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At least 163 records · Page 9

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NASA NTRS1985

LIMS data - Inferred stratospheric distribution of NOx and HOx trace constituents and the calculated odd nitrogen budget

LIMS, SAMS, SBUV and in-situ data have been used to infer species not measured but which are of photochemical interest, e.g., O(3P), O(1D), NO, N2O5, OH, HO2, ClO and HCl. (LIMS = limb infrared monitor of the stratosphere; SAMS = stratospheric and mesospheric sounder; and SBUV = solar backscattered ultraviolet instrument.) Production and loss of odd nitrogen have been calculated and estimates have been made of the odd nitrogen transport due to adiabatically driven circulation derived from LIMS data. Data used from LIMS include O3, NO2, HNO3, H2O and T. CH4 and N2O were taken from SAMS and the UV solar flux from the SBUV instrument. Species were inferred for periods in October, December, March and May. Results for December are discussed. Results indicate: (1) maximum stratospheric odd nitrogen levels of 25 ppbv; (2) evidence of odd nitrogen transport from the mesosphere appearing at 25 km in the wintertime polar latitudes; (3) the polar night build-up of high levels of N2O5 beginning after the autumnal equinox; and (4) the possibility of large downward fluxes of odd nitrogen into the troposphere during the winter at latitudes poleward of 60 degrees.

Callis, L. B.↗

NASA NTRS1986

The Comet Giacobini-Zinner magnetotail: Axial stresses and inferred near-nucleus properties

Utilizing the electron and magnetic field data from the ICE tail traversal of comet Giacobini-Zinner along with the MHD equations, a steady state, stress balance model of the cometary magnetotail was developed, and used to infer important but unmeasured ion properties within the magnetotail at ICE and upstream at the average point along each streamline where cometary ions are picked-up. The derived tailward ion flow speed at ICE is quite constant at approx. -20 to -30 km/sec across the entire tail. The flow velocity, ion temperature, density, and ion source rates upstream from the lobes (current sheet) at the average pick-up locations are approx. -75 km/sec (approx. -12), approx. 4 million K (approx. 100,000), approx. 20 cc (approx. 400), and approx. 15 cu cm/sec. Gradients in the plasma properties between the two regions are quite strong. Implications of inferred plasma properties for the near-nucleus region and for cometary magnetotail formation are examined.

Mccomas, D. J.↗

NASA NTRS1986

The effect of local advection on the inference of soil moisture from thermal infrared radiances

The degree to which the GOES-VISSR infrared data can be used to infer area-averaged soil moisture is explored for a five-day case study period. Chosen variables are transformed and incorporated into a multiple linear regression. The actual observations, rather than a simplified model, are used to determine the relationship between soil moisture and GOES-IR radiance. It is shown that a depletion coefficient of 0.92 produces an index of ground truth which is best correlated with soil moisture as inferred from GOES thermal infrared data. When all individual daily soil estimates during the case study period are averaged at each point and compared to the average observed soil moisture, the data correlate at 0.85. This implies that the algorithm can distinguish at least four categories of soil moisture.

Wetzel, Peter J.↗

NASA NTRS1986

The design and application of a Transportable Inference Engine (TIE1)

A Transportable Inference Engine (TIE1) system has been developed by the author as part of the Interactive Experimenter Planning System (IEPS) task which is involved with developing expert systems in support of the Spacecraft Control Programs Branch at Goddard Space Flight Center in Greenbelt, Maryland. Unlike traditional inference engines, TIE1 is written in the C programming language. In the TIE1 system, knowledge is represented by a hierarchical network of objects which have rule frames. The TIE1 search algorithm uses a set of strategies, including backward chaining, to obtain the values of goals. The application of TIE1 to a spacecraft scheduling problem is described. This application involves the development of a strategies interpreter which uses TIE1 to do constraint checking.

Mclean, David R.↗

NASA NTRS1987

The empirical accuracy of uncertain inference models

Uncertainty is a pervasive feature of the domains in which expert systems are designed to function. Research design to test uncertain inference methods for accuracy and robustness, in accordance with standard engineering practice is reviewed. Several studies were conducted to assess how well various methods perform on problems constructed so that correct answers are known, and to find out what underlying features of a problem cause strong or weak performance. For each method studied, situations were identified in which performance deteriorates dramatically. Over a broad range of problems, some well known methods do only about as well as a simple linear regression model, and often much worse than a simple independence probability model. The results indicate that some commercially available expert system shells should be used with caution, because the uncertain inference models that they implement can yield rather inaccurate results.

