scholarly journals Microscopic Traffic Simulation as a Decision Support System for Road Diet and Tactical Urbanism Strategies

2021 ◽  
Vol 13 (14) ◽  
pp. 8076
Author(s):  
Bernice Liu ◽  
Amirarsalan Mehrara Molan ◽  
Anurag Pande ◽  
Jonathan Howard ◽  
Serena Alexander ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Travel Demand ◽  
Traffic Simulation ◽  
The United States ◽  
Microscopic Traffic Simulation ◽  
Street Design ◽  
Tactical Urbanism ◽  
The City

Urban street networks in the United States have been primarily designed for automobile traffic with negligible considerations to non-motorized transportation users. Due to environmental issues and quality of life concerns, communities are reclaiming street spaces for active modes and slowing the speeds in their downtown. Moreover, tactical urbanism, i.e., the use of street space for innovative purposes other than moving automobile traffic, is becoming attractive due to reduced automobile travel demand and the need for outdoor activities in the age of the COVID-19 pandemic. This study provides details of the modeling of an urban downtown network (in the City of San Jose) using microscopic traffic simulation. The model is then applied to evaluate the effectiveness of street design changes at varying demand scenarios. The microsimulation approach was chosen because it allows for the detailed modeling and visualization of the transportation networks, including movements of individual vehicles, bicyclists, and pedestrians. The street design change demonstrated here involves one-way to two-way street conversion, but the framework of network-wide impact evaluation may also be used for complete street conversions. The base conditions network was also tested under different travel demand reduction scenarios (10%, 20%, and 30%) to identify the corridors in the city network in which the tactical urbanism strategies (e.g., open-air dining) may be best accommodated. The study provides framework for the use of a microscopic model as part of a decision support system to evaluate and effectively implement complete streets/tactical urbanism strategies.

scholarly journals Sistem Pendukung Keputusan Pemilihan Perumahan Dengan Menggunakan Metode Multi Attribute Utility Theory

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Muhammad L O Mardin ◽  
Achamad Fuad ◽  
Hairil K Sirajuddin
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Utility Theory ◽  
Selection Process ◽  
Housing Prices ◽  
Multi Attribute Utility Theory ◽  
Selection Decision ◽  
The City ◽  
Selection Of

Abstrak: Banyaknya pilihan rumah seringkali membuat calon pembeli merasa ragu atau kesulitan saat harus menentukan langsung rumah yang mana yang akan dibeli, karena pada pemilihan perumahan yang akan dibeli belum ada sistem yang akan membantu dalam memilih perumahan yang dibeli, sehingga pada proses pemilihan masih menggunakan pikiran saja dan belum ada perhitungan pada saat pemilihan perumahan yang akan di beli. Tujuan penelitian ini menghasilkan sebuah sistem pendukung keputusan pemilihan perumahan. Kriteria yang diajukan dalam proses pemilihan perumahan yaitu: Harga perumahan, Jarak dari pusat kota, Jarak dengan pasar terdekat, [1], tipe perumahan, jarak dengan jalan umum, jarak dengan lahar. Dari hasil pemilihan perumahan menggunakan sistem yang telah dibuat. dengan 10 alternatif, dengan tingkat kepentingan masing-masing kriteria yang digunakan yaitu: harga = 5, tipe rumah = 5, jarak dengan pusat kota = 2, jarak dengan pasar terdekat = 2, jarak dengan jalan umum = 4, jarak perumahan dengan lahar = 5, telah diperoleh alternatif yang akan direkomendasikan yaitu perumahan safira residen 70 dengan dengan nilai tertinggi 0,65.Kata kunci: Sistem Pendukung Keputusan, Pemilihan, Perumahan, Multi Attribute Utility TheoryAbstract: A large number of choices of houses often makes prospective buyers feel doubtful or difficult when they have to determine directly which house to buy because, in the selection of housing to be purchased, no system will assist in choosing the housing to be purchased so that in the selection process, you still use your mind. There is no calculation at the time of the selection of housing to be purchased. The purpose of this research is to produce a housing selection decision support system. The criteria proposed in the housing selection process are housing prices, distance from the city, distance to the nearest market, [1], type of housing, distance to public roads, distance to lava. From the results of the election using the system that has been created. With ten alternatives, with their respective interests. The criteria used are: price =5, type of house = 5, distance to city center = 2, distance to the nearest market = 2, distance to public roads = 4 distance from housing to lava = 5, has obtained an alternative that will be recommended, namely the residential sapphire housing 70 with the highest value of 0.65Keywords: Housing, Selection, Decision Support System, Multi-Attribute Utility Theory.

