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Автор: Grafiati

Опубліковано: 14 березня 2023

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1

Do, Myungsik. "Development of the Decision-Making System for National Highway Pavement Management." Journal of the Korean Society of Civil Engineers 34, no. 2 (2014): 645. http://dx.doi.org/10.12652/ksce.2014.34.2.0645.

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2

KOZLOVA, Valeria. "ECONOMIC DIAGNOSTICS IN THE SYSTEM OF INFORMATION SUPPORT FOR MANAGEMENT DECISION-MAKING." Herald of Khmelnytskyi National University. Economic sciences 312, no. 6(2) (December 29, 2022): 196–201. http://dx.doi.org/10.31891/2307-5740-2022-312-6(2)-33.

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Анотація:

The article updates the problem of the role, place and informative possibilities of economic diagnostics for making managerial decisions regarding the innovative development of the enterprise. A significant number of scientific publications of Ukrainian and foreign economists devoted to various aspects of managerial innovations were considered, and the need for a systematic search for ways of innovative transformation of managerial decision-making for the effective development of enterprises was revealed. Analytical models of managerial decision-making based on knowledge were analyzed, the necessity of using business analytics for multi-criteria decision-making was revealed. The factors of the impact of analytical information on the quality of management decisions regarding innovative development, technological improvement, productivity growth and value creation in the organizational environment are analyzed. The need to develop a system of information and analytical support for enterprise management using an analysis mechanism, the implementation of which is based on monitoring the achievement of predetermined evaluation criteria, is substantiated. The role of economic diagnostics in increasing the efficiency of management of the enterprise’s activities has been clarified. It is proposed to consider economic diagnostics as a leading element of the information support system of the management decision-making process, both to identify the causes of disagreements and to find factors for accelerating innovative transformations. The established diagnostic indicators of the system of innovative development of the enterprise are considered and the author’s approach to determining the factors of coordination is proposed. Thus, it was established that the use of economic diagnostics in the management of innovative development allows to increase the informative relevance for making conceptual management decisions.. Further research is proposed to focus on the development of methodological principles for the introduction of economic diagnostics into the system of management decision-making in operational, tactical and strategic directions.

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3

Zubovа, Lyudmila V., Eduard Viktorovich Korovin, Alexey Sergeevich Smirnov, Vladimir N. Kuzmin, and Andrey Valerievich Kurakov. "Development of Problem-Oriented Management and Decision-Making System and Optimization of Economic and Social Systems." Webology 18, SI05 (October 30, 2021): 436–51. http://dx.doi.org/10.14704/web/v18si05/web18239.

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The main goal of this study is to develop the theory of risk tolerance in task-oriented processes (using the example of enterprises engaged in research, development, and engineering), which is preceded by an analysis of scientific and methodological provisions for substantiating management decisions when developing promising space rocket technology under economic risks. The complexity of developing the theory of risk tolerance using the example of enterprises involved in the development of military and dual-use equipment lies in the multistructured evaluating system itself, justified by its multicomponent structure and large scale of topological complexity and logic of functioning in various modes and under different conditions, which leads to the need to divide it into a set of subsystems as moving substances in the process of task-oriented processes that have informational, methodological, and algorithmic commonality. That is accompanied by the decentralization of information processing in a structural parametric uncertainty. In this regard, in order to parameterize the uncertainty processes, the authors present a risk tolerance level assessment process diagram in task-oriented processes when developing military and dual-use equipment. Using the algorithm for determining the marginal cost of risk, marginal risk tolerance, and marginal risk level of an economic entity according to the method of L.V. Zubova, the work presents an approach of potentially dangerous risks (PDR) categorization of the financial and economic sphere and suggests ways to minimize risk, taking into account, if possible, risk rejection, determining the "cost of no action" in the face of uncertainty.

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4

Gibney, Lisa A., Scott E. Hansen, and Walter E. Wright, CEM. "Emergency management: Consequence management decision making." Journal of Emergency Management 2, no. 4 (October 1, 2004): 36. http://dx.doi.org/10.5055/jem.2004.0043.

