Decision Support System for Daily and Long Term Operations of the System of Milan, Italy

This paper describes a decision support system that forest managers can use to help evaluate short-term, site-specific silvicultural operating plans in terms of their potential impact on long-term, forest-level strategic objectives. The system is based upon strategic and tactical forest-level silvicultural planning models that are linked with each other and with a geographical information system. Managers can first use the strategic mathematical programming model to develop broad silvicultural strategies based on aggregate timber strata. These strategies help them to subjectively delineate specific candidate sites that might be treated during the first 10 years of a much longer planning horizon using a geographical information system and to describe potential silvicultural prescriptions for each candidate site. The tactical model identifies an annual silvicultural schedule for these candidate sites in the first 10 years, and a harvesting and regeneration schedule by 10-year periods for aggregate timber strata for the remainder of the planning horizon, that will maximize the sustainable yield of one or more timber species in the whole forest, given the candidate sites and treatments specified by the managers. The system is demonstrated on a 90 000 - ha area in northeastern Ontario.

Download Full-text

Decision Support System in an administrative context : The case of the reinsertion of Long-Term Unemployed in France

Decision Support in Public Administration ◽

10.1016/b978-0-444-81485-2.50015-0 ◽

1993 ◽

pp. 133-147 ◽

Cited By ~ 1

Author(s):

Jean-Charles Pomerol ◽

Michel Futtersack ◽

Jean-Marc Labat

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System

Download Full-text

A hybrid Decision Support System for the risk assessment of retinopathy development as a long term complication of Type 1 Diabetes Mellitus

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology ◽

10.1109/iembs.2010.5626245 ◽

2010 ◽

Cited By ~ 17

Author(s):

Marios Skevofilakas ◽

Konstantia Zarkogianni ◽

Basil G Karamanos ◽

Konstantina S Nikita

Keyword(s):

Diabetes Mellitus ◽

Risk Assessment ◽

Type 1 Diabetes ◽

Decision Support ◽

Decision Support System ◽

Type 1 Diabetes Mellitus ◽

Support System

Download Full-text

Long-term survival in patients included in a randomized controlled trial of TREAT, a decision support system for antibiotic treatment

Journal of Antimicrobial Chemotherapy ◽

10.1093/jac/dkt222 ◽

2013 ◽

Vol 68 (11) ◽

pp. 2664-2666 ◽

Cited By ~ 16

Author(s):

L. Leibovici ◽

G. Kariv ◽

M. Paul

Keyword(s):

Randomized Controlled Trial ◽

Decision Support ◽

Decision Support System ◽

Antibiotic Treatment ◽

Support System ◽

Controlled Trial ◽

Term Survival ◽

Long Term Survival ◽

Randomized Controlled

Download Full-text

Improving SHAW long-term soil moisture prediction for continuous wheat rotations, Alberta, Canada

Canadian Journal of Soil Science ◽

10.4141/cjss08084 ◽

2010 ◽

Vol 90 (1) ◽

pp. 37-53 ◽

Cited By ~ 12

Author(s):

H. Wang ◽

G N Flerchinger ◽

R. Lemke ◽

K. Brandt ◽

T. Goddard ◽

...

Keyword(s):

