800 resultados para Multicriteria Decision Support System


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In recent times, GIS is being increasingly used as a decision support system for management of fisheries and aquaculture. It provides new innovative approaches of the dynamic relations that characterize this sector. In this context, a study is conducted based on the secondary data of a major maritime state, Maharashtra, where mapping of fisheries profile of coastal districts in the state is performed through GIS tool having critical geographic dimensions. This paper aims to map information of the state which can be used for the purpose of planning and decision making as each aspect of map has a different component involved. For this purpose, at the core of the system, the data were accessed and integrated from different sources mainly from the five coastal districts of Maharashtra state. Data were brought in tabular form through Microsoft Excel and then joined to Map info Professional version 8.0 GIS software was used with the digitized map of Maharashtra state to enable mapping. This was further synchronized and integrated to generate four thematic maps searchable on several criteria. Map 1 contains the searchable criteria as regards to the fish growth for the year 1997-2004 and fish seed production for the year 2003-04. Map 2 contains fisher population along with their occupation for the year 1992. Map 3 contains brackish water and shrimp farming production and culture area. Map 4 contains infrastructural facilities which include type of boats etc. With this mapping, planners and various stakeholders have accessible information as regards to the various components of fisheries in the state of Maharashtra.

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结合前期研究共辨识出10项景观管理影响因子,依据其作用的性质和特点,将其分为4大类参数,通过NetWeaver模型构建了基于模糊逻辑的优先度评价知识库,在EMDS(Ecosystem Management Decision Support system)和ARCGIS9.x环境下,对4类景观管理影响因子的优先度进行了评价。结果显示:1)可行性因子综合优先度评价结果为除ws3、ws6、ws8和ws9 4个子流域的优先度为低外,其余6个子流域优先度居于中等优先水平;2)有效性因子优先度综合评价结果,ws1、ws9和ws10 3个子流域优先度为强,ws8优先度最低,其余子流域为中等优先;3)景观综合结果除ws1~ws33个子流域属于强外,其余子流域优先度为低;4)所有影响因子的综合结果为ws8子流域优先度最低,其余部分优先度居于中等。

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旱地作物需水量预报决策辅助系统是利用人工智能技术 ,在 Penman公式的基础上结合现有西北旱区的农学知识、模型以及经验进行系统集成而建立的智能化计算机软件系统 ,该系统是西北地区节水农业专家系统的一个子系统。在生产实践中可为陕西关中地区的冬小麦、夏玉米的栽培作出灌溉方案的决策咨询。

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为提高复杂网络环境和任务需求下器材保障的智能化水平,提出了一个数据驱动的多Agent器材保障决策支持系统DSS(decision support system),系统中的数据、模型以及Agent可分布在不同的网络节点上,高层Agent可由粒度更小的子Agent或Agent部件组合而成;系统中的各类智能Agent相互协作,共同完成异构数据集成、多维数据集构造、器材保障模型挖掘、复杂规划问题求解,以及保障方案自动生成等任务,从而有效降低了系统开发的难度,提高了Agent协作的灵活性。研究结果表明,该系统架构能够显著提升器材保障决策方案的质量和效率。

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阐述了一种交通战备保障方案实施决策支持系统,介绍了系统的数据库系统、模型库系统的设计.该系统主要针对突发事件,为交通战备保障方案的实施提供快速、有效的决策支持。