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Emergency managers have a dilemma in deciding what to do when there is an emergency that affects their community. Those who have habitual hazards in their community are basically prepared. When a tornado is sighted in “tornado alley,” everyone knows what to do. When a hurricane is coming to shore along the Florida and Texas Gulf Coast, there are basic emergency steps to follow. But in this time of new and more challenging risks, we need a better system to coordinate community emergency decision making, no matter what the hazard. A simple solution is to adopt the four-level emergency event classification system that is already in use with communities with commercial nuclear power plants.

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5

Ada, Şükrü, and Mohsen Ghaffarzadeh. "Decision Making Based On Management Information System and Decision Support System." European Researcher 93, no. 4 (March 15, 2015): 260–69. http://dx.doi.org/10.13187/er.2015.93.260.

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6

Balaban, Edward, Stephen B. Johnson, and Mykel J. Kochenderfer. "Unifying System Health Management and Automated Decision Making." Journal of Artificial Intelligence Research 65 (August 7, 2019): 487–518. http://dx.doi.org/10.1613/jair.1.11366.

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Health management of complex dynamic systems has evolved from simple automated alarms into a subfield of artificial intelligence with techniques for analyzing off-nominal conditions and generating responses. This evolution took place largely apart from the development of automated system control, planning, and scheduling (generally referred to in this work as decision making). While there have been efforts to establish an information exchange between system health management and decision making, successful practical implementations of integrated architectures remain limited. This article proposes that rather than being treated as connected yet distinct entities, system health management and decision making should be unified in their formulations. Enabled by advances in modeling and algorithms, we believe that a unified approach will increase systems' resilience to faults and improve their effectiveness. We overview the prevalent system health management methodology, illustrate its limitations through numerical examples, and describe a proposed unified approach. We then show how typical system health management concepts are accommodated in the proposed approach without loss of functionality or generality. A computational complexity analysis of the unified approach is also provided.

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7

Yu., Tararico, and Lukashuk V. "Intellectual decision-making technology in agricultural production." Artificial Intelligence 27, jai2022.27(1) (June 20, 2022): 219–28. http://dx.doi.org/10.15407/jai2022.01.219.

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Objective assessment of agro-resource potential of regions, understanding of the principles of forming the optimal structure of production in relation to soil and climatic conditions and energy potential, analysis of factors influencing the use of certain means of production, allows producers to make close to optimal current and strategic decisions. To do this, all industrial resources must be considered not separately, but in a complex structure of the agricultural production system in order to ensure the most rational use of them in optimal quantities and interaction. To strengthen the food security and energy independence of the state, it is necessary to form a powerful agricultural sphere of Ukraine. This is achieved through the rational use of agricultural resources, including solar energy through the binding of virtually unlimited resources of nitrogen, carbon, oxygen and hydrogen of the Earth's atmosphere in fats, proteins and hydrocarbons, provided mandatory recycling or reuse of minerals, balanced combination of biological and industrial resources and systematic increase of soil fertility. Therefore, it is necessary to make the transition from the traditional style of enterprise management, based on the production experience and intuition of managers and staff, to modern methods of decision-making that allow for operational and long-term planning with high accuracy and predictability. It is known that the main tool of systems analysis is modeling. The fundamental value of the model lies in its ability to change the real process. For most farms, the farm-wide experimentation procedure is either unacceptable or impractical. Such an experiment has too dangerous consequences for them. Therefore, when analyzing the problem, there is a need for a simulator of the researched enterprise, which could be used for testing instead of the real system. Such a simulator is a model that should reflect the most important patterns of transformation of natural, material, financial, informational, energy and labor resources into agricultural products. The result is a system of interconnected standard modules for determining indicators: production volumes, product prices, the amount of costs, the amount of credit required, the assessment of possible profits and the accumulation of own funds. Each of the considered production or economic indicators can be determined separately. The algorithm of the perspective information system presented in the work allows to comprehensively analyze the action and interaction of individual components of agricultural production and to make close to optimal strategic and current decisions at different levels of agro-industrial complex management.