Soil Moisture ◽

Decision Support ◽

Decision Support System ◽

Soil Water ◽

Support System ◽

Cropping System ◽

System Model ◽

Surface Residue ◽

Simultaneous Heat

The Decision Support System for Agrotechnology Transfer-Cropping System Model (DSSAT-CSM) is a widely used modeling package that often simulates wheat yield and biomass well. However, some previous studies reported that its simulation on soil moisture was not always satisfactory. On the other hand, the Simultaneous Heat and Water (SHAW) model, a more sophisticated, hourly time step soil microclimate model, needs inputs of plant canopy development over time, which are difficult to measure in the field especially for a long-term period (longer than a year). The SHAW model also needs information on surface residue, but treats them as constants. In reality, however, surface residue changes continuously under the effect of tillage, rotation and environment. We therefore proposed to use DSSAT-CSM to simulate dynamics of plant growth and soil surface residue for input into SHAW, so as to predict soil water dynamics. This approach was tested using three conventionally tilled wheat rotations (continuous wheat, wheat-fallow and wheat-wheat-fallow) of a long-term cropping systems study located on a Thin Black Chernozemic clay loam near Three Hills, Alberta, Canada. Results showed that DSSAT-CSM often overestimated the drying of the surface layers in wheat rotations, but consistently overestimated soil moisture in the deep soil. This is likely due to the underestimation of root water extraction despite model predictions that the root system reached 80 cm. Among the eight growth/residue parameters simulated by DSSAT-CSM, root depth, leaf area index and residue thickness are the most influential characteristics on the simulation of soil moisture by SHAW. The SHAW model using DSSAT-CSM-simulated information significantly improved prediction of soil moisture at different depths and total soil water at 0-120 cm in all rotations with different phases compared with that simulated by DSSAT-CSM. Key words: Soil moisture, modeling, Decision Support System for Agrotechnology Transfer-Cropping System Model, Simultaneous Heat and Water Model

Download Full-text

Design of an open source framework for oil spill decision support system

10.7287/peerj.preprints.1990v1 ◽

2016 ◽

Author(s):

Sahar Mokhtari ◽

Jiri Kadlec

Keyword(s):

Decision Support ◽

Decision Support System ◽

Open Source ◽

Oil Spill ◽

Support System ◽

Oil Pollution ◽

Long Term Effects ◽

Economic Activities ◽

Software Application

Oil spill in marine ecosystems have serious short term and long term effects on aquatics lifecycle and on social and economic activities. A Decision Support System (DSS) can assist environmental managers to visualize the distribution of oil pollution, identify sensitive areas that are likely to be exposed to oil pollutions, and assess vulnerable resources. This paper describes the design of an open source software framework and a prototype desktop software application of a DSS for oil spill management. This system can be connected to an open source oil spill simulation model. We also present a user interface for selecting the properties, time and location of a potential oil spill and for visualizing the oil spill affected area and its impact on coastal zone.

Download Full-text

Modules for Foodchain Transport, Dose Assessment and Long-Term Countermeasures in RODOS, The European Decision Support System

Radiation Protection Dosimetry ◽

10.1093/rpd/50.2-4.227 ◽

1993 ◽

Vol 50 (2-4) ◽

pp. 227-234

Author(s):

W. Friedland ◽

H. Müller ◽

G. Pröhl ◽

J. Brown ◽

N.P. McColl ◽

...

Keyword(s):

Decision Support ◽

Decision Support System ◽

Support System ◽

Dose Assessment

Download Full-text

A systematic approach for assessment of renewable energy using analytic hierarchy process

Energy Sustainability and Society ◽

10.1186/s13705-019-0219-y ◽

2019 ◽

Vol 9 (1) ◽

Cited By ~ 5

Author(s):

Gerçek Budak ◽

Xin Chen ◽

Serdar Celik ◽

Berk Ozturk

Keyword(s):

Renewable Energy ◽

Decision Support ◽

Decision Support System ◽

Analytic Hierarchy Process ◽

Support System ◽

Systematic Approach ◽

Analytic Hierarchy ◽

The World ◽

Hierarchy Process

Abstract Background Cities around the world face a great challenge in establishing a long-term strategy for the development of energy alternatives. Previous research tried to identify renewable energy across many different cities. Because each city has unique characteristics in terms of geographic and environmental conditions, population, economic development, and social and political environment, the most sustainable energy source for one city might be the least sustainable for another. Methods This research develops and implements a systematic approach to assess renewable energy and identify the energy alternatives for a city using the analytic hierarchy process. The methodology integrates experts’ input and data analytics and helps decision-makers form long-term strategies for renewable energy development. Results The decision support system is applied to three cities, Chengdu in China, Eskisehir in Turkey, and Chicago in the United States of America. Results show that improving energy efficiency and development of solar and wind energy are the most preferred energy alternatives whereas nuclear and hydroelectric are the least preferred energy alternatives for these three cities. Conclusions The results of this study are in line with decades of research and development in energy alternatives and show a clear direction for the future development of energy alternatives around the world. There are differences in the rankings of energy alternatives for different cities, indicating that it is necessary to apply the decision support system developed in this study to help form customized energy strategies for cities with unique characteristics.

Download Full-text