98 research outputs found

    Mathematical Optimization Techniques

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    The papers collected in this volume were presented at the Symposium on Mathematical Optimization Techniques held in the Santa Monica Civic Auditorium, Santa Monica, California, on October 18-20, 1960. The objective of the symposium was to bring together, for the purpose of mutual education, mathematicians, scientists, and engineers interested in modern optimization techniques. Some 250 persons attended. The techniques discussed included recent developments in linear, integer, convex, and dynamic programming as well as the variational processes surrounding optimal guidance, flight trajectories, statistical decisions, structural configurations, and adaptive control systems. The symposium was sponsored jointly by the University of California, with assistance from the National Science Foundation, the Office of Naval Research, the National Aeronautics and Space Administration, and The RAND Corporation, through Air Force Project RAND

    The determination of regression relationships using stepwise regression techniques

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    Stepwise regression routines are rapidly becoming a standard leature of large-scale computer statistical packages. They provide, in particular, a certain degree 01 flexibility in the selection of 'optimum' regression equations when one has available a large set of potential regressor variables. A major problem in the use of such routines is the determination of appropriate 'cut-off' criteria for terminating the procedures. There is a tendency in practice for standard F or t-statistics to be calculated at each step 01 the procedure, and for this value to be compared with conventional critical values. In this thesis an attempt has been made to provide a more satisfactory rationale for (single-step) stepwise procedures. The approach taken is to assume that a 'true' model exists (the regressors in which are a subset of those available) and to investigate the distribution of statistics which, at each stage, seem relevant to the termination decision. This leads to the consideration of alternative tests at each step to those usually employed. In the presence of considerable analytical complexity a simulation approach is used to obtain a comparison of the relative performances of various procedures. This study encompasses the use of forward, backward and mixed forward/backward procedures in both orthogonal and non-orthogonal set-ups. Procedures are evaluated both in terms of the 'closeness' of the finally selected model to the true one, and also in terms of prediction mean square-error. The study ends with an investigation into the usefulness of stepwise regression in identifying and estimating stochastic regression relationships of the type encountered in the analysis of time series

    Bulletin of the San Diego College for Women 1968-1969

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    135 pages : illustrations, photographs ; 22.5 cmhttps://digital.sandiego.edu/coursecatalogs-cfw/1015/thumbnail.jp

    The determination of regression relationships using stepwise regression techniques

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    Stepwise regression routines are rapidly becoming a standard leature of large-scale computer statistical packages. They provide, in particular, a certain degree 01 flexibility in the selection of 'optimum' regression equations when one has available a large set of potential regressor variables. A major problem in the use of such routines is the determination of appropriate 'cut-off' criteria for terminating the procedures. There is a tendency in practice for standard F or t-statistics to be calculated at each step 01 the procedure, and for this value to be compared with conventional critical values. In this thesis an attempt has been made to provide a more satisfactory rationale for (single-step) stepwise procedures. The approach taken is to assume that a 'true' model exists (the regressors in which are a subset of those available) and to investigate the distribution of statistics which, at each stage, seem relevant to the termination decision. This leads to the consideration of alternative tests at each step to those usually employed. In the presence of considerable analytical complexity a simulation approach is used to obtain a comparison of the relative performances of various procedures. This study encompasses the use of forward, backward and mixed forward/backward procedures in both orthogonal and non-orthogonal set-ups. Procedures are evaluated both in terms of the 'closeness' of the finally selected model to the true one, and also in terms of prediction mean square-error. The study ends with an investigation into the usefulness of stepwise regression in identifying and estimating stochastic regression relationships of the type encountered in the analysis of time series

    Integrating the key approaches of neural networks

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    The thesis is written in chapter form. Chapter 1 describes some of the history of neural networks and its place in the field of artificial intelligence. It indicates the biological basis from which neural network approximation are made. Chapter 2 describes the properties of neural networks and their uses. It introduces the concepts of training and learning. Chapters 3, 4, 5 and 6 show the perceptron and adaline in feedforward and recurrent networks particular reference is made to regression substitution by "group method data handling. Networks are chosen that explain the application of neural networks in classification, association, optimization and self organization. Chapter 7 addresses the subject of practical inputs to neural networks. Chapter 8 reviews some interesting recent developments. Chapter 9 reviews some ideas on the future technology for neural networks. Chapter 10 gives a listing of some neural network types and their uses. Appendix A gives some of the ideas used in portfolio selection for the Johannesburg Stock Exchange.ComputingM. Sc. (Operations Research

    Characterisation of a multispectral digital camera System for quantitatively comparing complex animal Patterns in natural environments.

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    Animal coloration can be described by complex colour patterns including elements of varying size, shape and spectral profile which commonly reflect energy outside the spectral range visible for humans. Whilst spectrometry is currently employed for the quantitative study of animal coloration, it is limited on its ability to describe the spatial characteristics of spectral differences in patterns. Digital photography has recently been used as a tool for measuring spatial and spectral properties of patterns based on quantitative analysis of linear camera responses recovered after characterising the device. However current applications of digital imaging for studying animal coloration are limited to image recording within a laboratory environment considering controlled lighting conditions. Here a refined methodology for camera characterisation is developed permitting the recording of images under different illumination conditions typical of natural environments. The characterised camera system thus allows recording images from reflected ultraviolet and visible radiation resulting in a multispectral digital camera system. Furthermore a standardised imaging processing workflow was developed based on specific characteristics of the camera thus making possible an objective comparison from images. An application of the characterised camera system is exemplified in the study of animal colour patterns adapted for camouflage using as a model two Australian, endemic lizard species. The interaction between the spectral and spatial properties of the respective lizards produces complex patterns than cannot be interpreted by spectrophotometry alone. Data obtained from analysis of images recorded with the characterised camera system in the visible and near-ultraviolet region of the spectrum reveal significative differences between sex and species and a possible interaction between sex and species, suggesting microhabitat specialisation to different backgrounds

    Electron scattering from an almost free neutron in deuterium

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    The Barely off-Shell Nucleon Structure (BoNuS) experiment measured electron scattering from neutrons bound in deuterium nuclei at Jefferson Lab\u27s Hall B with the intent of obtaining the ratio Fn2/Fp2 at high Bjorken x. The Fn2 structure function is difficult to obtain due to nature\u27s lack of a free neutron target. Previous experiments have measured inclusive scattering from atomic nuclei, but extracting Fn2 from these data requires knowledge of inclusive scattering from the proton and corrections for nucleon binding and Fermi motion. In BoNuS we restrict our analysis to neutron scattering events tagged by a backward-going low-energy recoil proton. This selects loosely bound neutrons that are nearly on their mass-shell and have few final state interactions with the recoil proton. The recoil protons were detected in a Radial Time Projection Chamber (RTPC) using gas electron multipliers (GEMs) in a cylindrical geometry around the target. The production data were taken at three beam energies: 2.140 GeV, 4.223 GeV and 5.262 GeV with an additional set of calibration data taken at 1.099 GeV. The kinematic coverage includes the invariant mass, W, from the quasi-elastic peak up to 3.0 GeV and momentum transfer, Q 2, from 0.2 GeV2 up to approximately 3.0 GeV 2. The final experimental observations presented here are the tagged/untagged cross section ratios, corrected for a number of physical processes and backgrounds. The ratio enables us to ignore many complications arising from a typical absolute cross section measurement. An extraction of Fn2/Fp2 for x up to 0.75 is made and compared with previous data These data are important because they can provide a model independent measurement of neutron structure
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