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8

Chen, Yi Lin. "Risk Decision-Making System in Manufacture Enterprise Management." Advanced Materials Research 694-697 (May 2013): 3592–95. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.3592.

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Risk has always been at the core of entrepreneurs daily decision-making, but factors will influence individuals decision-making. In this study, we investigated risk decision-making and cognition process of venture experts and novices under a given venture contexts. The purpose of the experiment is to investigate the difference of risk perception, risk propensity among venture experts, novice and college students, and to investigate the impact of these factors to individual risk decision-making. The result shows that, for the level of risk perception, there are prominent differences in experts and novices, but for the level of risk propensity, there is no prominent difference in experts and novices. It could be concluded that it is the risk perception influence individual risk decision-making but not the risk propensity.

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9

Awulor, Rita Ifeyinwa, Rhino Obi-Mallam, and Nnnena Mary Chukwu. "Enhancing organisational decision-making through management information system." Journal of Global Social Sciences 3, no. 11 (September 1, 2022): 115–33. http://dx.doi.org/10.31039/jgss.v3i11.71.

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Анотація:

The goal of a management information system is to deliver information in a timely and efficient manner to assist decision-making and other management functions. It consists of flow-processing operations based on computer data that are integrated with other procedures. This finding is also true when we take into account the exponential growth of modern business data and information. Efficient business decision-making is only possible with timely, accurate, high-quality information that is managed by qualified personnel, but in most cases, ineffective efficiency is caused by a lack of effective management information systems. Every aspect of life and human activity has been streamlined by the quick growth of information technology and telecommunications technology. To achieve high-quality decision-making at all levels of management, from the top level to the lowest, this technology must be well-organized. Information technology provides excellent options for quick and qualitative manipulation to improve the standard of decision-making preparation by organising the best and optimal database.

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10

Barr, Thomas R. "Critical Decision Making: The Decision to Deploy a Clinical Management System." Journal of Oncology Practice 1, no. 2 (July 2005): 71–74. http://dx.doi.org/10.1200/jop.2005.1.2.71.

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11

Barr, T. R. "Critical Decision Making: The Decision to Deploy a Clinical Management System." Journal of Oncology Practice 1, no. 2 (July 1, 2005): 71–74. http://dx.doi.org/10.1200/jop.1.2.71.

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12

Balashova, I. V. "Analyzing Problems of Decision-Making in Project Management." Vestnik of the Plekhanov Russian University of Economics, no. 2 (April 13, 2022): 74–81. http://dx.doi.org/10.21686/2413-2829-2022-2-74-81.

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Анотація:

The article shows that functioning of big companies is usually connected with accomplishing a great deal of various projects, whose management requires such tools that give an opportunity to organize project work. It is recommended to integrate systems of decision-making support with systems operating at the enterprise, which can increase the speed of data processing, search for alternative decisions and their impact on project management. It is possible to improve the process of project management at the enterprise by introducing new technologies and tools providing objective analysis of data with plotting a model of moving events and resolving problems dealing with the quality of estimating project solutions. Therefore, the information system should be used as a tool supporting decision-making aimed at collecting, optimizing, analyzing data, finding errors at present and forecasting further steps in project development. The system of decision-making support is an interactive automated system, whose goal is to help the user apply data and mechanisms for identification and settlement of problems in the adequate way. The efficient and wide use of software has become one of key factors of development and success of companies in conditions of fierce competition.

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13

Ravinder, H. V., and Carl R. Schultz. "Decision Making in a Standby Service System." Decision Sciences 31, no. 3 (September 2000): 573–93. http://dx.doi.org/10.1111/j.1540-5915.2000.tb00935.x.

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14

Hidayat, Moch Charis, and Abdul Wahab. "UTILIZATION OF EDUCATION MANAGEMENT INFORMATION IN DECISION MAKING." Humanities & Social Sciences Reviews 7, no. 3 (April 30, 2019): 349–55. http://dx.doi.org/10.18510/hssr.2019.7352.

