Web-Based Expert Geographical Information System for Advanced Transportation Management Systems

2000 ◽  
Vol 1719 (1) ◽  
pp. 200-208 ◽  
Author(s):  
Kaan Özbay ◽  
Shirsendu Mukherjee
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Support System ◽  
Support Systems ◽  
Management Systems ◽  
Incident Management ◽  
Decision Support Tools ◽  
Web Based ◽  
Transportation Management ◽  
Support Tools

The Internet is fast becoming the standard environment for client-server applications that involve multiple users. The proliferation of Internet-based application development tools opens new doors to transportation researchers who work in real-time decision support system development. In the 1990s, one of the most important problems in advanced transportation management systems research was the development of better incident management systems. Although the incident management process has been well studied, the development of real-time decision support systems that can be used by all the involved agencies remains a challenging area of transportation engineering research. Existing incident management systems are developed on various traditional computing platforms, including UNIX and Windows. However, with the advent of the World Wide Web and Internet-based programming tools such as Java, it is possible to develop platform independent decision support tools for the incident management agencies. Web-based support tools offer an invaluable opportunity to develop next-generation online decision support tools for real-time traffic management. The applicability of Web-based tools to the development of online decision support systems for incident management is explored and demonstrated, and a prototype incident management decision support system (DSS) that has most of the capabilities of similar UNIX-based DSS support systems is developed and tested. Briefly described are the implementation and development of a prototype wide-area incident management system using Web-based tools.

scholarly journals Decision-Support Systems For Ambulatory Care, Including Pandemic Requirements: Using Mathematically Optimized Solutions

2021 ◽  
Author(s):  
Neele Leithäuser ◽  
Dennis Adelhütte ◽  
Kristin Braun ◽  
Christina Büsing ◽  
Martin Comis ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Ambulatory Care ◽  
Support Systems ◽  
Alternative Solution ◽  
Healthcare Sector ◽  
Decision Support Tools ◽  
Transport Services ◽  
Support Tools ◽  
Planning Problems

Abstract Background: The healthcare sector poses many strategic, tactic and operational planning questions. Due to the historically grown structures, planning is often locally confined and much optimization potential is foregone. Methods: We implemented optimized decision-support systems for ambulatory care for four different real-world case studies that cover a variety of aspects in terms of planning scope and decision support tools. All are based on interactive cartographic representations and are being developed in cooperation with domain experts. The planning problems that we present are the problem of positioning centers for vaccination against Covid-19 (strategical) and emergency doctors (strategical/tactical), the out-of-hours pharmacy planning problem (tactical), and the route planning of patient transport services (operational). For each problem, we describe the planning question, give an overview of the mathematical model and present the implemented decision support application. Results: Mathematical optimization can be used to model and solve these planning problems. However, in order to convince decision-makers of an alternative solution structure, mathematical solutions must be comprehensible and tangible. Appealing and interactive decision-support tools can be used in practice to convince public health experts of the benefits of an alternative solution. The more strategic the problem and the less sensitive the data, the easier it is to put a tool into practice. Conclusions: Exploring solutions interactively is rarely supported in existing planning tools. However, in order to bring new innovative tools into productive use, many hurdles must be overcome.

scholarly journals Point-of-care, real-time decision support tools: a pathway compliance solution but only when they are used

2015 ◽  
Vol 18 (3) ◽  
pp. A271
Author(s):  
B.A. Feinberg ◽  
J. Laney ◽  
S. English ◽  
J. Drenning
Keyword(s):  
Decision Support ◽  
Real Time ◽  
Point Of Care ◽  
Decision Support Tools ◽  
Support Tools

scholarly journals Decision Support Tools for Selecting Organisational Improvement Initiatives: a Review

2018 ◽  
Vol 7 (3.7) ◽  
pp. 153
Author(s):  
Musli Mohammad ◽  
Ligesh Manni Vattiyan ◽  
Mohd Shahir Yahya
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Management Systems ◽  
Decision Support Tools ◽  
Decision Matrix ◽  
Future Studies ◽  
Support Tools ◽  
Improvement Team

Decision support tools are used in many organisations to support organisational decision making activities. However, very limited studies have been found focussing on the decision support tools for selecting organisational improvement initiatives. Improvement initiatives are approaches, management systems, tools and/or techniques that can be used for managing and improving organisations, such as Lean, ISO9001 and Improvement Team. Four existing decision support tools were reviewed and compared. All four decision support tools consist of decision matrix, rating and ranking to assist in selecting appropriate improvement initiative. Finally, several potential future studies have been proposed.  

