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The cascade correlation neural network was used to predict the two-year peak discharge (Q2) for major regional river basins of the continental United States (US). Watersheds ranged in size by four orders of magnitude. Results of the neural network predictions ranged from correlations of 0.73 for 104 test data in the Souris-Red Rainy river basin to 0.95 for 141 test data in California. These results are improvements over previous multilinear regressions involving more variables that showed correlations ranging from 0.26 to 0.94. Results are presented for neural networks trained and tested on drainage area, average annual precipitation, and mean basin elevation. A neural network trained on regional scale data in the...
In this study we describe the design and application of an automated classification system that utilizes artificial intelligence to corroborate the finding that Gunnison's prairie dogs have different alarm calls for different species of predators. This corroboration is strong because it utilizes an entirely different analysis technique than that used in the original research by Slobodchikoff et al. [Slobodchikoff, C.N., Fischer, C., Shapiro, J., 1986. Predator-specific alarm calls of prairie dogs. Am. Zool. 26, 557] or in subsequent study done by Slobodchikoff et al. [Slobodchikoff, C.N., Kiriazis, J., Fischer, C., Creef, E., 1991. Semantic information distinguishing individual predators in the alarm calls of Gunnison's...
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This page contains 15 estimated quantiles for 9,203 level-12 Hydrologic Unit Code in the Southeastern United States for the decades 1950-1959, 1960-1969, 1970-1979, 1980-1989, 1990-1999, and 2000-2009. A multi-output neural network was used to generate the estimated quantiles (Worland and others, 2019). The R scripts that generated the predictions are also included along with a README file. The 15 quantiles are associated with the following 15 non-exceedance probabilities (NEPs): 0.0003, 0.0050, 0.0500, 0.1000, 0.2000, 0.3000, 0.4000, 0.5000, 0.6000, 0.7000, 0.8000, 0.9000, 0.9500, 0.9950, and 0.9997. The quantiles were calculated using the Weibull plotting position (more details can be found in the accompanying...
This paper reports a study on the importance of the training criteria for wind power forecasting and calls into question the generally assumed neutrality of the ‘goodness’ of particular forecasts. The study, focused on the Spanish Electricity Market as a representative example, combines different training criteria and different users of the forecasts to compare them in terms of the benefits obtained. In addition to more classical criteria, an information theoretic learning training criterion, called parametric correntropy, is introduced as a means to correct problems detected in other criteria and achieve more satisfactory compromises among conflicting criteria, namely forecasting value and quality. We show that...
An understanding of individuality in animal vocalizations can assist in tracking individuals spatially and temporally, and is particularly useful for species of conservation concern. We determined whether fitz bew vocalizations of the endangered Southwestern Willow Flycatcher (Empidonax traillii extimus) showed vocal individuality, assessed the differences in vocal individuality among three populations, and tested the ability of predictive vocalization models to reidentify individuals. Fitz bew vocalizations were recorded from two populations in Arizona (Roosevelt Lake and San Pedro River) and one in California (Kern River). Individuality was determined using discriminant function analysis (DFA) and trained artificial...
Strong and effective systems of governance are required to steer energy finance towards the fulfilment of policy goals around energy security, energy poverty and sustainability. This article assesses and explains the nature of the contemporary governance of energy finance. It first provides a typology and analysis of the different governance dimensions associated with: (i) the public governance of public finance; (ii) the public governance of private finance; and (iii) the private governance of private finance. It then identifies and seeks to account for key cross-cutting trends in these patterns of governance. Overall, while it finds evidence of significant activity in each of these areas, there remains a substantial...
Abstract (from http://www.sciencedirect.com/science/article/pii/S0022169414003990#): Water temperature is a fundamental property of river habitat and often a key aspect of river resource management, but measurements to characterize thermal regimes are not available for most streams and rivers. As such, we developed an artificial neural network (ANN) ensemble model to predict mean daily water temperature in 197,402 individual stream reaches during the warm season (May-October) throughout the native range of brook trout Salvelinus fontinalis in the eastern U.S. We compared four models with different groups of predictors to determine how well water temperature could be predicted by climatic, landform, and land cover...
Strong and effective systems of governance are required to steer energy finance towards the fulfilment of policy goals around energy security, energy poverty and sustainability. This article assesses and explains the nature of the contemporary governance of energy finance. It first provides a typology and analysis of the different governance dimensions associated with: (i) the public governance of public finance; (ii) the public governance of private finance; and (iii) the private governance of private finance. It then identifies and seeks to account for key cross-cutting trends in these patterns of governance. Overall, while it finds evidence of significant activity in each of these areas, there remains a substantial...
    map background search result map search result map Estimated quantiles for the pour points of 9,203 level-12 hydrologic unit codes in the southeastern United States, 1950--2009 Estimated quantiles for the pour points of 9,203 level-12 hydrologic unit codes in the southeastern United States, 1950--2009