A pure plant community with a simple structure of the arrangement of individuals is considered. The stochastic model represented by a Markov random field (MRF), describes a productivity property of the plant community...
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This work aims to evaluate different error estimations of the shape and scale parameters of the Weibull probability density function of wind speed measured at the Fujairah site over a 1-year period. This study estimat...
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This work aims to evaluate different error estimations of the shape and scale parameters of the Weibull probability density function of wind speed measured at the Fujairah site over a 1-year period. This study estimates trends in the variation of Weibull parameters using moving averages and Markov series methods. The focus is on the scale and shape factors, which are evaluated by mapping monthly mean wind speeds into a Weibull probability distribution function. Due to the imprecise nature of these factors, multiple data simulations are used to predict Weibull factors based on data measuring interpolations. A procedural algorithm is proposed to select the overall best forecast based on several estimation methods that evaluate raised prediction errors. A probabilistic analysis is followed to predict future wind speed and wind energy based on variations in the scale and shape factors. This study focuses on the scale factor variation as it is found to be more dominant than the Weibull shape factor. The forecasted wind speed is checked with the measured value in future months and found to be within trend values. The results suggest that the proposed algorithm provides an accurate and reliable method for predicting future wind speed and energy output.
Accelerated stormwater runoff creates environmental problems in many urban communities. Methods of reducing runoff for individual residences are available, but are often recommended without sufficient analysis. For ex...
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Accelerated stormwater runoff creates environmental problems in many urban communities. Methods of reducing runoff for individual residences are available, but are often recommended without sufficient analysis. For example, many states provide guidance on creating rain gardens, but few include information about how well rain gardens actually work. An analysis algorithm is presented to evaluate rain garden effectiveness at reducing stormwater runoff by promoting infiltration, evaporation, and evapotranspiration. Example simulations are presented based on an Ohio meteorological record. Results indicate that garden effectiveness is dominated by infiltration. Evaporation and evapotranspiration play minor roles in reducing runoff. Results also indicate that current rain garden design recommendations are often too conservative. Even for low permeability soils, rain gardens can be more effective than currently assumed. Common depth recommendations are reasonable, but area recommendations are also conservative. Residential rain gardens have a much better chance of reducing stormwater runoff than rain barrels. Their design recommendations should be revised to concentrate less on garden flora and more on the properties that promote desirable hydrologic performance. (C) 2015 American Society of Civil Engineers.
This work is to study the dynamic characteristics of an oil turbine (OT) in the lubricating system of large-scale steam turbines. The configuration and the functions of OT are introduced. The mathematical models are a...
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This work is to study the dynamic characteristics of an oil turbine (OT) in the lubricating system of large-scale steam turbines. The configuration and the functions of OT are introduced. The mathematical models are accordingly explored. In addition, the experiment results are predicted and compared with the theoretical prediction. Finally, the dynamic characteristics in the start-up procedure are simulated and analyzed. The agreement between the numerical results and the experiment observations is in general satisfactory. It shows that the numerical simulation approach is reliable, and could be applied into the dynamic characteristics research and optimization of other complicated fluid systems as hydropower station.
Continuous sampling plans are used to ensure a high level of quality for items produced in long-run contexts. The basic idea of these plans is to alternate between 100% inspection and a reduced rate of inspection freq...
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Continuous sampling plans are used to ensure a high level of quality for items produced in long-run contexts. The basic idea of these plans is to alternate between 100% inspection and a reduced rate of inspection frequency. Any inspected item that is found to be defective is replaced with a non-defective item. Because not all items are inspected, some defective items will escape to the customer. Analytical formulas have been developed that measure both the customer perceived quality and also the level of inspection effort. The analysis of continuous sampling plans does not apply to short-run contexts, where only a finite-size batch of items is to be produced. In this paper, a simulation algorithm is designed and implemented to analyze the customer perceived quality and the level of inspection effort for short-run contexts. A parameter representing the effectiveness of the test used during inspection is introduced to the analysis, and an analytical approximation is discussed. An application of the simulation algorithm that helped answer questions for the U.S. Navy is discussed.
We derive a stochastic representation for the probability distribution on the positive orthant (0, infinity)(d) whose association between components is minimal among all probability laws with lp-norm symmetric surviva...
