Douglas C. Creighton

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This paper evaluates the four leading techniques proposed in the literature for construction of prediction intervals (PIs) for neural network point forecasts. The delta, Bayesian, bootstrap, and mean-variance estimation (MVE) methods are reviewed and their performance for generating high-quality PIs is compared. PI-based measures are proposed and applied(More)
Prediction intervals (PIs) have been proposed in the literature to provide more information by quantifying the level of uncertainty associated to the point forecasts. Traditional methods for construction of neural network (NN) based PIs suffer from restrictive assumptions about data distribution and massive computational loads. In this paper, we propose a(More)
The accurate prediction of travel times is desirable, but frequently prone to error. This is mainly attributable to both the underlying traffic processes, as well as in the data which are used to infer travel time. A more meaningful and pragmatic approach is to view travel time prediction as probabilistic inference and to construct prediction intervals,(More)
OLE Process Control (OPC) is an industry standard that facilitates the communication between PCs and Programmable Logic Controllers (PLC). This communication allows for the testing of control systems with an emulation model. When models require faster and higher volume communications, limitations within OPC prevent this. In this paper an interface is(More)
— Evolving artificial neural networks has attracted much attention among researchers recently, especially in the fields where plenty of data exist but explanatory theories and models are lacking or based upon too many simplifying assumptions. Financial time series forecasting is one of them. A hybrid model is used to forecast the hourly electricity price(More)
The performance of Adaptive Neuro Fuzzy Inference System (ANFIS) significantly drops when uncertainty exists in the data or system operation. Prediction Intervals (PIs) can quantify the uncertainty associated with ANFIS point predictions. This paper first presents a methodology to adapt the delta technique for construction of PIs for outcomes of the ANFIS(More)
When individual rats were exposed to different intensities of a stressor, foot shock, plasma catecholamines were found to be sensitive and reliable indices of the stress. Plasma corticosterone did not perform as well. Similarly, levels of both plasma epinephrine and norepinephrine correlated highly significantly with a behavioral measure of the degree of(More)