Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems

2020 ◽  
Vol 27 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Aleksandar Radonjić ◽  
Danijela Pjevčević ◽  
Vladislav Maraš

AbstractThis paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push boat–barge convoy assignmentsare part of the daily decision-making process done by dispatchers in IWT companiesforwhich a decision support tool does not exist. The aim of this paper is to develop a Neural Network Ensemble (NNE) model that will be able to assist in push boat–barge convoy assignments based on the push boat power.The primary objective of this paper is to derive an NNE model for calculation of push boat Shaft Powers (SHPs) by using less than 100% of the experimental data available. The NNE model is applied to a real-world case of more than one shipping company from the Republic of Serbia, which is encountered on the Danube River. The solution obtained from the NNE model is compared toreal-world full-scale speed/power measurements carried out on Serbian push boats, as well as with the results obtained from the previous NNE model. It is found that the model is highly accurate, with scope for further improvements.

2019 ◽  
Vol 109 (03) ◽  
pp. 134-139
Author(s):  
P. Burggräf ◽  
J. Wagner ◽  
M. Dannapfel ◽  
K. Müller ◽  
B. Koke

Der wachsende Bedarf an Wandlungsfähigkeit führt zu einer höheren Frequenz in der Umplanung von Montagesystemen und erfordert eine kontinuierliche Überprüfung und Anpassung des Automatisierungsgrades. Um auch die komplexen Umgebungsbedingungen abzubilden, sollen nicht-monetäre Faktoren in den Entscheidungsprozess eingebunden werden. Um die Entscheidung zu unterstützen, stellt dieser Beitrag ein Tool zur Identifizierung und Bewertung von Automatisierungsszenarien mittels einer Nutzwert-Aufwand-Analyse vor.   The increasing need for adaptability in assembly leads to a higher planning frequency of the system and requires continuous checks and adaptations of the appropriate level of automation. To account for the complex environmental conditions, non-monetary factors are included in the decision-making process. This paper presents a decision support tool to identify and evaluate automation scenarios by means of cost and benefit evaluation.


CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S14-S15
Author(s):  
S. McLeod ◽  
C. Thompson ◽  
B. Borgundvaag ◽  
L. Thabane ◽  
H. Ovens ◽  
...  

Introduction: eCTAS is a real time electronic triage decision-support tool designed to improve patient safety and quality of care by standardizing the application of the Canadian Triage and Acuity Scale (CTAS). The tool dynamically calculates a recommended CTAS score based on the presenting complaint, vital signs and selected clinical modifiers. The primary objective was to assess consistency of CTAS score distributions across 35 emergency departments (EDs) by 16 presenting complaints pre and post eCTAS implementation. Methods: This retrospective cohort study used population-based administrative data from January 2016 to December 2018 from all hospital EDs in Ontario that had implemented eCTAS with at least 9 months of data. Following a 3-month stabilization period, we compared data for 6 months post-eCTAS implementation to the same 6-month period the previous year (pre-implementation) to account for potential seasonal variation, patient volume and case-mix. We included triage encounters of adult (≥18 years) patients if they had one of 16 pre-specified high-volume, presenting complaints. A paired-samples t-test was used to determine consistency by estimating the absolute difference in CTAS distribution for each presenting complaint, by each hospital, pre and post eCTAS implementation, compared to the overall average of the 35 EDs. Results: There were 183,231 triage encounters in the pre-eCTAS cohort and 179,983 in the post-eCTAS cohort from 35 EDs across the province. Triage scores were more consistent with the overall average after eCTAS implementation in 6 (37.5%) presenting complaints: chest pain (cardiac features) (p < 0.001), extremity weakness/symptoms of cerebrovascular accident (p < 0.001), fever (p < 0.001), shortness of breath (p < 0.001), syncope (p = 0.02), and hyperglycemia (p = 0.03). Triage consistency was similar pre and post eCTAS implementation for the presenting complaints of altered level of consciousness, anxiety/situational crisis, confusion, depression/suicidal/deliberate self-harm, general weakness, head injury, palpitations, seizure, substance misuse/intoxication or vertigo. Conclusion: A standardized, electronic approach to performing triage assessments increased consistency in CTAS scores across many, but not all, high-volume CEDIS complaints. This does not reflect triage accuracy, as there are no known benchmarks for triage accuracy. Improvements in consistency were greatest for sentinel presenting complaints with a minimum allowable CTAS score.