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Purpose of Study: The undeniable fact that information at this time has been viewed as a very potential resource. Infor- mation is the only source needed by a leader of an educational institution. Information can be processed from other sources that are influenced by very complex organizations and owned computer devices. Methodology: Information processed using a computer can be used by an organizational leader and an individual with expertise as a means of communication and problem solving, as well as valuable information in the decision making the process. Results: In general from the results of research that researchers do indeed the combination of human resources and infor- mation technology applications that are tried to apply have been done. But this is not an easy matter, of course, depending on the focus of the development of management information systems individually sees the needs that are needed now. Implications/Applications: After studying and analyzing about the utilization of education management information sys- tem in decision making hence writer concludes that; first, decision making needs good information, second, irrelevant information will cause wrong judgment in making decision, third, the main basis of framework of information system utilization in taking decisions all information presented by the information system should be aimed at supporting certain phases of the decision-making process; fourth, the utilization framework of management information systems in decision making can also be used to assess an ongoing reporting system, fifth, decision making in education is an important part that should be done well by managers or other officials.

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15

C, Muthuvelayutham, and Sugantha lakshm T. "The impact of enterprise systems in management decision making." Journal of Management and Science 1, no. 1 (June 30, 2012): 68–72. http://dx.doi.org/10.26524/jms.2012.8.

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An Enterprise Resource Planning (ERP) system is composed of a basic transactional system and a management control system. Sammon et al. (2003) describesthese 2 components of ERP systems as the solution to “operational” integration problems and “informational” requirements of managers. Thus, the extreme standardisation of business process inherent in ERP systems creates huge volumes of data without providing a clue for how to exploit it and may therefore not beneficial from a decision-making point of view. In this paper, decision-making theory and models are reviewed, focusing on how an ERP implementation might impact on these constructs. This paper is an analysis about centralisation of decision making in an organisation and its impact on performance at a local level.

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16

Lee, Daniel T. "Expert Decision-support Systems for Decision-making." Journal of Information Technology 3, no. 2 (June 1988): 85–94. http://dx.doi.org/10.1177/026839628800300204.

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Computers have made tremendous contributions towards transactional processing. However, the highest pay-off the computer can make is not in transactional processing but in decision-making. Recently, expert systems have just begun to be used in the decision-making process. Individual technologies alone are inadequate for an effective decision support. The purpose of this paper is to investigate the related issues in decision support and to develop an expert decision support system (EDSS) for combining decision support systems and expert systems into a unified whole for decision support. The emphasis will be on developing a DSS/ES model which can be used to integrate the traditional DSS database and ES knowledge-base for building a user-friendly EDSS.

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17

BELYAKOVA, A. I. "MANAGEMENT AND SYSTEM ANALYSIS AS THE BASIS OF EFFECTIVE MANAGEMENT IN THE ECONOMY." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 1 (2021): 53–62. http://dx.doi.org/10.36871/ek.up.p.r.2021.01.01.009.

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Any management system is subject to change, and each time requires research and management decisionmaking in accordance with the changes. Decision-making in complex systems is carried out by a technical device or a person and is based on the comparison and evaluation of options for action. The study of decision-making procedures and the appropriate organization of the system is an urgent problem in the creation and operation of complex systems. Making such decisions is impossible without system analysis. This is due to the relevance of the article.

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18

Prato, Tony, Chris Fulcher, Shunxiang Wu, and Jian Ma. "Multiple-Objective Decision Making for Agroecosystem Management." Agricultural and Resource Economics Review 25, no. 2 (October 1996): 200–212. http://dx.doi.org/10.1017/s1068280500007863.

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Multiple-objective decision making (MODEM) provides an effective framework for integrated resource assessment of agroecosystems. Two elements of integrated assessment are discussed and illustrated: (1) adding noneconomic objectives as constraints in an optimization problem; and (2) evaluating tradeoffs among competing objectives using the efficiency frontier for objectives. These elements are illustrated for a crop farm and watershed in northern Missouri. An interactive, spatial decision support system (ISDSS) makes the MODEM framework accessible to unsophisticated users. A conceptual ISDSS is presented that assesses the socioeconomic, environmental, and ecological consequences of alternative management plans for reducing soil erosion and nonpoint source pollution in agroecosystems. A watershed decision support system based on the ISDSS is discussed.