Vaughan, David S.↗

NASA NTRS1987

Tectonic motion in the western United States inferred from very long baseline interferometry measurements, 1980-1986

Over six years of mobile very long baseline interferometry (VLBI) baseline measurements between 12 sites in the western U.S. were used to infer their velocities relative to the North American plate. These velocities were found to be generally consistent with those determined from geologic data and contemporaneous satellite laser ranging measurements in the same region. The discrepancy between the largest velocities determined from the VLBI measurements of 40-48 mm/yr and the relative plate velocity of 50-56 mm/yr predicted from plate motion models is found to be consistent with a broadened distribution of interseismic strain from cyclic activity on the San Andreas and subsidiary faults. The VLBI data are best explained by a cumulative rate of strike-slip motion near the plate boundary of approximately 48 mm/yr, although exclusion of competing values of 56 and 41 mm/yr is based upon very few data. The rates of offshore fault slip inferred from this study range from about 15 mm/yr in central California to negligible amounts in the San Francisco region. Finite element calculations of multiple fault strain distributions show good agreement with systematic variations in the distribution of shear strain along the San Andreas system, as revealed by previous geodetic measurements.

Kroger, Peter M.↗

NASA NTRS1986

An Ada inference engine for expert systems

The purpose is to investigate the feasibility of using Ada for rule-based expert systems with real-time performance requirements. This includes exploring the Ada features which give improved performance to expert systems as well as optimizing the tradeoffs or workarounds that the use of Ada may require. A prototype inference engine was built using Ada, and rule firing rates in excess of 500 per second were demonstrated on a single MC68000 processor. The knowledge base uses a directed acyclic graph to represent production lines. The graph allows the use of AND, OR, and NOT logical operators. The inference engine uses a combination of both forward and backward chaining in order to reach goals as quickly as possible. Future efforts will include additional investigation of multiprocessing to improve performance and creating a user interface allowing rule input in an Ada-like syntax. Investigation of multitasking and alternate knowledge base representations will help to analyze some of the performance issues as they relate to larger problems.

Lavallee, David B.↗

NASA NTRS1988

Confidence set inference with a prior quadratic bound

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z = (z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y(0)=(y sub 1(0),...,y sub D(0)) knowledge of the statistical distribution of the random errors in y(0). The data space Y containing y(0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x (e.g., energy or dissipation rate), Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. CSI is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface. Neither the heat flow nor the energy bound is strong enough to permit estimation of B(r) at single points on the CMB, but the heat flow bound permits estimation of uniform averages of B(r) over discs on the CMB, and both bounds permit weighted disc-averages with continous weighting kernels. Both bounds also permit estimation of low-degree Gauss coefficients at the CMB. The heat flow bound resolves them up to degree 8 if the crustal field at satellite altitudes must be treated as a systematic error, but can resolve to degree 11 under the most favorable statistical treatment of the crust. These two limits produce circles of confusion on the CMB with diameters of 25 deg and 19 deg respectively.

Backus, George E.↗

NASA NTRS1989

Hot oxygen geocorona as inferred from neutral exospheric models and mass spectrometer measurements

Summer hot oxygen densities of 10,000-30,000 per cubic cm at 1100 km (or 100,000-300,000 at 550 km) for low to moderate solar activities are inferred from differences between satellite drag and mass-spectrometer-based models. At high solar activities, densities at 925 km from 100,000-400,000 (or 5 x 10 to the 5th to 2 x 10 to the 6th at 550 km) are inferred from a limited number of Dynamics Explorer mass spectrometer measurements. The densities are of the same order as those reported previously from ground-based optical measurements. It is pointed out that a detailed theoretical calculation of the hot oxygen distribution consistent with the cool populations in mass-spectrometer-based models would provide the basis for a more complete interpretation of mass spectrometer data and of high-altitude differences between drag-based and mass-spectrometer-based models. It is concluded that hot oxygen could be providing the major contribution to satellite drag in the summer lower exosphere during low solar activity.

