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Showing 1 to 20 of 22 for “"Orthogonal arrays"”.
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Genetic Algorithms, Orthogonal Arrays and Diploid Chromosomes
… of genetic algorithms. The operators exploit the orthogonal arrays of Taguchi method. An operator that uses orthogonal arrays to create initial populations of genetic algorithms was developed. For binary encoded genetic algorithms it was found to be unreliable but is advantageous if it is used in …
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Using orthogonal arrays to train artificial neural networks.
The thesis outlines the use of Orthogonal Arrays for the training of Artificial Neural Networks. Such arrays are popularly used in system optimisation and are known as Taguchi Methods. The chief advantage of the method is that the network can learn quickly. Fast training methods may be used in …
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Cliques in block graphs of designs and orthogonal arrays
… the examination to block graphs of designs and orthogonal arrays. Through a comprehensive analysis of intersecting families within designs, we introduce a ratio between canonically intersecting families and non-canonical ones, demonstrating that almost all intersecting families in designs are …
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The performance of orthogonal arrays with adjoined or unavailable runs
Orthogonal arrays are a class of fractional factorial designs that are optimal according to a range of optimality criteria. This makes it tempting to construct fractional factorial designs by adjoining additional runs to an OA, or by removing runs from an OA, when the number of runs available for …
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On the existence and construction of difference schemes and orthogonal arrays.
… and construction of difference schemes and orthogonal arrays.
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Multi-Reference Pseudo-Random Phase-Encoded Joint Transfrom Correlation
… sequences are shifted to form two dimensional orthogonal arrays referred as m-arrays. The phase mask is used in one step to encode multiple reference images and at the same time eliminate false correlation peaks through power spectrum dispersion. A theoretical model of the implemented JTC is …
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Automated stereophotogrammetry
… eliminate the four-eight connectivity problem of orthogonal arrays, a pseudo-hexagonal array is used at all but the final resolution. Candidate matching points are determined from the oriented edge-vector graph. Candidates will be nodes on the graph, which represent observable features at the gray …
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A case study in application of robust design methods to waterjet processes in overhaul and repair of jet engine components
… on Robust Design methodology. Robust Design uses orthogonal arrays which allow a large number of variables to be studied with a small number of experiments. This requires selection of key input factors that affect the output characteristics of the product. A set of experiments with seven control …
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A Critical Review of Multi-Phase Materials and Optimization Strategies for Additive Printing Technologies
… provided for any which wish to investigate the orthogonal arrays used, or the combinatorial effects resulting in the attributes of the material system final products.
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Contributions to experimental design for quality control
… to the noise factors. Taguchi’s method utilizes orthogonal arrays which allow the investigation of main effects only, under the assumption that interaction effects are negligible. In this paper new techniques are developed to investigate two-factor interactions for 2<sup>t</sup> and 3<sup>t</sup> …
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A graphical comparison of designs for response optimization based on slope estimation
… of outliers. A study of augmenting saturated orthogonal arrays of strength two to detect lack of fit is included as an application of a combined squared bias and variance measure of MSE in slope. A study of the designs recommended for precise slope estimation in their robustness to outliers …
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Model for the design and implementation of reliable and cost effective ISO 9000 quality control systems
… from Design of Experiments (DOE) such as orthogonal arrays and from Taguchi signal-to-noise ratio. Factors, such as frequency of calibration, training of personnel and instruments and levels such as every month/every two months, in-house training/formal training and vernier/micrometer are …
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Applying the Lean Thinking in Health Economics to Improve the Healthcare Delivery
… process model. The next step implements Taguchi Orthogonal Arrays to test the simulation model with scenarios systematically to understand variability’s effects on the Cash Income Collection Procedure process. The results’ significance is validated by statistical analysis. Finally, the research …
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Control, gates, and error suppression with Hamiltonians in quantum computation
… the combinatorial concept of balanced-cycle orthogonal arrays, show how to construct them from classical error-correcting codes, and show how to use them to decouple n-qudit l-local Hamiltonians using protocols of length at most O(l-1 log n). We then present a scheme for implementing …
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Investigating Different Types of Variability in Food Production System
… (to mirror the real production line), Taguchi orthogonal arrays (to generate different scenarios in order to investigate the effect of variability on the simulation model), correlation analysis (to identify the highest variability factors), and the rule based system (to improve food production …
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Inverse Problems In Structural Damage Identification, Structural Optimization, And Optical Medical Imaging Using Artificial Neural Networks
… excessively impairing the integrity of the data. Orthogonal Arrays were also used to select a smaller number of training sets that can efficiently represent the given system.
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Row-column factorial designs and mutually orthogonal frequency rectangles
… has strength t if each row and column is an orthogonal array of strength t. We denote such a design by Iₖ (m,n,q,t). A frequency rectangle of type FR(m,n;q) is an m × n array based on a symbol set S of size q, such that each element of S appears exactly n/q times in each row and m/q times in …
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Computational intelligence for fault diagnosis in gearbox systems
… proposed: automated system based on Taguchi's orthogonal arrays and stepwise system using (Linear Regression (LR), Fuzzy Rule Based System (FRBS) and Principal Component Analysis (PCA), techniques ). To evaluate both strategies, four different classification models are employed using supervised …
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