Wildfire decision support tools: an exploratory study of use in the United States

2020 ◽  
Vol 29 (7) ◽  
pp. 581
Author(s):  
Claire Rapp ◽  
Emily Rabung ◽  
Robyn Wilson ◽  
Eric Toman
Keyword(s):  
United States ◽  
Decision Making ◽  
Decision Support ◽  
The United States ◽  
Strategic Decision ◽  
Incident Management ◽  
Fire Weather ◽  
Decision Support Tools ◽  
Support Tools ◽  
Behaviour Models

In the United States, many decision support tools exist to provide fire managers with weather and fire behaviour information to inform and facilitate risk-based decision-making. Relatively little is known about how managers use these tools in the field and when and how they may serve to influence decisions. To address this gap, we conducted exploratory interviews with 27 wildfire management and fire weather professionals across the United States. Results reveal that barriers to the use of decision support tools are structural and social. Specifically, fire weather and behaviour models may not generate reliable output and managers may not use the information they provide, but technical specialists on incident management teams (IMTs) play an active role in trying to overcome these barriers through their technical expertise and their relationships with other members of the IMT. Although researchers suggest tools such as the Wildland Fire Decision Support System (WFDSS) inform broad, strategic decision-making for line officers and IMTs, our results suggest fire weather and behaviour models are also important for communication and strategic or tactical planning within the IMT, especially for operations. We find that ultimately, managers may make use of fire weather and behaviour models, but they do not dictate decisions.

Development of a Web-Based Intelligent Spatial Decision Support System (WEBISDSS)

2011 ◽  
pp. 184-202 ◽  
Author(s):  
Ramanathan Sugumaran ◽  
Shriram Ilavajhala ◽  
Vijayan Sugumaran
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Web Based ◽  
Extensible Markup ◽  
Intelligent Decision Support Systems

A SDSS combines database storage technologies, geographic information systems (GIS) and decision modeling into tools which can be used to address a wide variety of decision support areas (Eklund, Kirkby, and Pollitt, 1996). Recently, various emerging technologies in computer hardware and software such as speedy microprocessors, gigabit network connections, fast internet mapping servers along with Web-based technologies like extensible markup language (XML), Web services, etc provide promising opportunities to take the traditional spatial decision support systems one step further to provide easy-to-use, round-the-clock access to spatial data and decision support over the Web. Traditional DSS and Web-based spatial DSS can be further improved by integrating expert knowledge and utilizing intelligent software components (such as expert systems and intelligent agents) to emulate the human intelligence and decision making. These kinds of decision support systems are classified as intelligent decision support systems. The objective of this chapter is to discuss the development of an intelligent web-based spatial decision support system and demonstrate it with a case study for planning snow removal operations.

scholarly journals Real-time Detection of Road Traffic Incidents

2012 ◽  
Vol 22 (4) ◽  
pp. 273-283 ◽  
Author(s):  
Pero Škorput ◽  
Sadko Mandžuka ◽  
Niko Jelušić
Keyword(s):  
Kalman Filter ◽  
Decision Support ◽  
Decision Support System ◽  
Real Time ◽  
Extended Kalman Filter ◽  
Support System ◽  
Management System ◽  
Road Traffic ◽  
Incident Management ◽  
Incident Detection

The paper analyses the real-time detection of incidents in road traffic. A general model is presented of an integral road traffic incident management system. The paper presents the major incident detection methods. The detection procedure on open highway sections has been dealt with in particular. Adequate mathematical model has been defined, as the base for the realisation of the estimators of the traffic flow condition variables. The proposed method is the Extended Kalman Filter. The final part of the paper deals with an example for the realisation of the Incident Management Decision Support System (IMDSS). KEY WORDS: intelligent transport system, incident management system, traffic model in the status space, theory of estimation, extended Kalman filter, automatic incident detection, decision support system

scholarly journals THE WEB–BASED REAL ESTATE MULTIPLE CRITERIA NEGOTIATION DECISION SUPPORT SYSTEM: A NEW GENERATION OF DECISION SUPPORT SYSTEMS

