Operational Evaluation Model Research Articles

Operational Efficiency Evaluation of the Weaponry System Supported by Information System

Information is the operational efficiency multiplier of modern weaponry system. Firstly, the operational efficiency multiplication constant of weaponry is defined, and the operational efficiency evaluation model of the weaponry system supported by information system is also set up. Then, it works out the operational efficiency of weaponry for both operational sides. Finally, an example is also given, which turns out that the operational efficiency of weaponry can be remarkably enhanced by information system.

Efficiency evaluation model of joint air defense operation based on advanced evidence reasoning

According to the advantage in dealing with uncertainty reasoning problems the evidence theory was introduced to evaluate the efficiency of joint air defense operation.Firstly an ordinary model based on evidential reasoning was proposed then fuzzy theory was applied to solve the problems with fuzzy concept or relations.The advanced evidence model was introduced to evaluate the efficiency of joint air defense operation aiming at the weighted or correlative evidence combination problems occured in actual condition.An example has been given to show the correctness of this new method and show the practicability and effectiveness in efficiency evaluation of joint air defense operation.

A driver-centred safety evaluation model of lane change operation for the aged driver

In this paper, a safety evaluation model was proposed, which was used to assist an aged driver with decision making while executing a lane change/merge (LC/M) task. This model combined the aged driver's lane change properties, such as lateral acceleration, longitudinal acceleration, time to accomplish the lane change and the permissible deceleration after finishing the lane change in the destination lane. It can be set to adapt to different types of driver. Based on this model, a visual warning assist system is built on a driving simulator. It gives out the safety information of the LC/M operation to the driver with a diode-bar mode in real-time. Some experiments that are centred on the aged driver are designed and executed. The effectiveness of the model was confirmed through the experiment.

1.2.2 Engineering of Complex Adaptive Systems using OpEMCSS

AbstractA graphical discrete event simulation library is proposed for the engineering of complex adaptive systems. This library works with EXTEND (Imagine That Inc), an inexpensive yet capable and easy to use simulation software package, and it is called Operational Evaluation Modeling for Context‐Sensitive Systems (OpEMCSS). Context‐Sensitive Systems (CSS) is a systems theory, based on finite state machines, that can assist a system designer in understanding and evaluating complex adaptive systems, represented as communicating concurrent (parallel) processes. CSS theory can be expressed using the OpEM graphical modeling language. Thus, OpEMCSS is a graphical simulation library that can model systems based on CSS theory and the OpEM language. As an example, an OpEMCSS model is discussed such that each of two intelligent agents learn rules that maximizes their average reward in the prisoner's dilemma game.

An evaluation model of enterprise operation and its application

This paper put forward an evaluation model with which one can make a comprehensive calculation of enterprise operation status concerning profit ability, repaying capability, economic efficiency and developing potential; and meanwhile the method of maximal distinction is employed to conduct the data synthesis of several targets and draw the conclusion of evaluation. Finally, a pratical illustration is given in this paper.

Simulation-Based Engineering Of Complex Adaptive Systems

Systems to be developed in the future will likely be more complex than in the past. The number of be haviors a system can exhibit is one measure of sys tem complexity. A complex system can be described as a large network of communicating subsystems. A regional or national Intelligent Transportation System exemplifies such a system. If each subsystem in the network adapts its behavior to collaborate with other subsystems to achieve overall goals, such a system is called a Complex Adaptive System (CAS). In this paper a building elevator system provides an example CAS in which each elevator collaborates with others to optimize system performance. A Context-Sensitive System model that explicitly deals with the complexity of CAS is dicussed. A graphi cal simulation language, Operational Evaluation Modeling for Context-Sensitive Systems (OpEMCSS), assists in understanding CAS and automates most complex simulation details and semantics. OpEMCSS is distinctive from most simulation languages that have a graphical user interface in its ability to du plicate processes without having to show every in stance onscreen. OpEMCSS and its use in simula tion-based systems engineering of CAS are discussed.

