Books on the topic 'Predicting model'

Ferguson, Dennis E. Predicting regeneration establishment with the prognosis model. [Ogden, Utah?]: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1993.

Ferguson, Dennis E. Predicting regeneration establishment with the prognosis model. [Ogden, Utah?]: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1993.

Ferguson, Dennis E. Predicting regeneration establishment with the prognosis model. [Ogden, Utah?]: U.S. Dept. of Agriculture, Forest Service, Intermountain Research Station, 1993.

United States. National Aeronautics and Space Administration., ed. Development of a model for predicting NASA/MSFC project success. [Huntsville, Ala.]: Dept. of Industrial and Systems Engineering, University of Alabama in Huntsville, 1990.

Ward, S. C. Validation of a CFD model for predicting film cooling performance. Washington, D. C: American Institute of Aeronautics and Astronautics, 1993.

Weber, Randal S. A model for predicting transfusion requirements in head and neck surgery. St. Louis, MO: American Laryngological, Rhinological and Otological Society, 1995.

Maurice, Clark Robert, and Risk Reduction Engineering Laboratory (U.S.), eds. Predicting the inactivation of giardia lamblia: A mathematical and statistical model. Cincinnati, Ohio: U.S. Environmental Protection Agency, Risk Reduction Engineering Laboratory, 1990.

Eskridge, Robert E. ROADWAY--a numerical model for predicting air pollutants near highways: User's guide. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1987.

Eskridge, Robert E. ROADWAY--a numerical model for predicting air pollutants near highways: User's guide. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1987.

Gentry, James A. Predicting industrial bond ratings with a probit model and funds flow components. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1985.

Eskridge, Robert E. ROADWAY--a numerical model for predicting air pollutants near highways: User's guide. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1987.

S, Bhown A., and Hazardous Waste Engineering Research Laboratory, eds. Predicting the effectiveness of chemical-protective clothing: Model and test method development. Cincinnati, OH: U.S. Environmental Protection Agency, Hazardous Waste Engineering Research Laboratory, 1986.

Eskridge, Robert E. ROADWAY--a numerical model for predicting air pollutants near highways: User's guide. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1987.

C, Yang Jiann, Kashiwagi Takashi, and National Institute of Standards and Technology (U.S.), eds. A global model for predicting the burning rates of liquid pool fires. Gaithersburg, MD: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

Eskridge, Robert E. ROADWAY--a numerical model for predicting air pollutants near highways: User's guide. Research Triangle Park, NC: U.S. Environmental Protection Agency, Atmospheric Sciences Research Laboratory, 1987.

Bos, M. J. Critical appraisal of the McDonnell Douglas closure model for predicting fatigue crack growth. Melbourne, Australia: Aeronautical Research Laboratory, 1991.

Davidson, Lars. Predicting stall of a two-dimensional airfoil using an algebraic Reynolds stress model. Toulouse, France: CERFACS, 1991.

W, Shoesmith D., and Atomic Energy of Canada Limited., eds. A Model for predicting the lifetimes of Grade-2 titanium nuclear waste containers. Pinawa, Manitoba: AECL, 1995.

Keane, Robert E. Predicting biogeochemical ecosystem processes in the Columbia River Basin using the BGC model. [Missoula, Mont.?]: [Intermountain Research Station, Fire Sciences Laboratory], 1996.

W, Weaver James, and Robert S. Kerr Environmental Research Laboratory., eds. Predicting subsurface contaminant transport and transformation: Considerations for model selection and field validation. Ada, OK: Robert S. Kerr Environmental Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 1989.

W, Weaver James, and Robert S. Kerr Environmental Research Laboratory, eds. Predicting subsurface contaminant transport and transformation: Considerations for model selection and field validation. Ada, OK: Robert S. Kerr Environmental Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, 1989.

Okoruwa, Ambrose Asonarenemen. Predicting patronization rates for urban retail centers: An extension of the poisson gravity model. Ann Arbor, M.I: University Microfilms International, 1986.

United States. Forest Service. Southern Region. and United States. Forest Pest Management., eds. TFS spot growth: A model for predicting the spread of southern pine beetle infestations. Atlanta, Ga: U.S. Dept. of Agriculture, Forest Service, Southern Region, 1985.

Predicting archaeological sites from environmental variables: A mathematical model for the Sierra Nevada foothills. Oxford: BAR, 1987.

United States. Forest Service. Southern Region and United States. Forest Pest Management, eds. TFS spot growth: A model for predicting the spread of southern pine beetle infestations. Atlanta, Ga: U.S. Dept. of Agriculture, Forest Service, Southern Region, 1985.

Parlia, Sean. Ion-Pair Conductivity Model and Its Application for Predicting Conductivity in Non-Polar Systems. [New York, N.Y.?]: [publisher not identified], 2020.

E, Nelson E., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Engineering., and Modeling and Computing Services (Firm), eds. Improved model for predicting J-R curves from Charpy data: Phase I final report. Washington, DC: Division of Engineering, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1989.