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In the paper through extensive study and design, the technical plan for establishing the exploration database center is made to combine imported and self developed techniques. By research and repeated experiment a modern database center has been set up with its hardware and network having advanced performance, its system well configured, its data store and management complete, and its data support being fast and direct. Through study on the theory, method and model of decision an exploration decision assistant schema is designed with one decision plan of well location decision support system being evaluated and put into action. 1. Study on the establishment of Shengli exploration database center Research is made on the hardware configuration of the database center including its workstations and all connected hardware and system. The hardware of the database center is formed by connecting workstations, microcomputer workstations, disk arrays, and those equipments used for seismic processing and interpretation. Research on the data store and management includes the analysis of the contents to be managed, data flow, data standard, data QC, data backup and restore policy, optimization of database system. A reasonable data management regulation and workflow is made and the scientific exploration data management system is created. Data load is done by working out a schedule firstly and at last 200 more projects of seismic surveys has been loaded amount to 25TB. 2. Exploration work support system and its application Seismic data processing system support has the following features, automatic extraction of seismic attributes, GIS navigation, data order, extraction of any sized data cube, pseudo huge capacity disk array, standard output exchange format etc. The prestack data can be accessed by the processing system or data can be transferred to other processing system through standard exchange format. For supporting seismic interpretation system the following features exist such as auto scan and store of interpretation result, internal data quality control etc. the interpretation system is connected directly with database center to get real time support of seismic data, formation data and well data. Comprehensive geological study support is done through intranet with the ability to query or display data graphically on the navigation system under some geological constraints. Production management support system is mainly used to collect, analyze and display production data with its core technology on the controlled data collection and creation of multiple standard forms. 3. exploration decision support system design By classification of workflow and data flow of all the exploration stages and study on decision theory and method, target of each decision step, decision model and requirement, three concept models has been formed for the Shengli exploration decision support system including the exploration distribution support system, the well location support system and production management support system. the well location decision support system has passed evaluation and been put into action. 4. Technical advance Hardware and software match with high performance for the database center. By combining parallel computer system, database server, huge capacity ATL, disk array, network and firewall together to create the first exploration database center in China with reasonable configuration, high performance and able to manage the whole data sets of exploration. Huge exploration data management technology is formed where exploration data standards and management regulations are made to guarantee data quality, safety and security. Multifunction query and support system for comprehensive exploration information support. It includes support system for geological study, seismic processing and interpretation and production management. In the system a lot of new database and computer technology have been used to provide real time information support for exploration work. Finally is the design of Shengli exploration decision support system. 5. Application and benefit Data storage has reached the amount of 25TB with thousand of users in Shengli oil field to access data to improve work efficiency multiple times. The technology has also been applied by many other units of SINOPEC. Its application of providing data to a project named Exploration achievements and Evaluation of Favorable Targets in Hekou Area shortened the data preparation period from 30 days to 2 days, enriching data abundance 15 percent and getting information support from the database center perfectly. Its application to provide former processed result for a project named Pre-stack depth migration in Guxi fracture zone reduced the amount of repeated process and shortened work period of one month and improved processing precision and quality, saving capital investment of data processing of 30 million yuan. It application by providing project database automatically in project named Geological and seismic study of southern slope zone of Dongying Sag shortened data preparation time so that researchers have more time to do research, thus to improve interpretation precision and quality.

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Synthetic Geology Information System(SGIS) is a part of the theory of Engineering Geomechanics-mate-Synthetics(EGMS), is also a development of its technical methodology. SGIS includes ways of geology engineering investigation, design, and construction. Although SGIS has an integrate theory frame, and some parts of it have gained great progress, the completion of SGIS is a continuous and accumulative process. This paper analyses the ways and principle of building knowledge database and model database, summarizes the experts' experience on exploration methods selection and the characters of exploration models, combining with the application of Decision Support System(DSS) in Decision support of Synthetic Exploration Methods for Railway engineering Geology. By the analysis of hierarchy structure of the model database, the effects of geology engineering factors on the selection of exploration methods are expressed. By the usage of fuzzy patterns recognize, hierarchy structure analysis, fuzzy collection closement analysis etc, the software of DSS for engineering design and construction are developed. At same time, by the development of Monitoring Data Analysis System and experiment data management system of Hydro-power project, this paper discussed the data management of science experiment of Hydro-power project by the usage of synthetic database and the usage of Geography Information System(GIS) and DSS technics. The technic of visual operation of data process and project monitoring system are presented. The intelligence algorithm of self-adoption is carried out to improve the data process and analysis of monitoring. Items of the project theoretical analysis and data process are designed in detail. All the theory and technical methods presented in this paper are one part of SGIS, in which the application of DSS and GIS, is an important step of the progress and completion of SGIS.

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Nutrient loss from agricultural land following organic fertilizer spreading can lead to eutrophication and poor water quality. The risk of pollution is partly related to the soil water status during and after spreading. In response to these issues, a decision support system (DSS) for nutrient management has been developed to predict when soil and weather conditions are suitable for slurry spreading. At the core of the DSS, the Hybrid Soil Moisture Deficit (HSMD) model estimates soil water status relative to field capacity (FC) for three soil classes (well, moderately and poorly drained) and has potential to predict the occurrence of a transport vector when the soil is wetter than FC. Three years of field observation of volumetric water content was used to validate HSMD model predictions of water status and to ensure correct use and interpretation of the drainage classes. Point HSMD model predictions were validated with respect to the temporal and spatial variations in volumetric water content and soil strength properties. It was found that the HSMD model predictions were well related to topsoil water content through time, but a new class intermediate between poor and moderate, perhaps ‘imperfectly drained’, was needed. With correct allocations of a field into a drainage class, the HSMD model predictions reflect field scale trends in water status and therefore the model is suitable for use at the core of a DSS.

