Operational Evaluation Modeling

Clymer, John R.; Corey, Philip D.; Nili, Nafise

doi:10.1177/003754979005500603

Cited by 11 publications

(6 citation statements)

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“…Table I suggests some abbreviations. This problem is based on Mead and Conway [9] and Katz [6]. The following states are sufficient for this controller.…”

Section: Statement Of the Traffic-light Problemmentioning

confidence: 99%

“…An operational evaluation modeling-(OpEM)-directed graph model [6]- [8] of the traffic-light problem is shown in Fig. 24.…”

Section: K Solution Via Opem-directed Graph Model 13mentioning

confidence: 99%

“…These include synchronization, deconfliction, and resource contention. A system design and evaluation methodology [8] based on OpEM diagrams [6] is summarized as follows. First, design each system process to work optimally to perform and adapt its activities, given information about the current situation; Second, assume unconstrained process communication, and apply machine learning [8] to optimize coordination and collaboration of processes by iteratively: 1) adapting process operation to achieve overall system goals, 2) discovering essential knowledge sharing required to achieve such collaboration, and 3) allocating system processes to subsystems and define a subsystem coordination and communication method to connect each subsystem effectively to share essential information.…”

Section: K Solution Via Opem-directed Graph Model 13mentioning

confidence: 99%

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The design-methods comparison project

Bahill

Alford²,

Bharathan

et al. 1998

IEEE Trans. Syst., Man, Cybern. C

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Early in the system design process, a design method must be chosen. This choice is usually dictated by what methods the designer has previously used, not by an open selection process. In this paper, we provide descriptions of some available design methods and examples of their use. In this project, we will develop benchmark problems that will be solved by a variety of design methods and will identify characteristics of problems that might make one system design method more or less appropriate. The top-level question we wish to answer is "for which type of problem is each method best?"If a system is to be built, then the system must ultimately be described as a collection of state machines. However, these state machines are often not created by the systems engineers. The systems engineers use some method to create a high-level abstraction of the desired system. Then they turn this abstraction over to the specialty engineers who actually reduce it to a collection of state machines. In this paper, we present solutions for a simple design problem by using the following 11 high-level system design methods: state transition diagrams, algorithmic state machine (ASM) notation, model-based system engineering, Graphical Description Language, RDD-100, structured analysis (using entity relationship diagrams, data-flow diagrams, and state transition diagrams with Ward-Mellor notation), functional decomposition, object-oriented analysis (OOA) with Shlaer-Mellor notation, OOA and object-oriented design (OOD) with Booch notation, an operational evaluation modeling-(OpEM)-directed graph, and IDEF0. Each method was used by an expert user of that method. The solutions presented make it obvious that the choice of a design method greatly effects the resulting system design. Index Terms-Architecture, design methodology, logic design, object-oriented methods. ).M. Alford is an independent consultant, Dean (M'97) received the M. A. degree in information system consulting from Brigham Young University, Provo, UT, in 1989 and the Ph.D. degree in management information systems from the University of Arizona, Tucson, in 1995. He is a Research Scientist at the Center for Management Information, University of Arizona. He provides consulting and research services on a number of topics, including electronic meeting systems (EMS), collaborative business process reengineering methods, and collaborative systems analysis and design methods. He has helped develop group-enabled activity and data modeling software to support technical and nontechnical users. He also developed structured meeting methods for use with these tools. The activity model software has since been made commercially available through Ventana Corporation, Tucson. His research interests include electronic meeting support of process and data modeling, business process reengineering, systems analysis and design, and group elicitation of information systems requirements.Jeremy Duke received the B.S. degree in systems (software) engineering in 1994 and the M.S. degree in systems engine...

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“…Table I suggests some abbreviations. This problem is based on Mead and Conway [9] and Katz [6]. The following states are sufficient for this controller.…”

Section: Statement Of the Traffic-light Problemmentioning

confidence: 99%

“…An operational evaluation modeling-(OpEM)-directed graph model [6]- [8] of the traffic-light problem is shown in Fig. 24.…”

Section: K Solution Via Opem-directed Graph Model 13mentioning

confidence: 99%

Section: K Solution Via Opem-directed Graph Model 13mentioning

confidence: 99%

See 1 more Smart Citation

The design-methods comparison project

Bahill

Alford²,

Bharathan

et al. 1998

IEEE Trans. Syst., Man, Cybern. C

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“…This state-of-the-art graphical, discrete event simulation library works with ExtendTM (by Imagine That, Inc.) and has the power of much more costly, general-purpose simulation products. OpEMCSS, which was developed based on earlier work [5][6][7][8][9][10][11][12][13], is capable of representing several commonly used systems views including queuing, process and resource, and message flow models (see http://ecs.fullerton.edu/~jclymer~.…”

Section: Introduction Zmentioning

confidence: 99%

Optimization of Simulated System Effectiveness Using Evolutionary Algorithms

Clymer

1999

SIMULATION

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Using evolutionary algorithms, a search is performed based on a population where each population member consists of a vector of attribute values and a fitness value. A simulation of a system is run, given a particular set of the member attribute values, producing a fitness value. Fitness measures how well the system achieves its mission objectives. If the fitness has a random component, several runs are made to produce average fitness. The procedure is to select the best members from the population based on average fitness and mutate the member attribute values to produce new population members. Since population member attributes can affect process reaction times, wait logic, or decision logic, a search for the best attribute values over 50 to 100 generations can result in optimal fitness. In order to demonstrate the use of evolutionary algorithms in system optimization, a simple inventory system that has a complex fitness surface is considered.

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“…An OpEM [7][8][9][10][11][12][13][14][15] simulation program was developed that simulates surface ships and submarines transiting a surveillance area. A collection of signals was associated with ship type, either surface ship or submarine, each having a particular speed.…”

Section: Introductionmentioning

confidence: 99%

Induction Of Classification Rules From Noisy Sonar Features

1994

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Developing rules to classify surface ships and submarines based on noisy features extracted from underwater acoustic signals is difficult and time consuming; indeed, it is difficult to generate decision making rules for any complex system. The Operational Evaluation Modeling (OpEM) Simulation Tool Kit including Expert System Controller and Induction Program, discussed in this paper, greatly mitigates this problem for most complex system simulation projects such as airports, factories, or space defense systems. A theory for inductive learning of decision making rules in cybernetic systems is presented to provide a concise way-of thinking about inductive learning. An OpEM directed graph model is presented that describes operation of a sonar detection and classification system. An OpEM Pascal simulation of this system demonstrates how effective classification rules can be that are induced from simulation generated cases, even with noisy features present. The OpEM induction program is described and innovative features are discussed. Rules generated by the OpEM induction program are compared to rules obtained by Ross Quinlan's ID3 induction program. Performance of the OpEM induction program when noisy features are present is compared with ID3.

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Operational Evaluation Modeling

Cited by 11 publications

References 1 publication

The design-methods comparison project

The design-methods comparison project

Optimization of Simulated System Effectiveness Using Evolutionary Algorithms

Induction Of Classification Rules From Noisy Sonar Features

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