E, Nelson E., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Engineering., and Modeling and Computing Services (Firm), eds. Improved model for predicting J-R curves from Charpy data: Phase I final report. Washington, DC: Division of Engineering, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1989.

Bonin, Rejean. A Canadian population change prediction model: Predicting population change in Canada between 1996 and 2001 using 1996 socio-economic indicators. Sudbury, Ont: [s.n.], 2003.

Emile, Coleman W., and United States. Environmental Protection Agency, eds. Ozonation/post-chlorination of humic acid: A model for predicting drinking water disinfection by-products. [Washington, D.C: U.S. Environmental Protection Agency, 1992.

Emile, Coleman W., and United States. Environmental Protection Agency, eds. Ozonation/post-chlorination of humic acid: A model for predicting drinking water disinfection by-products. [Washington, D.C: U.S. Environmental Protection Agency, 1992.

Emile, Coleman W., and United States. Environmental Protection Agency., eds. Ozonation/post-chlorination of humic acid: A model for predicting drinking water disinfection by-products. [Washington, D.C: U.S. Environmental Protection Agency, 1992.

Hughes, Garrett A. Key algorithms used in GR02: A computer simulation model for predicting tree and stand growth. [Broomall, Pa.]: U.S. Dept. of Agriculture, Forest Service, Northeastern Forest Experiment Station, 1985.

Emile, Coleman W., and United States. Environmental Protection Agency, eds. Ozonation/post-chlorination of humic acid: A model for predicting drinking water disinfection by-products. [Washington, D.C: U.S. Environmental Protection Agency, 1992.

Emile, Coleman W., and United States. Environmental Protection Agency, eds. Ozonation/post-chlorination of humic acid: A model for predicting drinking water disinfection by-products. [Washington, D.C: U.S. Environmental Protection Agency, 1992.

Lander, Linda M. A conceptual model of incentive values for explaining and predicting preference for selected physical activities. Eugene: Microform Publications, College of Human Development and Performance, University of Oregon, 1985.

McGrattan, Ellen R. Predicting the effects of Federal Reserve policy in a sticky-price model: An analytical approach. [Minneapolis, Minn.]: Federal Reserve Bank of Minneapolis, 1999.

Holloway, Christopher L. A simplified model for predicting the power delay profile characteristics of an indoor propagation channel. [Washington, DC]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1998.

Pilgram, Tom. Predicting archaeological sites from environmental variables: A mathematical model for the Sierra Nevada foothills, California. Oxford, England: B.A.R., 1987.

Miller, Dean R. Analytical model for predicting emergency shutdown of a two-blade d horizontal axis wind turbine. [Washington, DC: U.S. Dept. Energy, Wind Energy Technology Division, 1985.

1945-, Bennett Robert M., and Langley Research Center, eds. Using transonic small disturbance theory for predicting the aeroelastic stability of a flexible wind-tunnel model. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1990.

Karvonen, Tuomo. A model for predicting the effect of drainage on soil moisture, soil temperature and crop yield. Otaniemi, Finland: Helsinki University of Technology, Laboratory of Hydrology and Water Resources Engineering, 1988.

Pasmore, Joe. A computer forecasting model for predicting requirements for beds in a secure custody juvenile corrections institutions. Phillip, ACT, Australia: Australian Institute of Criminology, 1989.

Laigna, K. J. Mathematical model for predicting the athmospheric [sic] pollution state in the areas of local and regional scale. Tallin: Estonian Scientific Research Institute for Scientific-Technical Information and Technical-Economic Research, 1990.

Barajas, Rita Gabriela. The Family Process Model: Predicting Youth Behavior Problems in Mexican American, African American, and European American Families. [New York, N.Y.?]: [publisher not identified], 2011.

Ontario. Ministry of Municipal Affairs. Lakeshore Capacity Study: Integration : a simulation model for predicting the impact of lakeshore cottages on the environment. Toronto, Ont: Ontario Ministry of Municipal Affairs, 1986.

Murray, Dryer, and Space Environment Laboratory, eds. The interplanetary shock propagation model: A model for predicting solar-flare-caused geomagnetic storms, based on the 2 1/2 D, MHD numerical simulation results from the interplanetary global model (2D IGM). Boulder, Colo: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Laboratory ; Springfield, VA, 1995.

Murray, Dryer, and Space Environment Laboratory, eds. The interplanetary shock propagation model: A model for predicting solar-flare-caused geomagnetic storms, based on the 2 1/2 D, MHD numerical simulation results from the interplanetary global model (2D IGM). Boulder, Colo: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Laboratory ; Springfield, VA, 1995.

Murray, Dryer, and Space Environment Laboratory, eds. The interplanetary shock propagation model: A model for predicting solar-flare-caused geomagnetic storms, based on the 2 1/2 D, MHD numerical simulation results from the interplanetary global model (2D IGM). Boulder, Colo: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Laboratory ; Springfield, VA, 1995.

S, Kumar. Investigation of the feasibility of using the MESOPUFF II model for predicting acid deposition in Maryland: Final report. [Annapolis, MD]: PPRP, 1987.