target entity recognition in battlefield data analysis plays an important role in decision making. Battlefield situation data are typical battlefield data containing many dynamic entities with close interactions. However, such data often contain strong noise due to hostile interference or concealment; hence, they require higher robustness than general time-series data. This paper proposes a new method based on graph neural networks to represent and process the unstructured data and mine the category information of hostile combat entities. First, the dynamic time warping algorithm was used to establish a new graph structure between combat entities based on their trajectory. Then, a robust graph neural network method was proposed and applied for the type identification of combat entities beyond the radar identification range according to the node attribute information of combat entities. Test results on the simulation data set obtained from the military simulation platform reveal that the proposed method maximizes the temporal characteristics of the entity data and associated attribute information of each node. Compared with the graph neural network and multilayer perceptron methods that rely on singletime relation, the proposed method has advantages in identification accuracy and robustness, expanding the radius of operational entity identification to a certain extent. © 2023, Editorial Department of CAAI Transactions on Intelligent Systems. All rights reserved.     

信息系统概念建模研究框架①

信息系统概念建模是本世纪初产生的一门新学科,对信息系统的开发、引进、改造、标准化和集成具有重要的质量保证作用。针对已有研究存在的问题和未来的研究需求提出了一个研究框架,详细探讨了信息系统概念建模的涵义和范围,概念建模方法的种类和绩效评价,概念模型的内容与质量评估以及概念建模环境等方面存在的研究机遇问题,旨在为后续的概念建模研究工作提供一些参考。     

Agent-based simulation of affordance-based human behaviors in emergency evacuation

Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory. In this paper, we explore simulating human behaviors using affordance-based finite state automata (FSA) modeling, based on the ecological concept of affordance theory. To this end, we introduce the conceptual and generic framework of affordance-based human behavior simulation developed through our previous work. Following the generic framework, formal simulation models of affordance-based human behaviors are developed, especially for emergency evacuation, to mimic perception-based dynamic human actions interacting with emergent environmental changes, such as fire. A “warehouse fire evacuation” case is used to demonstrate the applicability of the proposed framework. The human action planning algorithms in the simulation model are developed and implemented using the Adjusted Floor Field Indicators, which represent not only the evacuee’s prior knowledge of the floor layout but the perceivable information about dynamic environmental changes. The results of our simulation study verify that the proposed framework accurately simulates human fire evacuation behavior. The proposed framework is expected to capture the natural manner in which humans behave in emergency evacuation and enhance the simulation fidelity of analyses and predictions of perceptual human behaviors/responses in the systems by incorporating cognitive intent into human behavior simulations.     

GSL: a requirements specification language for end-user intelligibility

Software Requirements Specifications (SRS) have been used to fill the communication gap between systems analysts and the end-users. SRSs should satisfy the needs of both systems analysts and end-users. Non-technical end-users require intelligible SRSs while systems analysts need more precise, clear and concise SRSs. Object-oriented methods cannot represent temporal relations between events precisely. However, object-oriented principles are widely used in systems analysis and designing. Hence, there is a need for a software requirements specification language which supports object-oriented analysis methods, represents temporal knowledge precisely and whose representation scheme resembles natural languages. The specification language presented in this paper, GSL, is designed to meet the above requirements. The language is based on First-order Temporal Logic (FTL), which has temporal operators in addition to classical logical connectives and quantifiers. Since FTL cannot represent relative temporal knowledge and it inherits problems with point-based time models, a new logical connective TAND and redefined AND connective are used to represent relative temporal knowledge and to solve the problems with FTL. The language employs object-oriented principles: events, conditions, rules and activities can be represented as objects as well as attributes of an object. However, systems analysts can decide whether to use object-oriented conceptual modeling or not. © 1998 John Wiley & Sons, Ltd.     

