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Jared Nystrom, Raymond R. Hill, Andrew Geyer, Joseph J. Pignatiello and Eric Chicken
Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction…
Abstract
Purpose
Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.
Design/methodology/approach
Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lightning prediction.
Findings
The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.
Research limitations/implications
The research is limited to the data collected in support of weather prediction work through the 45th Weather Squadron of the United States Air Force.
Practical implications
These methods are important due to the increasing reliance on sensor systems. These systems often provide incomplete and chaotic data, which must be used despite collection limitations. This work establishes a viable data imputation methodology.
Social implications
Improved lightning prediction, as with any improved prediction methods for natural weather events, can save lives and resources due to timely, cautious behaviors as a result of the predictions.
Originality/value
Based on the authors’ knowledge, this is a novel application of these imputation methods and the forecasting methods.
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Joshua L. McDonald, Edward D. White, Raymond R. Hill and Christian Pardo
The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting.
Abstract
Purpose
The purpose of this paper is to demonstrate an improved method for forecasting the US Army recruiting.
Design/methodology/approach
Time series methods, regression modeling, principle components and marketing research are included in this paper.
Findings
This paper found the unique ability of multiple statistical methods applied to a forecasting context to consider the effects of inputs that are controlled to some degree by a decision maker.
Research limitations/implications
This work will successfully inform the US Army recruiting leadership on how this improved methodology will improve their recruitment process.
Practical implications
Improved US Army analytical technique for forecasting recruiting goals..
Originality/value
This work culls data from open sources, using a zip-code-based classification method to develop more comprehensive forecasting methods with which US Army recruiting leaders can better establish recruiting goals.
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Zachary Hornberger, Bruce Cox and Raymond R. Hill
Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces…
Abstract
Purpose
Large/stochastic spatiotemporal demand data sets can prove intractable for location optimization problems, motivating the need for aggregation. However, demand aggregation induces errors. Significant theoretical research has been performed related to the modifiable areal unit problem and the zone definition problem. Minimal research has been accomplished related to the specific issues inherent to spatiotemporal demand data, such as search and rescue (SAR) data. This study provides a quantitative comparison of various aggregation methodologies and their relation to distance and volume based aggregation errors.
Design/methodology/approach
This paper introduces and applies a framework for comparing both deterministic and stochastic aggregation methods using distance- and volume-based aggregation error metrics. This paper additionally applies weighted versions of these metrics to account for the reality that demand events are nonhomogeneous. These metrics are applied to a large, highly variable, spatiotemporal demand data set of SAR events in the Pacific Ocean. Comparisons using these metrics are conducted between six quadrat aggregations of varying scales and two zonal distribution models using hierarchical clustering.
Findings
As quadrat fidelity increases the distance-based aggregation error decreases, while the two deliberate zonal approaches further reduce this error while using fewer zones. However, the higher fidelity aggregations detrimentally affect volume error. Additionally, by splitting the SAR data set into training and test sets this paper shows the stochastic zonal distribution aggregation method is effective at simulating actual future demands.
Originality/value
This study indicates no singular best aggregation method exists, by quantifying trade-offs in aggregation-induced errors practitioners can utilize the method that minimizes errors most relevant to their study. Study also quantifies the ability of a stochastic zonal distribution method to effectively simulate future demand data.
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Petar Jackovich, Bruce Cox and Raymond R. Hill
This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and…
Abstract
Purpose
This paper aims to define the class of fragment constructive heuristics used to compute feasible solutions for the traveling salesman problem (TSP) into edge-greedy and vertex-greedy subclasses. As these subclasses of heuristics can create subtours, two known methodologies for subtour elimination on symmetric instances are reviewed and are expanded to cover asymmetric problem instances. This paper introduces a third novel subtour elimination methodology, the greedy tracker (GT), and compares it to both known methodologies.
Design/methodology/approach
Computational results for all three subtour elimination methodologies are generated across 17 symmetric instances ranging in size from 29 vertices to 5,934 vertices, as well as 9 asymmetric instances ranging in size from 17 to 443 vertices.
Findings
The results demonstrate the GT is the fastest method for preventing subtours for instances below 400 vertices. Additionally, a distinction between fragment constructive heuristics and the subtour elimination methodology used to ensure the feasibility of resulting solutions enables the introduction of a new vertex-greedy fragment heuristic called ordered greedy.
Originality/value
This research has two main contributions: first, it introduces a novel subtour elimination methodology. Second, the research introduces the concept of ordered lists which remaps the TSP into a new space with promising initial computational results.
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Sarah Neumann, Darryl Ahner and Raymond R. Hill
This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of…
Abstract
Purpose
This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict.
Design/methodology/approach
In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction.
Findings
In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict.
Research limitations/implications
The study is based on actual historical data and is purely data driven.
Practical implications
The study demonstrates the utility of the analytical methodology but carries not implementation recommendations.
Originality/value
This is the first study to use the statistical methods employed to not only investigate the re-clustering of countries but more importantly the impact of that change on analytical predictions.
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A number of recent studies have suggested that many small businesses are opting to become members of strategic alliances with other firms in order to minimise the perceived…
Abstract
A number of recent studies have suggested that many small businesses are opting to become members of strategic alliances with other firms in order to minimise the perceived barriers to adoption of electronic commerce (E‐commerce). This study compares the perception of barriers to E‐commerce adoption between a sample of Swedish small to medium enterprises (SMEs) that have become members of some form of strategic alliance and those that have remained outside such arrangements. The results show that, in general, SMEs that are part of a strategic alliance perceive barriers as less applicable than their counterparts that are not part of a strategic alliance.
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Current issues of Publishers' Weekly are reporting serious shortages of paper, binders board, cloth, and other essential book manufacturing materials. Let us assure you these…
Abstract
Current issues of Publishers' Weekly are reporting serious shortages of paper, binders board, cloth, and other essential book manufacturing materials. Let us assure you these shortages are very real and quite severe.
Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some…
Abstract
Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.
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It has often been said that a great part of the strength of Aslib lies in the fact that it brings together those whose experience has been gained in many widely differing fields…
Abstract
It has often been said that a great part of the strength of Aslib lies in the fact that it brings together those whose experience has been gained in many widely differing fields but who have a common interest in the means by which information may be collected and disseminated to the greatest advantage. Lists of its members have, therefore, a more than ordinary value since they present, in miniature, a cross‐section of institutions and individuals who share this special interest.