Here flexible algorithms are used for teaching purposes in a course for beginners. flexible algorithms have a simple notation and are multifaceted. They may be executed in a variety of orders, sequential or parallel, ...
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ISBN:
(纸本)9781424408580
Here flexible algorithms are used for teaching purposes in a course for beginners. flexible algorithms have a simple notation and are multifaceted. They may be executed in a variety of orders, sequential or parallel, producing results independent of the execution order. They may be converted to sequential algorithms and to hardware block diagrams. They may also be used for giving an overall description of systems. The educational approach is as follows. Reading and executing flexible algorithms - understanding their behaviours. Acquiring an early awareness of parallelism. Converting flexible algorithms to hardware block diagrams (arouse curiosity). Converting flexible algorithms to sequential algorithms (tail recursion). Deeper understanding of flexible algorithms computational induction. Changes to flexible algorithms. Writing flexible algorithms. Overall description of systems using flexible algorithms (arouse curiosity). The "core" algorithmic notation is based on functions with "IN", "OUT" but no "INOUT" parameters, and conditional statements. As in mathematics, variables, parameters, etc., receive a value once only. Blocks, loops, etc. (including nested forms) are not part of the "core" language but viewed as abbreviations for certain compound forms in the "core" language. Our notation has an iterative style and includes a once only assignment statement. This material is suitable for beginning undergraduate students of computing science and for suitable students in their final year of secondary school.
Oil consumption plays a vital role in socio-economic development of most countries. This study presents a flexible fuzzy regression algorithm for forecasting oil consumption based on standard economic indicators. The ...
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Oil consumption plays a vital role in socio-economic development of most countries. This study presents a flexible fuzzy regression algorithm for forecasting oil consumption based on standard economic indicators. The standard indicators are annual population, cost of crude oil import, gross domestic production (GDP) and annual oil production in the last period. The proposed algorithm uses analysis of variance (ANOVA) to select either fuzzy regression or conventional regression for future demand estimation. The significance of the proposed algorithm is three fold. First, it is flexible and identifies the best model based on the results of ANOVA and minimum absolute percentage error (MAPE), whereas previous studies consider the best fitted fuzzy regression model based on MAPE or other relative error results. Second, the proposed model may identify conventional regression as the best model for future oil consumption forecasting because of its dynamic structure, whereas previous studies assume that fuzzy regression always provide the best solutions and estimation. Third, it utilizes the most standard independent variables for the regression models. To show the applicability and superiority of the proposed flexible fuzzy regression algorithm the data for oil consumption in Canada, United States, Japan and Australia from 1990 to 2005 are used. The results show that the flexible algorithm provides accurate solution for oil consumption estimation problem. The algorithm may be used by policy makers to accurately foresee the behavior of oil consumption in various regions. (C) 2009 Elsevier Ltd. All rights reserved.
Databases may exhibit many forms of incompleteness. This paper explores methods for overcoming incompleteness in the form of missing tuples. Specifically, algorithms are investigated for replacing a relation that is k...
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Databases may exhibit many forms of incompleteness. This paper explores methods for overcoming incompleteness in the form of missing tuples. Specifically, algorithms are investigated for replacing a relation that is known to be incomplete with a superset. Of particular interest are algorithms that make available at any time a current approximation and with the property that the approximate solution improves monotonically with computing time. Although this paper concentrates on rule matching in rule-based systems, application of these and similar methods to problems of knowledge discovery in incomplete databases is also discussed.
In this study, the reliability-based design optimization (RBDO) of rotating functionally graded cylindrical shells (FGCSs) subjected to temperature dependent probabilistic frequency constraints is investigated. The un...
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In this study, the reliability-based design optimization (RBDO) of rotating functionally graded cylindrical shells (FGCSs) subjected to temperature dependent probabilistic frequency constraints is investigated. The uncertain parameters such as FG material properties and the shell thermo-mechanical loads are considered as random variable in RBDO. To decrease model uncertainty, the effect of initial thermal stresses are efficiently included in elasticity-based vibration equations of the shell and the powerful differential quadrature method (DQM) is employed to accurately determine the shell frequency parameters. An efficient RBDO framework based on the hybrid weighted average simulation method (WASM) and DQM together with the particle swarm optimization (PSO) method is then presented for design optimization of the FGCSs. A key feature of proposed hybrid DQ-WASM-PSO is that only one simulation run is required for WASM during entire optimization process of the FGCS, even if the distribution type of input variables and/or the system target reliability level be changed. The influence of temperature rise, temperature-dependence of FGM properties, annular velocity, PDFs of the random variables, and convection heat transfer coefficient of the shell inside fluid on the RBDO results are carried out. Parametric study indicates that exact evaluation of the initial thermal stresses, temperature dependence of the FGM properties and convection heat transfer coefficient have considerable effect on optimization results. (C) 2017 Elsevier Masson SAS. All rights reserved.
The authors present a new method for determining the optical properties of arbitrary refractive index elliptical core fibres. The method applies the elliptic cylindrical coordinate system to Maxwell's equations an...
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The authors present a new method for determining the optical properties of arbitrary refractive index elliptical core fibres. The method applies the elliptic cylindrical coordinate system to Maxwell's equations and appropriately, using Fourier Transforms, operated on an elliptical core optical fibre waveguide, derives a flexible algorithm, which can be used to determine the optical properties of elliptical fibre waveguides. By dividing the fibre into a series of uniform consecutive thin dielectric layers transversely across the elliptical cross section with suitable transforming functions representing voltage and current themselves based on the electromagnetic field components, leads to transverse transmission line equations. The resonance frequencies of the cascaded matrices determine the mode propagation constants. The analysis leads to a numerical algorithm for calculating the exact modes of propagation constants. The method is analytically exact and computationally accurate, leading to algorithmic implementation, without making use of Mathieu functions which are solutions for step index waveguide. The advantage of this work is also the fact that it can be applied to arbitrary refractive index profiles. They present results of modal $\bar b - V$b over bar -V diagrams for various fibre ellipticities and also apply this method to determine the birefringence of graded index profile fibres and mode cut-off frequencies.
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