Hedin, A. E.↗

NASA NTRS1989

Inferring surface solar absorption from broadband satellite measurements

An atmospheric solar radiation model and surface albedo models that include wavelength dependence and surface anisotropy are combined to study the possibility of inferring the surface solar absorption from satellite measurements. The model includes ocean, desert, pasture land, savannah, and bog surface categories. Problems associated with converting narrowband measurements to broadband quantities are discussed, suggesting that it would be easier to infer surface solar absorption from broadband measurements directly. The practice of adopting a linear relationship between planetary and surface albedo to estimate surface albedos from satellite measurements is examined, showing that the linear conversion between broadband planetary and surface albedos is strongly dependent on vegetation type. It is suggested that there is a linear slope-offset relationship between surface and surface-atmosphere solar absorption.

Cess, Robert D.↗

NASA NTRS1989

Radial diffusion in the Uranian radiatian belts - Inferences from satellite absorption loss models

Low-energy charged particle (LECP) phase space density profiles available from the Voyager/1986 Uranus encounter are analyzed, using solutions of the time-averaged radial diffusion equation for charged particle transport in a dipolar planetary magnetic field. Profiles for lower-energy protons and electrons are first analyzed to infer radial diffusion rate as a function of L, assuming that satellite absorption is the dominant loss process and local sources for these particles are negligible. Satellite macrosignatures present in the experimentally derived profiles are approximately reproduced in several cases, lending credence to the loss model and indicating that magnetospheric distributed losses are not as rapid as satellite absorption near the minimum satellite L shells for the particles. Diffusion rates and L dependences are found to be similar to those previously inferred in the inner Jovian magnetosphere (Thomsen et al., 1977) and for the inner Saturnian magnetosphere (Hood, 1985). Profiles for higher energy electrons and protons are also analyzed using solutions that allow for the existence of significant particle sources as well as sinks. Possible implications for radial diffusion mechanisms in the Uranian radiation belts are discussed.

Hood, L. L.↗

NASA NTRS1986

The design and application of a Transportable Inference Engine (TIE1)

Mclean, David R.↗

NASA NTRS1990

Topics in inference and decision-making with partial knowledge

Two essential elements needed in the process of inference and decision-making are prior probabilities and likelihood functions. When both of these components are known accurately and precisely, the Bayesian approach provides a consistent and coherent solution to the problems of inference and decision-making. In many situations, however, either one or both of the above components may not be known, or at least may not be known precisely. This problem of partial knowledge about prior probabilities and likelihood functions is addressed. There are at least two ways to cope with this lack of precise knowledge: robust methods, and interval-valued methods. First, ways of modeling imprecision and indeterminacies in prior probabilities and likelihood functions are examined; then how imprecision in the above components carries over to the posterior probabilities is examined. Finally, the problem of decision making with imprecise posterior probabilities and the consequences of such actions are addressed. Application areas where the above problems may occur are in statistical pattern recognition problems, for example, the problem of classification of high-dimensional multispectral remote sensing image data.

Safavian, S. Rasoul↗

NASA NTRS1989

Inference of geophysical parameters from multifrequency polarimetric radar observations and model inversion

In summer 1988 an intensive field experiment was conducted in the vicinity of the Pisgah lava flow in the Mojave Desert. Physical properties such as microtopography, composition, soil moisture, and dielectric constant were measured at five sites representing surfaces with rms heights varying from less than one centimeter to tens of centimeters. In addition, polarimetric radar images at P-band, L-band, and C-band were acquired at three different incidence angles with the NASA/JPL airborne imaging radar polarimeter. Using trihedral corner reflectors deployed in the area prior to imaging, the L- and C-band images were calibrated to provide sigma0 values for each resolution element in the scene. The results of inferring geophysical parameters such as rms surface height and correlation length of the measured surfaces by fitting the observed signatures with those predicted by the small-perturbation model are presented: for smoother surfaces, the rms height values inferred are in good agreement with in situ measurements.

Van Zyl, J. J.↗

NASA NTRS1992

How well is Martian ozone inferred with reflectance spectroscopy?

