As is the case for many statistical model-fitting problems, time series models often require a transformation of the response to stabilize the variance and normalize the errors. A previous Quality Qu...

– Queries as a pioneering measure of public attention on various social issues have elicited considerable scholarly attention. The purpose of this paper is to address two fundamental questions, as fol...

iii OZ v DEDICATION vii ACKNOWLEDGEMENT viii LIST OF TABLES xi LIST OF FIGURES xii LIST OF ABBREVIATIONS xiv

Wireless traffic usage forecasting methods can help to facilitate proactive resource allocation solutions in cloud managed wireless networks. In this paper, we present temporal and spatial analysis of...

Wind speed forecasting is critical for wind energy conversion systems since it greatly influences the issues such as scheduling of the power systems, and dynamic control of the wind turbines. Also, it...

Wind speed forecasting is critical for the operations of wind turbine and penetration of wind energy into electricity systems. In this paper, a novel time series forecasting method is proposed for thi...

When selling similar products, mainly dueto product substitution by customers incase of stock outs and price/brand concerns,demand for a particular product may dependon the inventory positions of othe...

We study the value of smoothing replenishment rules in seasonal supply chains.Simulation modeling is adopted to compare the traditional and smoothing OUT.The impact of Holt-Winters parameters are stud...

We propose a methodology for employing memetics (local search) within the framework of evolutionary algorithms to optimize parameters of hidden markov models. With this proposal, the rate and frequenc...

We present the design of a Wireless Sensor Networks (WSN) level event prediction framework to monitor the network and its operational environment to support proactive self* actions. For example, by mo...

We present a system for online probabilistic event forecasting. We assume that a user is interested in detecting and forecasting event patterns, given in the form of regular expressions. Our system ca...

We know that SARS-Cov2 produces the new COVID-19 disease, which is one of the most dangerous pandemics of modern times. This pandemic has critical health and economic consequences, and even the health...

We formalise the notion of important extrema of a time series, that is, its major minima and maxima; analyse the basic mathematical properties of important extrema; and apply these results to the prob...

We consider the problem of predicting response time of a large scale enterprise system using causal forecasting models. Specifically, the problem pertains to predicting potential system failure well i...

We consider the problem of detecting temporal changes in the functional state of human subjects due to varying levels of cognitive load using real-time psychophysiological data. The proposed approach ...

We compare the 24-hour ahead forecasting performance of two methods commonly used for the prediction of the power output of photovoltaic systems. Both methods are based on Artificial Neural Networks (...

Volunteer grid computing comprises of volunteer resources which are unpredictable in nature and as such the scheduling of jobs among these resources could be very uncer-tain. It is also difficult to e...

Validating the quality of data is crucial for establishing the trustworthiness of data pipelines. State-of-the-art solutions for data validation and error detection require explicit domain expertise (...

Urban areas around the world are populating their streets with wireless sensor networks (WSNs) in order to feed incipient smart city IT systems with metropolitan data. In the future smart cities, WSN ...

Topology identification (TI) is a key task for state estimation (SE) in distribution grids, especially the one with high-penetration renewables. The uncertainties, initiated by the time-series behavio...