The k-nearest neighbor (k-NN) technique is a non-parametric technique that can be used to make predictions of discrete (class-type) as well as continuous variables. The k-NN technique and many of its derivatives belong to the group of .lazy learning algorithms.. It is lazy, as it passively stores the development data set until the time of application; all calculations are performed only when estimations need to be generated.
The purpose of the SolarCalQ Version 1 JAVA model is to simulate the spectral quality of incident solar radiation for any location on the globe, down to one minute time steps.
Spreadsheet from the paper entitled: On the Use of Linearized Langmuir Equations by C.H. Bolster and G.M. Hornberger, Soil Science Society of America Journal, 2007, 71(6): 1796-1806.
Estimates water retention, saturated and unsaturated hydraulic conductivity from basic soil data (requires 32-bit Windows).
Data from: Effect of macronutrients and fiber on postprandial glycemic responses and meal glycemic index and glycemic load value determinations
Effect of macronutrients and fiber on postprandial glycemic responses and meal glycemic index and glycemic load value determinations
Background: The potential confounding effect of different amounts and proportions of macronutrients across eating patterns on meal or dietary glycemic index (GI) and glycemic load (GL) value…
Data from: Trends and sensitivities of low streamflow extremes to discharge timing and magnitude in Pacific Northwest mountain streams
The relative influences of total precipitation and air temperature on the annual low streamflow extremes are quantified from 42 Pacific Northwest stream gauges from 1948 to 2013 using mean annual streamflow as a proxy for precipitation amount effects and streamflow center of timing as a proxy for temperature effects on low flow metrics.
SWIFT (Small Watershed Nutrient Forecasting Tool) is a web-based tool that allows the rapid estimation of sediment and nutrient loads from small watersheds for a given ecoregion in the US.
Data from: Comparative farm-gate life cycle assessment of oilseed feedstocks in the Northern Great plains
This MS Word document contains the oilseed feedstock farm-gate model inventories, results, and uncertainty analyses for the Northern Great Plains discussed in Moeller et. al 2017. Analysis was conducted using IPCC GHG standardized emissions. Methodology is detailed in the associated publication (doi: 10.1007/s41247-017-0030-3). The supplementary information contains the names of the ecoinvent inventories; oilseed yield, seeding rates, and fertilization rates per USDA crop management zone (CMZ); climate change, freshwater eutrophication, and marine eutrophication percent contributions ReCiPe results per CMZ; Monte Carlo uncertainty results per CMZ; and farm-gate energy balance analysis results per CMZ.