The Mariner 9 UV spectrometer scanned from 2100 to 3500 Angstroms in one of its two spectral channels every 3 seconds with a spectral resolution of 15 Angstroms and an effective field-of-view of approximately 300 km(exp 2). The only gaseous absorption in the 2000 to 3000 Angstrom region was assumed to come from the Hartley band system of ozone, and therefore the amount of ozone was inferred by fitting this absorption feature with laboratory data of ozone absorption. Mars O3 as inferred from these spectra shows strong seasonal and latitudinal variation, with column abundances ranging from 0.2 microns at equatorial latitudes to 60 microns over the northern winter polar latitudes. The detectability limit of the spectrometer was approximately 3 microns. I use a radiative transfer model based on the discrete ordinate method to calculate synthetic radiance spectra. When typical amounts of dust and cloud are present, significant underestimation of O3 occurs. A factor of 3 times as much O3 is needed to generate the same spectrum for cloudy, dusty atmospheres as for a clear atmosphere. If the scattering properties of Martian clouds and dust were well known, then their appearance would not be a problem, as a model would be capable of retrieving the O3 abundance. However, these properties are not well known, which raises doubts about the effectiveness of the current UV spectroscopy technique used to measure O3. Spatial and temporal variability in temperature and water vapor have been claimed to account for the scatter of the data points. However, water vapor is a small source of odd hydrogen in the winter polar atmosphere, and may not account for most of the variability. Masking by clouds and dust may also account for some of the observed O3 variability, because the nature and opacity of the clouds and dust in the polar hood change dramatically in latitude and even on a day-to-day basis. As the maximum O3 abundance resides near the surface, spacecraft must be able to observe through the entire cloud and dust abundance in order to actually see the total O3 column abundance. If reflectance spectroscopy is used, as on Mariner 9, then the cloud and the airborne dust must be traversed twice; first by the incoming solar flux down to the surface, and then once again upon reflection from the surface out to the spacecraft.

Lindner, Bernhard Lee↗

NASA NTRS1992

An expert system shell for inferring vegetation characteristics

The NASA VEGetation Workbench (VEG) is a knowledge based system that infers vegetation characteristics from reflectance data. The report describes the extensions that have been made to the first generation version of VEG. An interface to a file of unkown cover type data has been constructed. An interface that allows the results of VEG to be written to a file has been implemented. A learning system that learns class descriptions from a data base of historical cover type data and then uses the learned class descriptions to classify an unknown sample has been built. This system has an interface that integrates it into the rest of VEG. The VEG subgoal PROPORTION.GROUND.COVER has been completed and a number of additional techniques that infer the proportion ground cover of a sample have been implemented.

Harrison, P. Ann↗

NASA NTRS1992

Evaluation of fuzzy inference systems using fuzzy least squares

Efforts to develop evaluation methods for fuzzy inference systems which are not based on crisp, quantitative data or processes (i.e., where the phenomenon the system is built to describe or control is inherently fuzzy) are just beginning. This paper suggests that the method of fuzzy least squares can be used to perform such evaluations. Regressing the desired outputs onto the inferred outputs can provide both global and local measures of success. The global measures have some value in an absolute sense, but they are particularly useful when competing solutions (e.g., different numbers of rules, different fuzzy input partitions) are being compared. The local measure described here can be used to identify specific areas of poor fit where special measures (e.g., the use of emphatic or suppressive rules) can be applied. Several examples are discussed which illustrate the applicability of the method as an evaluation tool.

Barone, Joseph M.↗

NASA NTRS1992

Inference in fuzzy rule bases with conflicting evidence

Inference based on fuzzy 'If ... then' rules has played a very important role since when Zadeh proposed the Compositional Rule of Inference and, especially, since the first successful application presented by Mamdani. From the mid-1980's when the 'fuzzy boom' started in Japan, numerous industrial applications appeared, all using simplified techniques because of the high levels of computational complexity. Another feature is that antecedents in the rules are distributed densely in the input space, so the conclusion can be calculated by some weighted combination of the consequents of the matching (fired) rules. The CRI works in the following way: If R is a rule and A* is an observation, the conclusion is computed by B* = R o A* (o stands for the max-min composition). Algorithms implementing this idea directly have an exponential time complexity (maybe the problem is NP-hard) as the rules are relations in X x Y, a k1 x k2 dimensional space, if X is k1, Y is k2 dimensional. The simplified techniques usually decompose the relation into k1 projections in X(sub i) and measure in some way the degree of similarity between observation and antecedent by some parameter of the overlapping. These parameters are aggregated to a single value in (0,1) which is applied as a resulting weight for the given rule. The projections of rules in dimensions Y(sub i) are weighted by these aggregated values and then they are combined in order to obtain a resulting conclusion separately in every dimension. This method is unapplicable with sparse bases as there is no guarantee that an arbitrary observation matches with any of the antecedents. Then, the degree of similarity is 0 and all consequents are weighted by 0. Some considerations for such a situation are summarized in the next sections.

Koczy, Laszlo T.↗