scholarly journals Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework

2020 ◽  
Vol 13 ◽  
pp. 175628642093896
Author(s):  
Vida Abedi ◽  
Ayesha Khan ◽  
Durgesh Chaudhary ◽  
Debdipto Misra ◽  
Venkatesh Avula ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Improve Patient Care ◽  
The United States ◽  
Therapeutic Window ◽  
Ethical Challenges ◽  
Presenting Symptoms ◽  
Stroke Diagnosis

Stroke is the fifth leading cause of death in the United States and a major cause of severe disability worldwide. Yet, recognizing the signs of stroke in an acute setting is still challenging and leads to loss of opportunity to intervene, given the narrow therapeutic window. A decision support system using artificial intelligence (AI) and clinical data from electronic health records combined with patients’ presenting symptoms can be designed to support emergency department providers in stroke diagnosis and subsequently reduce the treatment delay. In this article, we present a practical framework to develop a decision support system using AI by reflecting on the various stages, which could eventually improve patient care and outcome. We also discuss the technical, operational, and ethical challenges of the process.

scholarly journals Decision-Support System for LID Footprint Planning and Urban Runoff Mitigation in the Lower Rio Grande Valley of South Texas

2020 ◽  
Vol 12 (8) ◽  
pp. 3152
Author(s):  
Javier Guerrero ◽  
Taufiqul Alam ◽  
Ahmed Mahmoud ◽  
Kim D. Jones ◽  
Andrew Ernest
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Rio Grande Valley ◽  
Rio Grande ◽  
The United States ◽  
South Texas ◽  
Lower Rio Grande Valley ◽  
Commercial Development ◽  
Lower Rio Grande

To address regional flooding in the United States, federal and state agencies are adopting strict drainage policies in any large-scale commercial development within the watershed boundary. The conventional approach of implementing a wet detention pond (WP) reduces the land cover and causes operation and maintenance challenges eventually. The present study developed a decision-support system (DSS) in the Lower Rio Grande Valley region of South Texas for optimal selection of Best Management Practices (BMPs) by substituting a portion of the WP footprint with three regionally promising low-impact development practices, namely, porous concrete pavement (PCP), bioretention (BR), and bioswale (BS). Source Load Assessment and Management Model for Windows (WinSLAMM) was used as the foundation for the DSS database and algorithm development. This tool suggested that the implementation of bioswale alone can considerably reduce the footprint and construction cost. Less than 0.95 ha of installation of BR and BS can mitigate 79–91% of runoff from a maximum of 5 ha of commercial development. A combination of BR, BS, and WP was found to reduce runoff significantly (~100%), which suggests that the successful adoption of DSS might support better planning of the urban stormwater management in the Lower Rio Grande Valley (LRGV).

scholarly journals Menentukan Rujukan Rumah Sakit Terbaik Bagi Pasien BPJS Menggunakan Metode Weighted Sum Model (WSM) Pada Puskesmas

2018 ◽  
Vol 3 ◽  
pp. 103
Author(s):  
Maulida Purba ◽  
Marsono Marsono ◽  
Rina Mahyuni
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Health Center ◽  
Support System ◽  
Weighted Sum ◽  
Cost Of Treatment ◽  
Level 1 ◽  
Level I ◽  
The Cost ◽  
The City

BPJS Health is one of the most important services for the community. For people who are sick and have been registered in BPJS, then the cost of treatment will be borne by the BPJS and the community is what is said as Patient BPJS. However, if a patient BPJS experiencing pain, then the patient first went to the health center or Faskes level 1 before being referred to the Hospital. Therefore, this study aims to build decision support system that has the ability to analyze in determining referral hospital for Patient BPJS at puskesmas or Faskes level 1. The method used in this research is Weighted Sum Model (WSM). The hospital samples used as many as 10 obtained from UPT Puskesmas Padang Bulan, Jln. Jamin Ginting - Medan. Based on calculations performed obtained the highest value of 77.5, ie on RS3. Therefore, this hospital is the foremost hospital as a reference for Patients BPJS. This research is expected to help the Puskesmas or Faskes level I in the city of Medan in providing hospital referrals for patients BPJS.