Modeled response of photochemical oxidants to systematic reductions in anthropogenic volatile organic compound and NOx emissions

As an exercise in model sensitivity, the Environmental Protection Agency's regional oxidant model (ROM) was run for several simulations to study the impact of across‐the‐board reductions in anthropogenic volatile organic compound (VOC) and NOx emissions on the photochemical environment of the eastern United States. The ROM, which simulates most of the physical and chemical processes responsible for the formation of O3 on regional scales, was used to simulate a widespread high O3 episode in the eastern United States. Separate simulations were performed over the period July 2–10, 1988, for each of the sensitivity runs. An operational evaluation and several model diagnostics were performed on the base case simulation. The sensitivity runs reduced anthropogenic NOx and VOC emissions separately and in combination in increments of 25% of full scale emissions. Biogenic emissions were held constant across all sensitivity tests. Seventeen of the potential 25 nodes of the NOx, VOC emissions reduction matrix were simulated. In the analysis the modeled domain (the eastern half of the United States) is subdivided into several chemically coherent regions. Several chemical species, including afternoon average concentrations of O3, PAN, HNO3, OH, and HO2 + RO2, are examined to gain an understanding of how the reduction in emissions affected the overall chemical system for each sensitivity test. Results are presented as a series of statistical and graphical displays illustrating the response of the system within the selected subdomains to the emission reductions.

System design and evaluation using discrete event simulation with AI

During system design and evaluation, development of optimal decision making rules for an intelligent system can be very difficult. The Operational Evaluation Modeling (OpEM) Fuzzy, Adaptive Expert System Controller, integrated into the OpEM Simulation Tool Kit, has greatly facilitated this task. The rule specification language for Controller consists of all primitives needed to implement local and global decision making. These primitives include fuzzy facts to transform analog variables into discrete concepts and variable instantiation of facts to consider lists of facts in context sensitive, global decisions. A single-track railroad system is evaluated as an example context sensitive system, and other methods of decision making are compared with OpEM. Future research is discussed that adds a machine learning module to Controller, called Supervisor, to automatically search for better decision making rules.

Induction Of Classification Rules From Noisy Sonar Features

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.

Induction of decision making rules for context sensitive systems

System design and analysis of highly context-setrsitive systems is both a difficult and time consuming problem. An induction program is discussed that greatly mitigates this problem. The Operational Evaluation Modeling (Op EM) Induction program receives, as input, a case file generated by an OpEM discrete event simulation program. Each case consists of a decision fact plus all knowledge base facts available for this decision (i.e., the decision context). The OpEM induction program analyzes this set of cases and produces an optimal set of rules that decides all of these cases correctly. An OpEM directed graph model is presented that describes the complex, context-sensitive parallel processes of a single-track railroad system, and a Pascal simulation of this railroad system is described to demonstrate that effective decision rules can be induced from extracted expert knowiedge obtained from simulation generated cases. A description of the OpEM induction program is provided, and rules generated by it are compared with rules generated by Ross Quinlan's ID3 Induction prograin using the saine set of cases.

Discrete event fuzzy airport control

A discrete event simulation that uses a modified expert system as a controller is described. Fuzzy logic concepts from analog controllers are applied in the expert system controller to mimic human control of an airport, modeled with a combined discrete and continuous state space. The controller is adaptive so rule confidences are automatically varied to achieve near optimum system performance. An explicit formalism, called operational evaluation modeling (OpEM), is used to describe airport operations. This formalism assists a systems analyst in visualizing system operation and, in particular, greatly assists in performing the knowledge engineering required to determine control rules. >

OpEM distributed simulation

Distributed simulation based on Opera tional Evaluation Modeling (OpEM) is discussed. OpEM, a system design and analysis methodology, uses a two-dimen sional, directed graph language to describe system operation. The OpEM simulation programming system, that implements this methodology, includes object-oriented event processing routines, moving-object routines, an expert system controller, and continuous system simulation routines. These routines are required to model large systems, such as the Strategic Defense Initiative (SDI) systems, that are characterized by closely coupled, context sensitive interactions. These interactions are modeled using a large global state space consisting of both discrete and continuous state variables. Execution of such large, complex models on uniprocessors can be slow; therefore, possible speedup by execution on a multiprocessor system, a set of processors that share memory, is investigated. A generic surface- ship warfare simulation, characteristic of many large models, is executed on a simulation of a multiprocessor system to investigate speedup.