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We derive a stochastic representation for the probability distribution on the positive orthant (0, infinity)(d) whose association between components is minimal among all probability laws with lp-norm symmetric survival functions. It is given by a transformation of a uniform distribution on the standard unit simplex that is multiplied with an independent finite mixture of certain beta distributions and an additional atom at unity. On the one hand, this implies an efficient simulation algorithm for arbitrary probability laws with l(p)-norm symmetric survival function. On the other hand, this result is leveraged to construct an exact simulation algorithm for max-infinitely divisible probability distributions on the positive orthant whose exponent measure has l(p)-norm symmetric survival function. Both applications generalize existing results for the case p = 1 to the case of arbitrary p >= 1. (C) 2021 Elsevier Inc. All rights reserved.
PurposeVariability in contouring contributes to large variations in radiation therapy planning and treatment outcomes. The development and testing of tools to automatically detect contouring errors require a source of...
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PurposeVariability in contouring contributes to large variations in radiation therapy planning and treatment outcomes. The development and testing of tools to automatically detect contouring errors require a source of contours that includes well-understood and realistic errors. The purpose of this work was to develop a simulation algorithm that intentionally injects errors of varying magnitudes into clinically accepted contours and produces realistic contours with different levels of variability. MethodsWe used a dataset of CT scans from 14 prostate cancer patients with clinician-drawn contours of the regions of interest (ROI) of the prostate, bladder, and rectum. Using our newly developed Parametric Delineation Uncertainties Contouring (PDUC) model, we automatically generated alternative, realistic contours. The PDUC model consists of the contrast-based DU generator and a 3D smoothing layer. The DU generator transforms contours (deformation, contraction, and/or expansion) as a function of image contrast. The generated contours undergo 3D smoothing to obtain a realistic look. After model building, the first batch of auto-generated contours was reviewed. Editing feedback from the reviews was then used in a filtering model for the auto-selection of clinically acceptable (minor-editing) DU contours. ResultsOverall, C values of 5 and 50 consistently produced high proportions of minor-editing contours across all ROI compared to the other C values (0.936 +/-$ \pm \;$0.111 and 0.552 +/-$ \pm \;$0.228, respectively). The model performed best on the bladder, which had the highest proportion of minor-editing contours (0.606) of the three ROI. In addition, the classification AUC for the filtering model across all three ROI is 0.724 +/-$ \pm \;$0.109. DiscussionThe proposed methodology and subsequent results are promising and could have a great impact on treatment planning by generating mathematically simulated alternative structures that are clinically relevant and realistic e
DEVS is a sound Modeling and simulation (M&S) framework that describes a model in a modular and hierarchical way. It comes along with an abstract simulation algorithm which defines its operational semantics. Many ...
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DEVS is a sound Modeling and simulation (M&S) framework that describes a model in a modular and hierarchical way. It comes along with an abstract simulation algorithm which defines its operational semantics. Many variants of such an algorithm have been proposed by DEVS researchers. Yet, the proper interpretation and analysis of the computational complexity of such approaches have not been systematically addressed and defined. As systems become larger and more complex, the efficiency of the DEVS simulation algorithms in terms of time complexity measure becomes a major issue. Therefore, it is necessary to devise a method for computing this complexity. This paper proposes a generic method to address such an issue, taking advantage of the recursion embedded in the triggered-by-message principle of the DEVS simulation protocol. The applicability of the method is shown through the complexity analysis of various DEVS simulation algorithms.
In this paper, we use the variational iteration method (VIM) to construct approximate solutions for the general nth-order integro-differential equations. We show that his method can be effectively and easily used to s...
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In this paper, we use the variational iteration method (VIM) to construct approximate solutions for the general nth-order integro-differential equations. We show that his method can be effectively and easily used to solve some classes of linear and nonlinear Volterra integro-differential equations. Finally, some numerical examples with exact solutions are given.
We investigate the problem of computing the reachable blocks of the simulation equivalence and its natural counterpart for the simulation preorder, referred to as the reachable simulation problem. Through a theoretica...
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We investigate the problem of computing the reachable blocks of the simulation equivalence and its natural counterpart for the simulation preorder, referred to as the reachable simulation problem. Through a theoretical investigation of this problem, we unveil a sharp contrast with the already settled case of bisimulation equivalence. Then, we design algorithms to solve the reachable simulation problem by leveraging the idea of interleaving reachability and simulation computation while possibly avoiding the computation of all the reachable states or the whole simulation preorder. Specifically, we propose algorithms achieving different guarantees on the precision of the output, and a symbolic algorithm that operates on state partitions and relations between their blocks, which is particularly well-suited for processing infinite-state systems.
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