Douglas C. Creighton

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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)
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)
An unmanned aerial vehicle (UAV) has many applications in a variety of fields. Detection and tracking of a specific road in UAV videos play an important role in automatic UAV navigation, traffic monitoring, and ground-vehicle tracking, and also is very helpful for constructing road networks for modeling and simulation. In this paper, an efficient road(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)
This paper investigates a new approach for solving the multiobjective job shop scheduling problem, namely the Cuckoo Search (CS) approach. The requirement is to schedule jobs on a single machine so that the total material waste is minimised as well as the total tardiness time. The material waste is quantified in terms of saving factors to show the reduction(More)
A rich literature discussing techniques for adopting neural networks for metamodelling of complex systems exists. The main focus in many studies conducted so far has been on training and utilising neural networks as point estimators/predictors. Uncertainties prevailing within complex systems and dependencies amongst constituent entities are real threats for(More)
The accurate prediction of travel times is desirable but frequently prone to error. This is mainly attributable to both the underlying traffic processes and the data that are used to infer travel time. A more meaningful and pragmatic approach is to view travel time prediction as a probabilistic inference and to construct prediction intervals (PIs), which(More)
This paper presents the comparison between the Microsoft Kinect depth sensor and the Asus Xtion for computer vision applications. Depth sensors, known as RGBD cameras, project an infrared pattern and calculate the depth from the reflected light using an infrared sensitive camera. In this research, we compare the depth sensing capabilities of the two sensors(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)