Holistic environmental soil-landscape modeling of soil organic carbon

In environmental soil-landscape modeling (ESLM), the selection of predictive variables is commonly contingent on the researchers' domain expertise on soil–environment processes. This variable selection strategy may suffer bias or even fail in regions where the process knowledge is insufficient. To overcome this problem, this study demonstrates a holistic ESLM framework which consists of five components: model conceptualization, data compilation, process identification, parsimonious model calibration, and model validation. Based on the STEP-AWBH conceptual model, a comprehensive pool of 210 potential environmental variables that exhaustively cover pedogenic and environmental factors was constructed. This was followed by strategic variable selection and development of parsimonious prediction models using machine learning techniques. The all-relevant variable selection successfully identified the major and minor factors relevant to the SOC variation, showing that the major factors important for explaining SOC variation in Florida were vegetation and soil water gradient. Topography and climate showed moderate effects on SOC variation. Parsimonious SOC models developed using four minimal-optimal variable selection techniques and simulated annealing yielded optimal predictive performance with minimal model complexity. The holistic ESLM framework not only provides a new view of selecting and utilizing variables for predicting soil properties but can also assist in identifying the underlying processes of soil-environment systems of interest. Due to the flexibility of the framework to incorporate various types of variable selection and modeling techniques, the holistic environmental modeling strategy can be generalized to other environmental modeling domains for both prediction and process identification.     

Towards a holonic multiple aspect analysis and modeling approach for complex systems: Application to the simulation of industrial plants

In complex systems, multiple aspects interact and influence each other. A vast number of entities are present in the system. Traditional modeling and simulation techniques fail to capture interactions between loosely coupled aspects of a complex system. In this work, we describe a generic framework for modeling and analysis of naturally distributed and complex systems based on Holonic Multi-Agent paradigm. We illustrate the suitability of our generic model by applying it to the modeling and simulation of an important industrial plant in the east of france.     

作战模拟方法的水面舰艇反导作战效能评估

在对抗仿真的基础上研究了水面舰艇对来袭导弹的作战效能.在分析水面舰艇反导作战过程的基础上,结合水面舰艇反导的特点,提出了基于攻防对抗仿真的反导作战效能评估一般可采用的四个环节.并采用自顶向下的分析方法,建立了水面舰艇反导作战效能评估的指标体系.还对反导作战效能评估方法和仿真模型的建立、仿真平台设计等进行了研究.最后以两艘水面舰艇对抗为例评估了水面舰艇的反导作战效能.结果表明该方法合理可行.     

对抗条件下反导导弹拦截能力研究

受对抗手段的影响，反导导弹可能出现指令周期增大、有效末制导距离减小、过载需求加大等现象，最终表现为其拦截能力的变化。为了研究对抗条件下上述因素对反导导弹拦截能力的影响，建立了反导导弹的逻辑模型及其视场变化模型，实现了包括攻防双方主要武器系统模型的对抗仿真环境，最后，通过仿真实验，研究了反导导弹指令周期、末制导开机距离及弹道导弹弹道变化等因素对反导导弹拦截能力的影响。     

An integrated data collection and analysis framework for remote monitoring and planning of construction operations

Recent advances in data collection and operations analysis techniques have facilitated the process of designing, analyzing, planning, and controlling of engineering processes. Mathematical tools such as graphical models, scheduling techniques, operations research, and simulation have enabled engineers to create models that represent activities, resources, and the environment under which a project is taking place. Traditionally, most simulation paradigms use static or historical data to create computer interpretable representations of real engineering systems. The suitability of this approach for modeling construction operations, however, has always been a challenge since most construction projects are unique in nature as every project is different in design, specifications, methods, and standards. Due to the dynamic nature and complexity of most construction operations, there is a significant need for a methodology that combines the capabilities of traditional modeling of engineering systems and real time field data collection. This paper presents the requirements and applicability of a data-driven modeling framework capable of collecting and manipulating real time field data from construction equipment, creating dynamic 3D visualizations of ongoing engineering activities, and updating the contents of a discrete event simulation model representing the real engineering system. The developed framework can be adopted for use by project decision-makers for short-term project planning and control since the resulting simulation and visualization are completely based on the latest status of project entities.     