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19

Kuznetsova, Inna, Yulia Karpenko, and Andriy Repin. "Decision-making management for improvement of the logistics system." Socio-Economic Research Bulletin, no. 2(73) (June 28, 2020): 136–49. http://dx.doi.org/10.33987/vsed.2(73).2020.136-149.

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20

Orak, İlhami M., Beyza Yaman, and Giovanna Guerrini. "Designing workshop management system supporting decision making with OODB." Procedia Technology 1 (2012): 19–23. http://dx.doi.org/10.1016/j.protcy.2012.02.006.

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21

B.M., Pleskach. "Precedent support for decision-making in energy management." Artificial Intelligence 25, no. 2 (July 15, 2020): 53–60. http://dx.doi.org/10.15407/jai2020.02.053.

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The article presents an approach to the formation of a decision support system in the management of energy consumption of production technological systems. Such systems allow the company to detect and respond in a timely manner to the appearance of hidden energy losses, to carry out organizational measures aimed at energy saving and to optimize the timing and scope of repair and restoration work. The approach is based on the modeling of stationary sections of energy consumption, presented in the form of precedents, their accumulation and subsequent analysis in the space of influential technological parameters. In addition to the base of precedents, the system includes software modules for assessment and formation of the profile of hidden energy losses, modules of technical condition, forecast and formation of precedents. The analysis of precedents consists in the selection of similar cases of energy consumption, the formation of efficient energy consumption functions and the calculation of energy losses with its help. Hidden energy losses can be calculated in real time for all technological systems of the enterprise. This allows you to build a profile of energy losses of the enterprise. The advantage of this approach in comparison with the known ones is that it allows to adapt to technological systems with different energy sources. The article emphasizes that the method can work with the energy manager with both linear and nonlinear dependence of energy consumption on process parameters. However, the limitations of this approach are noted. Thus, the determination of latent energy losses and technical condition of the equipment requires the participation of qualified specialists of the enterprise, who must be able to analyze the results and propose measures to eliminate energy losses.

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22

Badiru, Adedeji B., P. Simin Pulat, and Myungkoo Kang. "DDM: Decision support system for hierarchical dynamic decision making." Decision Support Systems 10, no. 1 (July 1993): 1–18. http://dx.doi.org/10.1016/0167-9236(93)90002-k.

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23

Forth, Jeremy, Kostas Stathis, and Francesca Toni. "Decision Making with a KGP Agent System." Journal of Decision Systems 15, no. 2-3 (January 2006): 241–66. http://dx.doi.org/10.3166/jds.15.241-266.

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24

Lewandowski, Andrzej. "SCDAS — Decision support system for group decision making: Decision theoretic framework." Decision Support Systems 5, no. 4 (December 1989): 403–23. http://dx.doi.org/10.1016/0167-9236(89)90019-5.

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25

Powell, Robert A., and Dennis M. Buede. "Decision-Making for Successful Product Development." Project Management Journal 37, no. 1 (March 2006): 22–40. http://dx.doi.org/10.1177/875697280603700103.

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Success is the objective during product development and good decision-making is the “yellow brick road” that leads to success. Decisions are used by systems engineers and project managers to guide and control events that occur during product development. Mistakes due to an improper definition of decisions made in the front end of the development process can have substantially negative impacts on the total cost of the system and its success with users and bill payers. The purpose of this paper is to define key decisions that can aid project managers and systems engineers during product development.

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26

Ak, Hacer, and Washington Braida. "Sustainable municipal solid waste management decision making." Management of Environmental Quality: An International Journal 26, no. 6 (September 14, 2015): 909–28. http://dx.doi.org/10.1108/meq-03-2015-0028.