Electronics ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. 1708
Author(s):  
Rafael Casado ◽  
Aurelio Bermúdez

Conflict detection and resolution is one of the main topics in air traffic management. Traditional approaches to this problem use all the available information to predict future aircraft trajectories. In this work, we propose the use of a neural network to determine whether a particular configuration of aircraft in the final approach phase will break the minimum separation requirements established by aviation rules. To achieve this, the network must be effectively trained with a large enough database, in which configurations are labeled as leading to conflict or not. We detail the way in which this training database has been obtained and the subsequent neural network design and training process. Results show that a simple network can provide a high accuracy, and therefore, we consider that it may be the basis of a useful decision support tool for both air traffic controllers and airborne autonomous navigation systems.


2012 ◽  
Vol 39 (3) ◽  
pp. 192 ◽  
Author(s):  
Michael Bode ◽  
Karl E. C. Brennan ◽  
Keith Morris ◽  
Neil Burrows ◽  
Neville Hague

Context Exclosure fences are widely used to reintroduce locally extinct animals. These fences function either as permanent landscape-scale areas free from most predators, or as small-scale temporary acclimatisation areas for newly translocated individuals to be ‘soft released’ into the wider landscape. Existing research can help managers identify the best design for their exclosure fence, but there are currently no methods available to help identify the optimal location for these exclosures in the local landscape (e.g. within a property). Aims We outline a flexible decision-support tool that can help managers choose the best location for a proposed exclosure fence. We applied this method to choose the site of a predator-exclusion fence within the proposed Lorna Glen (Matuwa) Conservation Park in the rangelands of central Western Australia. Methods The decision was subject to a set of economic, ecological and political constraints that were applied sequentially. The final exclosure fence location, chosen from among those sites that satisfied the constraints, optimised conservation outcomes by maximising the area enclosed. Key results From a prohibitively large set of potential exclosure locations, the series of constraints reduced the number of candidates down to 32. When ranked by the total area enclosed, one exclosure location was clearly superior. Conclusions By describing the decision-making process explicitly and quantitatively, and systematically considering each of the candidate solutions, our approach identifies an efficient exclosure fence location via a repeatable and transparent process. Implications The construction of an exclusion fence is an expensive management option, and therefore needs to convincingly demonstrate a high expected return-on-investment. A systematic approach for choosing the location of an exclosure fence provides managers with a decision that can be justified to funding sources and stakeholders.


2018 ◽  
Vol 9 (2) ◽  
pp. 6
Author(s):  
Megan Olander ◽  
Stephen Waring ◽  
David D Stenehjem ◽  
Allise Taran ◽  
Paul L Raneli ◽  
...  

  Background: Considerable progress has been made in the way of pharmacogenetic research and the development of clinical recommendations; however, its implementation into clinical practice has been slower than anticipated. We sought to better understand its lack of clinical uptake within primary care. Aim: The primary objective of this survey was to ascertain primary care clinicians’ perceptions of pharmacogenetic use and implementation in an integrated health system of metropolitan and rural settings across several states. Methods: Primary care clinicians (including MDs, DOs, NPs, and PAs) were invited to participate in a survey via email. Questions about pharmacogenetics knowledge and perceptions were presented to assess current understanding and usage of pharmacogenetics in practice. Results: The rate of response for the survey was 17%. Of the 90 respondents, 58% were female, 69% were MDs/DOs, 20% were NPs, and 11% were PAs. Fifty-eight percent of respondents received their clinical degree in or after 2000. Ninety percent of respondents noted that they were uncomfortable ordering a pharmacogenetics test, with 76% stating they were uncomfortable applying the results of a pharmacogenetic test. Notably, 78% of respondents were interested in having pharmacogenetic testing available through Medication Therapy Management (MTM) services, although PAs were significantly less interested as compared to NPs and MD/DOs. Ninety-five percent of respondents were interested in a clinical decision support tool relevant to pharmacogenetic results. Conclusions: As a whole, prescribing clinicians in primary care clinics are uncomfortable in the ordering, interpreting, and applying pharmacogenetic results to individual patients. However, favorable attitudes towards providing pharmacogenetic testing through existing MTM clinics provides the opportunity for pharmacists to advance existing practices. Conflict of Interest: We declare no conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received), employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties Treatment of Human Subjects: IRB determined project was non-HSR   Type: Student Project


Author(s):  
Seung-Kyum Choi ◽  
Mervyn Fathianathan ◽  
Dirk Schaefer

The advances in information technology significantly impact the engineering design process. The primary objective of this research is to develop a novel probabilistic decision support tool to assist management of structural systems under risk and uncertainty by utilizing a stochastic optimization procedure and IT tools. The proposed mathematical and computational framework will overcome the drawbacks of the traditional methods and will be critically demonstrated through large-scale structural problems. The efficiency of the proposed procedure is achieved by the combination of the Karhunen-Loeve transform with the stochastic analysis of polynomial chaos expansion to common optimization procedures. The proposed technology, comprising new and adapted current capabilities, will provide robust and physically reasonable solutions for practical engineering problems.


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