A theater level simulation with COMO-III

A computerized modeling system is described which presents the analysis of a large number of interacting units operating at various levels of managerial control. The COMO-III system employs a “tool kit” approach to modelling by providing great flexibility in fitting the various parts of the model together. The decision maker/manager can directly interact with the model through a special COMIL language to permit “what if” analysis to be performed in direct support of the decision process.First the model is described in general and then we report the application of the COMO-III modeling system to a theater level air defense simulation. COMO-III is an advanced simulation package developed by the SHAPE Technical Center (The Hague, Netherlands). We believe that this may be the first such simulation of theater level combat in the level of detail described. A large number of individual air defense weapons are simulated on an event oriented basis. The COMO-III system demonstrated to us a considerable state-of-the-art advancement in the methodology of military simulation. Our development efforts also encompassed an expansion of COMO-III to include interactive gaming of individual Air Force interceptor aircraft which showed the model to be unusually flexible. Representative simulation results are presented together with perceived advantages from employing the COMO-III system. It has both methodological and managerial advantages and is entirely government owned and operated. Because the features of COMO-III have not been previously described in the literature, a specially constructed example and commentary are included in an appendix. Implications for future applications are also introduced.     

虚拟环境概念模型建模方法研究*

由于目前常用的概念建模方法对于虚拟环境中物体方位、行为和交互模型等信息缺乏足够的描述方法,在吸取现有概念模型建模概念和技术的基础上,提出了虚拟环境概念模型建模框架,给出了虚拟场景静态结构和动态行为的概念建模方法,并通过虚拟化学实验平台的设计和实现验证了方法的可行性。通过在虚拟环境设计阶段引入概念建模阶段,使不具备专业编程知识的普通人员通过使用图形化的建模语言也能够进行虚拟环境的开发,为虚拟环境的顶层设计提供了一个科学、有效的手段。     

Object structures for real-time systems and simulators

The market for real-time applications has grown considerably in years, and in response engineering methods have also improved. Today's techniques, while adequate for building moderately complex embedded applications, are inadequate for building the large, highly reliable, very complex real-time applications that are increasingly in demand. To build such large systems, engineering teams need a more uniform, integrated approach than is available today. Ideally, the development approach would make uniform the representations of both application environments and control systems as they proceed through various system engineering phases. The ideal representation (or modeling) scheme should be effective not only for abstracting system designs but also for representing the application environment. It should also be capable of manipulating logical values and temporal characteristics at varying degrees of accuracy. This ideal modeling scheme is not likely to be realized through conventional object models. Although they are natural building blocks for modular systems, conventional object models lack concrete mechanisms to represent the temporal behavior of complex, dynamic systems. This article describes a real-time object structure that can flexibly yet accurately specify the temporal behavior of modeled subjects. This approach supports strong requirements-design traceability, the feasibility of thorough and cost-effective validation, and ease of maintenance     

基于工作流网的实时协同系统模拟技术

基于Petri网和工作流的概念，提出一种实时协同系统的形式化模拟与分析技术——逻辑工作流网，逻辑工作流网是抑制弧Petri网和高级Petri网的抽象和扩展，其变迁的输入／输出受逻辑表达式的约束，它与一般工作流网相比，能够在一定程度上缓解状态空间爆炸问题，且便于系统设计人员掌握和使用，该文分析了逻辑工作流网的若干性质及组合网的性质继承问题，并以网上企业销售系统为例，说明逻辑工作流网在实时协同系统模拟分析中的应用。     

MeDEA: A database evolution architecture with traceability

One of the most important challenges that software engineers (designers, developers) still have to face in their everyday work is the evolution of working database systems. As a step for the solution of this problem in this paper we propose MeDEA, which stands for Metamodel-based Database Evolution Architecture. MeDEA is a generic evolution architecture that allows us to maintain the traceability between the different artifacts involved in any database development process. MeDEA is generic in the sense that it is independent of the particular modeling techniques being used. In order to achieve this, a metamodeling approach has been followed for the development of MeDEA. The other basic characteristic of the architecture is the inclusion of a specific component devoted to storing the translation of conceptual schemas to logical ones. This component, which is one of the most noteworthy contributions of our approach, enables any modification (evolution) realized on a conceptual schema to be traced to the corresponding logical schema, without having to regenerate this schema from scratch, and furthermore to be propagated to the physical and extensional levels.