Decision Support System for the Rational Greening of the City on the Example of Yerevan, Republic of Armenia

2019 ◽  
Vol 10 (2) ◽  
pp. 87-96
Author(s):  
A. S. Akopov ◽  
◽  
A. L. Beklaryan ◽  
A. Saghatelyan ◽  
L. Sahakyan ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
The City

Hydronomeas 2020: Open-source decision support system for water resources management

2020 ◽  
Author(s):  
George Karavokiros ◽  
Dionysios Nikolopoulos ◽  
Stavroula Manouri ◽  
Andreas Efstratiadis ◽  
Christos Makropoulos ◽  
...  
Keyword(s):  
Decision Support ◽  
Water Resources ◽  
Decision Support System ◽  
Open Source ◽  
Support System ◽  
Early Stage ◽  
Linear Optimization ◽  
Optimization Approach ◽  
The City ◽  
Resources Planning

<p>Over the last 30 years, numerous water resources planning and management studies in Greece have been conducted by using state-of-the-art methodologies and associated computational tools that have been developed by the Itia research team at the National Technical University of Athens. The spearhead of Itia’s research toolkit has been the Hydronomeas decision support system (which stands for “water distributer” in Greek) supporting multi-reservoir hydrosystem management. Its methodological framework has been based on the parameterization-simulation-optimization approach comprising stochastic simulation, network linear optimization for the representation of water and energy fluxes, and multicriteria global optimization, ensuring best-compromise decision-making. In its early stage, Hydronomeas was implemented in Object Pascal – Delphi. Currently, the software is being substantially redeveloped and its improved version incorporates new functionalities, several model novelties and interconnection with other programs, e.g., EPANET. Hydronomeas 2020 will be available at the end of 2020 as a free and open-source Python package. In this work we present the key methodological advances and improved features of the current version of the software, demonstrated in the modelling of the extensive and challenging raw water supply system of the city of Athens, Greece.</p>

Building the Mobility Aircraft Availability Forecasting (MAAF) Simulation Model and Decision Support System

2005 ◽  
Vol 2 (2) ◽  
pp. 57-69 ◽  
Author(s):  
Frank W. Ciarallo ◽  
Raymond R. Hill ◽  
Sriram Mahadevan ◽  
Vikrant Chopra ◽  
Patrick J. Vincent ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
The United States ◽  
Limiting Factors ◽  
Mobility Modeling ◽  
Concept Model ◽  
Prototype Development ◽  
Mobility System ◽  
Definition Of

The Mobility Aircraft Availability Forecasting (MAAF) model prototype development and study effort was initiated to help the United States Air Force Air Mobility Command (AMC) answer the question, “How can we accurately predict mission capable (MC) rates?” While perfect prediction of aircraft MC rates is not possible, we investigate a simulation-based risk analysis approach. Current prediction methods utilize “after the fact” analyses and user opinion, making it difficult to perform quick, accurate, and effective analyses of potential limiting factors and policy changes, particularly in time-sensitive situations. This paper describes the MAAF proof-of-concept model and decision support system built to provide AMC managers the dynamic, predictive tools needed to better forecast aircraft availability. The simulation component featured new capabilities for mobility modeling to include dynamic definition of the configuration of a mobility system, dynamic definition of the capabilities of the individual airbases within a mobility system, improved representation of the aircraft objects within the model, and a new approach to modeling aircraft maintenance including the realistic consideration of partially mission capable aircraft. The development efforts and sample experimental results are recounted in this paper.

scholarly journals Developing the US Wildland Fire Decision Support System

2011 ◽  
Vol 2011 ◽  
pp. 1-14 ◽  
Author(s):  
Erin K. Noonan-Wright ◽  
Tonja S. Opperman ◽  
Mark A. Finney ◽  
G. Thomas Zimmerman ◽  
Robert C. Seli ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Program Effectiveness ◽  
Fire Management ◽  
Wildland Fire ◽  
The United States ◽  
Informed Decision ◽  
Informed Decision Making

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.

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