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

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The environment is one of the greatest concerns of humankind. Nowadays, the activities which improve or destroy it must be assessed and controlled by efficient means which should permit the control of environmental impact caused by the development of these activities. This document presents an information system implementation, as a Decision Support system, allowing the Decision Maker to evaluate, foresee and control the future environmental impact of Tourism through consultation, the management and the presentation of decision schemes based on defined measures of a regional tourism planning.

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Tese de doutoramento, Ciências do Mar, da Terra e do Ambiente, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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The design and development of simulation models and tools for Demand Response (DR) programs are becoming more and more important for adequately taking the maximum advantages of DR programs use. Moreover, a more active consumers’ participation in DR programs can help improving the system reliability and decrease or defer the required investments. DemSi, a DR simulator, designed and implemented by the authors of this paper, allows studying DR actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. DemSi considers the players involved in DR actions, and the results can be analyzed from each specific player point of view.

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Energy systems worldwide are complex and challenging environments. Multi-agent based simulation platforms are increasing at a high rate, as they show to be a good option to study many issues related to these systems, as well as the involved players at act in this domain. In this scope the authors’ research group has developed a multi-agent system: MASCEM (Multi-Agent System for Competitive Electricity Markets), which simulates the electricity markets. MASCEM is integrated with ALBidS (Adaptive Learning Strategic Bidding System) that works as a decision support system for market players. The ALBidS system allows MASCEM market negotiating players to take the best possible advantages from the market context. However, it is still necessary to adequately optimize the player’s portfolio investment. For this purpose, this paper proposes a market portfolio optimization method, based on particle swarm optimization, which provides the best investment profile for a market player, considering the different markets the player is acting on in each moment, and depending on different contexts of negotiation, such as the peak and offpeak periods of the day, and the type of day (business day, weekend, holiday, etc.). The proposed approach is tested and validated using real electricity markets data from the Iberian operator – OMIE.

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One of the techniques used to detect faults in dynamic systems is analytical redundancy. An important difficulty in applying this technique to real systems is dealing with the uncertainties associated with the system itself and with the measurements. In this paper, this uncertainty is taken into account by the use of intervals for the parameters of the model and for the measurements. The method that is proposed in this paper checks the consistency between the system's behavior, obtained from the measurements, and the model's behavior; if they are inconsistent, then there is a fault. The problem of detecting faults is stated as a quantified real constraint satisfaction problem, which can be solved using the modal interval analysis (MIA). MIA is used because it provides powerful tools to extend the calculations over real functions to intervals. To improve the results of the detection of the faults, the simultaneous use of several sliding time windows is proposed. The result of implementing this method is semiqualitative tracking (SQualTrack), a fault-detection tool that is robust in the sense that it does not generate false alarms, i.e., if there are false alarms, they indicate either that the interval model does not represent the system adequately or that the interval measurements do not represent the true values of the variables adequately. SQualTrack is currently being used to detect faults in real processes. Some of these applications using real data have been developed within the European project advanced decision support system for chemical/petrochemical manufacturing processes and are also described in this paper

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Introducción Los Grupos Relacionados de Diagnóstico (GRD) se han usado para determinar la calidad de la atención en varios sistemas de salud. Esto ha llevado a que se obtengan resultados en el mejoramiento continuo de la atención y del cuidado. El objetivo de este estudio es determinar desenlaces clínicos de los pacientes a quienes se les había realizado reemplazo de articulares según la complejidad clínica definida mediante GRD. Métodos Se realizó un estudio longitudinal descriptivo en el cual se incluyeron todos los pacientes que tuvieron cirugía de reemplazo total de hombro, cadera y rodilla entre 2012 y 2014. Se realizó la estratificación de los pacientes de acuerdo a tres niveles de complejidad dados por el sistema de GRD y se determinaron las proporciones de pacientes para las variables de estancia hospitalaria, enfermedad trombo-embólica, cardiovascular e infección del sitio operatorio. Resultados Se realizaron en total 886 reemplazos articulares de los cuales 40 (4.5%) presentaron complicaciones. Los eventos más frecuentes fueron las complicaciones coronarias, con una presencia de 2.4%. El GRD1, sin complicaciones ni comorbilidades, fue el que presentó mayor número de eventos. La estancia hospitalaria fue de 3.8 a 9.3 días para todos los reemplazos. Conclusiones Contrario a lo planteado en la hipótesis de estudio, se encontró que el primer GRD presentó el mayor número de complicaciones, lo que puede estar relacionado con el tamaño del grupo. Es necesario realizar nuevas investigaciones que soporten el uso de los GRD como herramienta para evaluar desenlaces clínicos.