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Анотація:

Purpose – The purpose of this paper is to assess a comprehensive model that computes a single score in order to evaluate the sustainability of the municipal solid waste management (MSWM) system of a given city. The model was applied to calculate the sustainability index for the MSWM of Istanbul, Turkey as a case study. Design/methodology/approach – Different sustainability indicators (including environmental, economical, and social parameters) along with exergy analysis were integrated to utilize an analytical hierarchy process (AHP) under a life cycle perspective. Findings – The Istanbul case study helped to verify that AHP is an effective and efficient decision-making tool. According to the analysis, the current MSWM system of Istanbul is sustainable, and the sustainability can be improved only by changing the amounts to be treated by the current system without any new technological investments. Research limitations/implications – The Municipal Solid Waste Management Sustainability Index (MSWMSI) in this study allowed to integrate large amount of information on interrelated parameters and the sustainability indicators in the whole life cycle into one value that is useful for a general or a comparative judgment and helpful in MSWM decision making. Originality/value – The fact that the weighting assigned to each component in the model is dependent on the decision makers’ evaluations enables the model to be tailored to any city of concern. The model allows the user to readily determine the relative contribution of each criterion or sub-criterion to the final MSWM selection. It is convenient to use and the computations can be run utilizing available specialized software as well as computing by hand.

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27

Gottschalk, Petter. "System dynamics and multiple-criteria decision making." System Dynamics Review 2, no. 1 (1986): 67. http://dx.doi.org/10.1002/sdr.4260020106.

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28

van Bruggen, Gerrit H., Ale Smidts, and Berend Wierenga. "Improving Decision Making by Means of a Marketing Decision Support System." Management Science 44, no. 5 (May 1998): 645–58. http://dx.doi.org/10.1287/mnsc.44.5.645.

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29

Venkatcharyulu, S., and Dr G. K. Viswanadh. "Model Study of Decision Support System for Water Management." E3S Web of Conferences 184 (2020): 01119. http://dx.doi.org/10.1051/e3sconf/202018401119.

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Анотація:

Decision making system (DSS ) is Integrated , interacting tool with information which provide solutions or answers to the policy makers , Dss users, End users to make quick and useful decision. In this paper it is reviewed Dss model based journal papers and presented various model functionality and description of methodology that are used. It is also discussed about literature review of that papers. Most of the water resources journal papers are published on various approaches are based on Software used decision making. Dss in Inida is required for the water management and hydropower management. Several papers published GIS based decision making and papers emphasis on computer based decision making. Quick review of Dss with few number (14) reviewed and presented in this paper.

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30

Song, Kai, Peng Xu, Guo Wei, Yinsheng Chen, and Qi Wang. "Health Management Decision of Sensor System Based on Health Reliability Degree and Grey Group Decision-Making." Sensors 18, no. 7 (July 17, 2018): 2316. http://dx.doi.org/10.3390/s18072316.

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Metal Oxide Semiconductor (MOS) gas sensor has been widely used in sensor systems for the advantages of fast response, high sensitivity, low cost, and so on. But, limited to the properties of materials, the phenomenon, such as aging, poisoning, and damage of the gas sensitive material will affect the measurement quality of MOS gas sensor array. To ensure the stability of the system, a health management decision strategy for the prognostics and health management (PHM) of a sensor system that is based on health reliability degree (HRD) and grey group decision-making (GGD) is proposed in this paper. The health management decision-making model is presented to choose the best health management strategy. Specially, GGD is utilized to provide health management suggestions for the sensor system. To evaluate the status of the sensor system, a joint HRD-GGD framework is declared as the health management decision-making. In this method, HRD of sensor system is obtained by fusing the output data of each sensor. The optimal decision-making recommendations for health management of the system is proposed by combining historical health reliability degree, maintenance probability, and overhaul rate. Experimental results on four different kinds of health levels demonstrate that the HRD-GGD method outperforms other methods in decision-making accuracy of sensor system. Particularly, the proposed HRD-GGD decision-making method achieves the best decision accuracy of 98.25%.

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31

Sinta Dewi Octavia Sakti and Dwihanus Dwihanus. "PERAN SISTEM INFORMASI MANAGEMENT (SIM) DALAM PENGAMBILAN KEPUTUSAN." Jurnal Manajemen dan Ekonomi Kreatif 1, no. 1 (December 27, 2022): 212–25. http://dx.doi.org/10.59024/jumek.v1i1.43.

