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Approximation and Visualization of Interactive Decision Maps Short course of lectures. Alexander V. Lotov Dorodnicyn Computing Center of Russian Academy of Sciences and Lomonosov Moscow State University.
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Alexander V. Lotov
Dorodnicyn Computing Center of Russian Academy of Sciences and
Lomonosov Moscow State University
Plan of the lecture
1. The problem of database screening
2. A simple graphic description of the method
3. Software demonstration (comparison of RGM and FGNL)
4. Screening procedure
5. Several applications of the RGM/IDM technique
The problem of database screeningA database of alternatives in the form of a decision matrix is considered, i.e., table of N decision alternatives (rows) given by a finite number of attributes (columns), a part of which is used as the criteria in database screening: one or several preferable rows must be selected from the database.
The criteria, which used for selecting a small number of alternatives, are assumed to be real values. Thus, an alternative is associated with a criterion point. The method is based on visualization of the Pareto frontier of the “cloud” of criterion points.
The decision maker has to identify the goal on the Pareto frontier of the “cloud”. Such information of the DM’s preferences helps to select a small number of «good» alternatives. This study can be considered as a special form of data mining.
The alternatives can be found in multiple large lists in Web describing the selection options: real estate on sale, second-hand cars, hotels, universities, etc.
On the other hand, alternative points can be results of scientific experiments or collecting research data.
Lists of financial projects can be developed described by such attributes as discounted investment, discounted income, term of complete investment return, reliability, etc.;
Alternative variants of portfolio or of assets allocation can exist described by such attributes as dividend, income, variability, etc.;
Alternative variants of business location given in a Geographical Information System can be found;
Large by finite number of Pareto-optimal strategies for solving of environmental or technical problems can be developed by using Feasible Goals technique, etc.
Approximating the Edgeworth-Pareto hull of the convex hull (the so-called CEPH)
Visualization of the Pareto frontier
is based on approximation of the CEPH and application of the Interactive Decision Mapstechniquefor the interactive analysisof the frontiers of the slices.
RGM/IDM-based software Visual Market – 2
Many rural areas in the USA, compete for medical doctor, thus creating choice opportunities for those interested in practicing rural medicine. Yet, these efforts coupled with various US federal programs have had mixed results in attracting and retaining primary health care providers in rural localities. One possible cause for this is the lack of effective information tools that would aid the prospective medical doctors in screening practice locations options and learning about tradeoffs involved.
The approach based on the RGM/IDM technique allows the prospective doctors to select preferable locations based on their closeness to the goal specified by them without the difficulty of specifying criterion weights. Along with the RGM/IDM technique, the DSS applies the geographic data query and visualization module implemented in ArcViewTM 3.0.
Data representing health-care, social, economic, and environmental information were aggregated by 47 Primary Care Service Area (PCSA) encompassing the entire state of Idaho. The attribute database describing the PCSA provided information for evaluation criteria. The criteria were grouped into professional and personal.
Professional criteria included:
Personal criteria included:
The modules supplement each other in providing decision support functions. The prospective physician can learn quickly about the location of places offering practice opportunities, their physical and socio-demographic characteristics, amenities offered by them, and relate this information to the surrounding physical environment by viewing and querying reference maps in ArcView. The information gained from spatial data query and visualization becomes useful in selecting a reasonable goal for the health practice location.
The goal selection, which is performed by the user, results in returning a list of few locations that are <<close>> to the selected goal in the sense described above. These locations can be in turn displayed and analyzed in ArcView. The process is interactive and iterative. Its intended outcome is a better-informed decision on the part of prospective health care professional about rural practice location selection.
In order to illustrate the application of the method, we use five attributes for the location selection criteria:
Actually, Nampa is the only location, which is close to the identified goal in the common sense of this word (note that the need for physicians is much higher in Nampa than it was set in the goal). Since the software does not know the preference trade-off of the user, it displays three different locations, which are not very near the goal, but may happen to be better locations from the user perspective than Nampa. Note that in Nampa the prospective physician has to spend 1.29 hours on call instead of one hour in the identified goal.
In St.Maries one has to spend only 0.92 hours on-call per week. Perhaps, the user would agree to sacrifice the population level for this advantage? Only the user can decide it. Weiser was selected since it is a little bit larger than St.Maries. Finally, Boise, the capital of Idaho, was chosen since Nampa does not meet the population level of the goal. Perhaps this is important for the user? The user has to decide whether any of the selected places is attractive enough for the location of health care practice. It is important to note that all other places in the database were further away from the identified goal, and so they were not selected.
APLICACIÓN DE LA MINERÍA DE DATOS EN LA LOCALIZACIÓN ÓPTIMA DE INSTALACIONES PETROLERASAlberto Barrón Alcántara, PEMEX PEP SCTIDavid Alberto Salas de León, ICML de la UNAMGlicinia Valentina Ortiz Zamora ICML de la UNAMMardocheo Palma Muñoz ICML de la UNAMWiliam Bandy ICML de la UNAMCarlos Mortera ICML de la UNAMAlexander LótovCCARCRomán Efrémov URJC
1.- Estructuración de geobase de datos
2.- Filtrado de datos
3.- Selección de variables
4.- Extracción de conocimiento
5.- Interpretación y evaluación
Number of decision alternatives was about 9000.
para la exploración
óptima de reservas petroleras
Ing. Alberto Barrón Alcántara
CCARC ( Centro de Computación de la Academia Rusa de Ciencias)
Dr. Alexander Lótov
Mr. Alexander Kistanov
Mr. Alexander Zaitzev
Dr. Roman Efremov
En total, 4907 alternativas…
Exploration of pollution abatement cost in the Electricity Sector – Israeli case study(jointly with D. Soloveitchik and other specialists fromMinistry of National Infrastructures, Israel)
Several hundreds of pollution reduction alternatives for the Israel electricity sector were developed for the period 2003 – 2013 by application of a complicated non-linear mathematical model (FGNL does not exist that time). Then, the IDM-based screening of alternatives was applied.
Decision map displays trade-off between CO2_% and NPV_D for several levels of NOx reduction as well as given levels of marginal abatement cost and percent of growing average cost of electricity
MULTIOBJECTIVE OPTIMIZATION FOR RIVER BASIN MANAGEMENT PLANL. Galbiati1, F.J. Elorza2, A. Udias3, F. Bouraoui1(1) JRC, Institute for Environment and sustainability. Rural, Water and Ecosystem Resources Unit (Italy).(2) D.M.A.M.I. (E.T.S.I. de Minas). Universidad Politécnica de Madrid. email: email@example.com.(3) D.E.I.O. (E.S. de C.C. Experimentales y Tecnología). U.R.J.C. Mostoles, Madrid (Spain).
Diffuse sources of pollution coming from agricultural practices are among the biggest problem to tackle when dealing with water management. Often the crop management is oriented to maximize production without considering the contamination caused to the ecosystem. This study is focusing on the identification of an optimize crop rotation, applying a MOEA technique coupled with a comprehensive hydrological model (ISSm) capable to take account all the components of the water cycle as well as the contamination occurring during agricultural practices and benefits from crop production. This tool has been applied to Burana-Po di Volano basin (Italy), demonstrating the effectiveness to provide tradeoff solutions that simultaneously minimize the leaching of pollutants to the groundwater and maximizes the exploitation benefits only choosing the adequate crop sequences. This methodology is an important support for policy makers and water managers, providing information about the cost-effectiveness of alternative agricultural practices.
Decision variables: allocation of crops between all sub-sub-regions for each year