scholarly journals Approach to the organization of decision support in the formulation of innovative regional development strategies applying adaptive-simulation model

Upravlenie ◽  
2019 ◽  
Vol 7 (3) ◽  
pp. 103-112
Author(s):  
L. Chernyakhovskaya ◽  
M. Nizamutdinov ◽  
V. Oreshnikov ◽  
A. Atnabaeva
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Regional Development ◽  
Support System ◽  
Knowledge Bases ◽  
Development Strategies ◽  
Innovative Development ◽  
Development Management ◽  
Adaptive Simulation ◽  
Regional Development Strategies

The issues of formation of the decision support system in the field of regional development management have been considered. The presented review of the existing approaches in this field testifies on the one hand to their diversity, and on the other hand, it allows us to draw a conclusion about the need to solute a number of methodological and practical issues of decision support in terms of innovative development of regions. On this basis, the goal of the research is to develop the concept of a decision support system to substantiate the parameters of the innovative strategy of regional development based on adaptive mechanisms for coordinating the interests of economic agents.The research methodology is based on the synthesis of different approaches in the framework of integration into the structure of adaptive simulation models of problem-oriented knowledge bases, as well as intelligent technologies for processing semistructured information, using to find decisions in the process of formation and adjustment of parameters of management of innovative development of the region. The result of the study is a theoretical justification for the development of problem-oriented DSS, including a description of the interrelated stages, determining the main design features of this toolkit.As a part of the study, a conceptual scheme of implementation of the decision support system in the field of management of regional innovative development has been proposed, the key functional blocks of the proposed tools have been described, the place of existing tools in the structure of the regional development management system has been determined, the possibilities of its use in the formation of forecast-planned assessments of regional development, as well as the evaluation of the effectiveness of alternative management actions, have been shown.In our opinion, the proposed tools will expand the possibilities of applying the management theory and decision support methods, intelligent information technology, economic and mathematical methods, modern computer simulation technologies for strategic planning of socio-economic systems of macro- and meso-level. In practice, the tools can be interesting for public authorities to solve problems in the formulation of innovative regional development strategies for the Russian regions, the formation of medium-term forecasts and the justification of the parameters of social, economic and budgetary policy.

scholarly journals LATIS: A Spatial Decision Support System to Assess Low Impact Site Development Strategies

2008 ◽  
Author(s):  
G. Wayne Wilkerson ◽  
William H. McAnally ◽  
James L. Martin ◽  
Jeffrey A. Ballweber ◽  
Kim Collins ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Development Strategies ◽  
Spatial Decision Support System ◽  
Spatial Decision Support ◽  
Impact Site ◽  
Site Development

scholarly journals The Current Principles of Regional Development Management and Regional Policy Formation

2020 ◽  
Vol 12 (515) ◽  
pp. 128-133
Author(s):  
O. Y. Churikanova ◽  
Keyword(s):  
Regional Development ◽  
Regional Policy ◽  
Business Models ◽  
Development Strategies ◽  
Regional Governance ◽  
Policy Formation ◽  
The State ◽  
Investment Policy ◽  
Development Management ◽  
Regional Development Strategies

The article is concerned with the current principles of regional development management and formation of regional policy. The key aspects and mechanisms of regional governance such as public administration and regionalistics are examined. The directions of research in the sphere of regional development management are provided. The main stages and components that provide for the implementation of the State policy of regional development are considered. Based on both Ukrainian and European regional development strategies, the following key principles of regional development management and regional policy formation are allocated: regional development based on the principles of sustainability; regional development based on the principles of circular economy; regional development based on the principles of typologization of regions; regional development based on the principles of investment policy. Each of these principles is considered separately in terms of the importance of application in the formation of regional development policy. During the analysis, it was noted that the topical issues in the formation of regional development strategies on the basis of sustainability were and remain the issues of assessment of the achieved results, which are distilled down to the development of a single conception and determination of the relevant goals of the group of indicators on which this conception should be based. It also emphasized the need to develop certain measures for the implementation of circular business models, development of transition strategy and policy of both the State-controlled and regional support. It is specified that in order to effectively develop territories in the management of regional development and formation of regional policy, it is necessary to take into account the specifics of each region, and therefore to perform a preliminary typologization. When considering regional investments in the formation of a regional development strategy, it is emphasized that in the formation of an effective investment policy at the regional level, the application of the approach based on the typologization of regions both in terms of development in general and in terms of investment development in particular becomes an important aspect. The general conception of regional development management and regional policy formation has been formed. The author emphasizes the conformity of such a conception to modern conditions for the development of Ukrainian regions.