2009 ◽  
Vol 13 (3) ◽  
pp. 267-286 ◽  
Author(s):  
Vita Urbanavičienė ◽  
Artūras Kaklauskas ◽  
Edmundas K. Zavadskas ◽  
Mark Seniut
Keyword(s):  
Decision Support ◽  
Real Estate ◽  
Decision Support System ◽  
Stress Analysis ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Web Based ◽  
New Generation ◽  
Voice Stress

The negotiations are an inseparable part of the real estate buying and selling process. Currently real estate are characterized by the intensive creation and use of information, knowledge and automation (software, knowledge and decision support systems, neural networks, etc.) applications. It is commonly agreed that a better integration of information, knowledge and automation applications, as well use of voice stress analysis (one of biometric technologies) might be an efficient mean for decision making in real estate negotiations. Voice stress analysis can help the negotiators to distinguish between truth and lies, improve the value of decisions made, significantly speed up real estate sector processes, help to reach a better real estate sales and purchase agreement terms and decrease the overall cost of real estate search and negotiation processes. The authors’ objective is to improve the quality and efficiency of decision support systems. The article analyses scientific research related to negotiations and presents the developed Web–based Real Estate Multiple Criteria Negotiation Decision Support System with integrated voice stress analysis– a new generation of Decision Support Systems. Santruka Derybos yra neatskiriama nekilnojamojo turto pirkimo ir pardavimo proceso dalis. Dabartiniam nekilnojamojo turto sektoriui būdingas intensyvus informacijos, žiniu ir automatizavimo naudojimas bei kūrimas (programine iranga, žiniu ir sprendimu paramos sistemos, neuroniniai tinklai ir pan.). Sutariama, kad geresnis informacijos, žiniu, automatizavimo, taip pat balso streso analizes (biometrines technologijos) integravimas pagreitina nekilnojamojo turto sektoriaus veikla. Balso streso analize gali padeti derybininkams atskirti, kada sakoma tiesa, o kada meluojama, padidina priimamu sprendimu naudinguma, paspartina nekilnojamojo turto paieškos ir derybu procesus, padeda pasiekti naudingesniu pirkimo ir pardavimo sutarties salygu bei sumažina nekilnojamojo turto paieškos ir derybu proceso kaina. Straipsnio autoriai, siekdami pagerinti sprendimu paramos sistemu kokybe ir efektyvuma, analizuoja mokslininku atliktu derybu srities tyrimu rezultatus ir pristato sukurta nekilnojamojo turto derybu internetine sprendimu paramos sistema su integruota balso streso analizes technologija kaip naujos kartos sprendimu paramos sistema.

Development of a Web-Based Intelligent Spatial Decision Support System (WEBISDSS)

2011 ◽  
pp. 637-651
Author(s):  
Ramanathan Sugumaran ◽  
Shriram Ilavajhala ◽  
Vijayan Sugumaran
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Web Based ◽  
Extensible Markup ◽  
Intelligent Decision Support Systems

A SDSS combines database storage technologies, geographic information systems (GIS) and decision modeling into tools which can be used to address a wide variety of decision support areas (Eklund, Kirkby, and Pollitt, 1996). Recently, various emerging technologies in computer hardware and software such as speedy microprocessors, gigabit network connections, fast internet mapping servers along with Web-based technologies like extensible markup language (XML), Web services, etc provide promising opportunities to take the traditional spatial decision support systems one step further to provide easy-to-use, round-the-clock access to spatial data and decision support over the Web. Traditional DSS and Web-based spatial DSS can be further improved by integrating expert knowledge and utilizing intelligent software components (such as expert systems and intelligent agents) to emulate the human intelligence and decision making. These kinds of decision support systems are classified as intelligent decision support systems. The objective of this chapter is to discuss the development of an intelligent web-based spatial decision support system and demonstrate it with a case study for planning snow removal operations.

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