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In this study we will describe an intervention decision-support method related to residential buildings, which is modelling the condition of buildings based on linguistic expert opinions so that it is capable of taking into consideration the uncertainties included in the expert opinions. Fuzzy signature-based model is used, wherein the uncertainties are integrated into the system by applying interval...
Influence diagrams is getting extensively applied as rule acquisition in economics, business, and military fields, in traditional influence diagrams, computational models of dependence relations are established by probability distribution, which has good performance in deterministic information system. However, information systems(IS) in real world usually are uncertain or approximate, such as IS...
We present an experimental design method for choosing optimal experiments to reduce dynamics uncertainty in dynamical gene networks. The method, takes into account both the modeling objective and the experimental error.
Deep and wide surveys of the sky have led to a remarkable set of discoveries in cosmology. As the survey volumes become so large that statistical uncertainties almost disappear, cosmological modeling must reach unprecedented levels of scale and accuracy to properly interpret observational results. I will describe the key scientific problems and issues involved and then present the HACC (Hardware/Hybrid...
Obtaining informative measurements is a fundamental problem when inadequate models are used to guide the design of experiments. A comprehensive approach to experimental design for inadequate physics-based models is proposed by focusing on the coupling between the structural uncertainty modeling and the adaptive data collection process. First, by taking advantage of the structure of physics-based models,...
A computationally efficient model-based design of experiments (MBDOE) strategy is developed to plan an optimal experiment by specifying the experimental stimulation magnitudes and measurement points. The strategy is extended from previous work which optimized the experimental design over a space of measurable species and time points. We include system inputs (stimulation conditions) in the experiment...
Current formalisms for modelling a Clinical Practice Guideline (CPG) as a Computer-Interpretable Guideline (CIG) do not support the explicit representation of uncertainty due to the unpredictability of treatment outcomes and the incomplete knowledge of the actual patient condition. Given this limitation, the existing CIG approaches support only the computation of patient-specific diagnostic and treatment...
When faced with a complicated visual scene many animals including humans attend to important regions in a systematic serial manner. The ability to orient rapidly towards an important region in a scene allows an organism to accomplish activities, such as navigation, foraging and detecting possible prey/mates. Developing a computational model of visual attention has long been of interest as such models...
Forest fires are a major risk factor with strong impact at ecological-environmental and socio-economical levels, reasons why their study and modeling is very important. However, the models frequently have a certain level of uncertainty in some input parameters given that they must be approximated or estimated, as a consequence of diverse difficulties to accurately measure the conditions of the phenomenon...
This paper proposes the analysis of probabilistic equilibrium models of electricity markets by means of point estimated methods. We follow a model to address generation companies' strategic analysis based on a conjectured price-response market equilibrium representation. Furthermore, we consider uncertainty in power system demands. The resulting probabilistic equilibrium problem is then solved using...
The large-scale integration of renewable resources has recently raised interest in systematic methods for committing locational reserves in order to secure the system against contingencies and the unpredictable and highly variable fluctuation of renewable energy supply, while accounting for power flow constraints imposed by the transmission network. In this paper we compare two approaches for committing...
An integrated assessment model is being developed and tested to explore possible future trends of Canadian agriculture in response to projected global scenarios in the ecological, economic, and social dimensions. Although many studies suggest more favorable growing conditions for Canada due to rising temperature and CO2 concentration, the agricultural sector will likely face challenges of water scarcity...
In this paper we develop a novel approach to model error modelling. There are natural links to others recently developed ideas. However, here we make several key departures, namely (i) we focus on relative errors; (ii) we use a broad class of model error description which includes, inter alia, the earlier idea of stochastic embedding; (iii) we estimate both, the nominal model and undermodelling simultaneously...
The interconnectedness of different actors in the global freight transportation industry has rendered such a system as a large complex system where different sub-systems are interrelated. On such a system, policy-related-exploratory analyses which have predictive capacity are difficult to perform. Although there are many global simulation models for various large complex systems, there is unfortunately...
Most of existing revenue sharing contract models are based on expected utility theory which is a pure rational method and assumed that all decision makers are risk-neutral or loss-neutral. The paper develops a revenue sharing contract model based on prospect theory in which decision makers in the supply chain are all loss-averse. The best order quantity of retailer, effects of retailer's loss-aversion...
In this paper we describe a method of using interval valued survey responses from multiple experts on multiple occassions to produce General Type-2 fuzzy sets. In the method we propose, both the intra- and inter-person variability are modelled, with no loss of information. The resulting sets are completely determined by the data, providing an accurate representation (in terms of being defined solely...
In this paper we provide a novel method to deal with uncertainties in initial value problems based on solving positivity conditions, by means of semidefinite programmes and sum of squares decompositions. More specifically, given a nonlinear dynamical system with uncertainties in initial conditions and parameter values, our method provides enclosures for state trajectories. Due to the fact that we...
The paper presents a comparative analysis between the Multicore and the Grid execution of SWAT hydrological model. We try to emphasize the advantages brought by the Grid infrastructure, especially for large scale applications which require large number of executions and huge data resources. We use as a case study a large scale hydrological model, built using the Arc SWAT program, which covers the...
C2C is an important part of E-commerce, even in the economic crisis it is still rapidly growing. However, compared with the traditional economy, the research on the network economy is still in its infancy. So this paper aims to C2C market to find consumer behavior rules. Differential pricing exists in C2C market, too. But the main reason is the uncertainty of product quality. Because different kinds...
Out-of-equilibrium price dynamics are studied using agent-based computational models. We examine how agents with bounded rationality act in an environment in which they do not know precisely both relative prices and the level of the prices. We model imprecision and uncertainty with fuzzy numbers and use the theory of probabilistic sets as part of the simulation model. Our results explain both positive...
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