scholarly journals EXPERT AND KNOWLEDGE SYSTEMS AND DATABASES OF THE BEST PRACTICE

2004 ◽  
Vol 10 (3) ◽  
pp. 88-95 ◽  
Author(s):  
Artūras Kaklauskas ◽  
Edmundas Kazimieras Zavadskas ◽  
Leonarda Gargasaite
Keyword(s):  
Knowledge Management ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Best Practice ◽  
Expert Knowledge ◽  
Knowledge Bases ◽  
Knowledge Systems ◽  
Web Based ◽  
The Web

Investigations on the similarities and differences of expert, knowledge management and decision support systems are presented in the paper. Explicit and tacit knowledge is analysed. The benefit of knowledge management systems, their development and implementation are analysed. The aspects of the best practice and its knowledge bases and databases are described. Practical possibilities to apply the knowledge systems are presented. On the base of practice acquired during the FP 6 project INTELCITIES the database of the best practice and the web‐based decision support system for real estate are developed. On the base of the BPJTA in PuBs project the database of the best practice and the web‐based decision support system for retrofit of public buildings are developed.

scholarly journals Intellectualization of Emergency Control of Power Systems on the Basis of Incorporated Ontologies of Knowledge-Bases

2019 ◽  
Vol 13 (2) ◽  
pp. 86-94
Author(s):  
Vladimir Morkun ◽  
Ihor Kotov
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Power Systems ◽  
Power System ◽  
Knowledge Base ◽  
Support System ◽  
Large Scale ◽  
Knowledge Bases ◽  
Experiment Planning ◽  
Control Actions

Abstract The research deals with improvement of methods and systems of controlling integrated power systems (IPSs) on the basis of intellectualization of decision-making support. Complex analysis of large-scale accidents at power facilities is performed, and their causes and damages are determined. There is substantiated topicality of building condition knowledge-bases as the foundation for developing decision-support systems in power engineering. The top priorities of the research include developing methods of building a knowledge base based on intensity models of control actions influencing the parameters of power system conditions and introducing the smart system into information contours of the automated dispatch control system (ADCS), as well as assessing practical results of the research. To achieve these goals, the authors apply methods of experiment planning, artificial intelligence, knowledge presentation, mathematical simulation, and mathematical statistics as well as methods of power systems studying. The basic research results include regression models of a power system sensitivity to control actions, methods of building a knowledge base based on the models of sensitivity matrices, a structure of the smart decision-support system, a scheme of introducing the decision-support system into the operating ADCS environment. The problem of building a knowledge base of the dispatch decision-support system on the basis of empirical data resulted from calculating experiments on the system diagram has been solved. The research specifies practical efficiency of the suggested approaches and developed models.

scholarly journals Enhancing Clinical Decision Support Systems with Public Knowledge Bases

2017 ◽  
Vol 1 (1) ◽  
pp. 49-60 ◽  
Author(s):  
Danchen Zhang ◽  
Daqing He
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Clinical Decision Support ◽  
Support System ◽  
Clinical Decision Support System ◽  
Clinical Decision ◽  
Knowledge Bases ◽  
Biomedical Literature ◽  
Automatic Diagnosis ◽  
Daunting Task

Abstract With vast amount of biomedical literature available online, doctors have the benefits of consulting the literature before making clinical decisions, but they are facing the daunting task of finding needles in haystacks. In this situation, it would be of great use to the doctors if an effective clinical decision support system is available to generate accurate queries and return a manageable size of highly useful articles. Existing studies showed the usefulness of patients’ diagnosis information in supporting effective retrieval of relevant literature, but such diagnosis information is often missing in most cases. Furthermore, existing diagnosis prediction systems mainly focus on predicting a small range of diseases with well-formatted features, and it is still a great challenge to perform large-scale automatic diagnosis predictions based on noisy medical records of the patient. In this paper, we propose automatic diagnosis prediction methods for enhancing the retrieval in a clinical decision support system, where the prediction is based on evidences automatically collected from publicly accessible online knowledge bases such as Wikipedia and Semantic MEDLINE Database (SemMedDB). The assumption is that relevant diseases and their corresponding symptoms co-occur more frequently in these knowledge bases. Our methods use Markov Random Field (MRF) model to identify diagnosis candidates in the knowledge bases, and their performance was evaluated using test collections from the Clinical Decision Support (CDS) track in TREC 2014, 2015, and 2016. The results show that our methods can automatically predict diagnosis with about 75% accuracy, and such predictions can significantly improve the related biomedical literatures retrieval. Our methods can generate comparable retrieval results to the state-of-the-art methods, which utilize much more complicated methods and some manually crafted medical knowledge. One possible future work is to apply these methods in collaboration with real doctors. Notes: a portion of this work was published in iConference 2017 as a poster, which won the best poster award. This paper greatly expands the research scope over that poster.

scholarly journals A SET OF TOOLS TO SUPPORT DEVELOPMENT AND MAINTENANCE OF SOLVERS FOR SYSTEMS WITH ONTOLOGICAL KNOWLEDGE BASES

2020 ◽  
Author(s):  
В.В. Грибова ◽  
Е.А. Шалфеева
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Knowledge Bases ◽  
Tool Support ◽  
Modern Approach ◽  
Knowledge Based ◽  
Ontological Approach ◽  
Collective Development ◽  
Software Services

Использование онтологического подхода является одним из современных подходов к созданию систем с базами знаний. Для построения жизнеспособных программных сервисов, работающих с такими базами знаний, и управления их коллективной разработкой предложена инструментальная среда. Метод инструментальной поддержки нацелен на создание и развитие библиотек онтолого-базированных операций, на использование их при конструировании программных средств, на распределение полномочий по созданию компонентов систем с базами знаний, на контроль и интеграцию их в облачную сопровождаемую систему поддержки принятия решений на основе знаний. The modern approach to creating systems with knowledge bases is based on an ontological approach. A tool environment is proposed for building viable software services that work with such knowledge bases and managing their collective development. The tool support method is aimed at creating and developing libraries of ontology-based operations, using them in the design of software tools, allocating authority to create components of systems with knowledge bases, and controlling and integrating them into a cloud-based, supported knowledge-based decision support system.

Data Mining in Designing an Agent-Based DSS

Data Mining ◽  
2011 ◽  
pp. 421-436
Author(s):  
Christian Bohm ◽  
Maria R. Galli ◽  
Omar Chiotti
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Software Engineering ◽  
Decision Support System ◽  
Support System ◽  
Knowledge Bases ◽  
Case Based Reasoning ◽  
Agent Based ◽  
Use Of Data ◽  
Using Data

The aim of this work is to present a data-mining application to software engineering. Particularly, we describe the use of data mining in different parts of the design process of an agent-based architecture for a dynamic decision-support system. The work is organized as follows: An introduction section defines the characteristics of a dynamic decision-support system and gives a brief background about the use of data mining and case-based reasoning in software engineering. A second section describes the use of data mining in designing the system knowledge bases. A third section presents the use of data mining in designing the learning process of the dynamic decision-support system. Finally, a fourth section describes the agent-based architecture we propose for the dynamic decision support system. It implements the mechanisms designed by using data mining to satisfy the system functionality.

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