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In keeping with the times today that in the management of human resources ef ectively, every organization is absolutely necessary to create a human resources information system for the development of information systems could affect decision-making in an institution. Expected decision- making is a process towards better so with pegetahuan accruing from the information system will add to the discourse, consideration and finally decided appropriately. For information system consists of components supporting educational institutions to provide information needed by decision-makers when making educational activities

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Morozov, A. O. "Decision-making. Terms and definitions." Mathematical machines and systems 2 (2022): 64–67. http://dx.doi.org/10.34121/1028-9763-2022-2-64-67.

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Decision-making is directly connected with purposeful human activity. All people are engaged in this process on a daily basis both personally and using automatic or automated systems. The paper considers the issues of decision-making technology in automatic and automated systems, identifies the main stages of decision making: data – information – knowledge – decision making – decision implementation. There are defined terms «data», «information», «knowledge», «decision», «implementation» which are used at the stages of decision making and decision implementation in automated and automatic control systems. In the paper, there are provided definitions of automatic and automated systems, robots as a separate class of automatic systems, as well as the next stage of development of robots – self-organizing automatic machines which are independently configured to perform various target functions based on the rules of acquiring knowledge. Some features of large systems such as industry or state are noted. For such systems, it is impossible to get all the necessary data about the processes that take place in them. Therefore, the information obtained as a result of their processing will not provide enough knowledge for decision-making on system management. Missing knowledge can be obtained thanks to the unformalized knowledge of people. The definition of unformalized knowledge is provided as well. The paper forms the principles of building automated and automatic systems using artificial intelligence and describes the sequence of control processes in any automatic or automated control system

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Țîrlea, Anca Victoria, Claudiu Vasile Kifor, and Florin Cristian Țîrlea. "Integrated Neuronal Network in ERP for Management Decision Making." Balkan Region Conference on Engineering and Business Education 1, no. 1 (October 1, 2019): 206–12. http://dx.doi.org/10.2478/cplbu-2020-0024.

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AbstractEnterprise Resource Planning systems have proven to be efficient and have become a de facto standard for coordinating vital business components. However, the obvious question has arisen: if each company uses the same ERP system, what happens to the competitive aspect of the business after the implementation of the IT systems?While for some organizations, ERPs have only become a necessity for running and organizing business, others want to exploit it to exceed the performance of competitors.Consequently, ERP systems are often a combined solution between the legacies of the systems they have replaced and the model proposed by the ERP provider, resulting in systems with unique, customized features. Keeping this idea, we aim to add to the present paper elements of artificial intelligence within a module for managing car sales within an ERP.

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Asadi, Mounes, Hamed Fazlollahtabar, and Babak Shirazi. "An Enterprise Management Decision Making System based on Possibility Theory." International Journal of Enterprise Information Systems 11, no. 4 (October 2015): 1–27. http://dx.doi.org/10.4018/ijeis.2015100101.

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One of the substantial problems in large scale enterprises is lack of the integrity of the operational systems. The information flow among different departments is aiming at integrating data, applications and business processes in an organizational platform. In this research, the authors propose to design a process of decision support system for the integration of three corporate units: purchasing, sales and production. Here, they examine the process in two steps of information flow in each enterprise unit for decision making. While in the second step and according to data from the previous step and due to the uncertainty in the enterprise data it was determined to implement the rules of the system by the possibility theory. Thereby, the events that have effective role in the integrity of organization for each unit are known and enterprise should focus on them to achieve goals. Also, to use actual data of enterprise and to be able to use the results of the work objectively, the authors conducted a case study for implementation purpose.

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Bulger, Dan, and Harold Hunt. "The forest management decision support system project." Forestry Chronicle 67, no. 6 (December 1, 1991): 622–28. http://dx.doi.org/10.5558/tfc67622-6.

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The focus of a decision support system is much different from Management Information Systems (MIS) and data-based "decision support systems". Decision support systems, as defined by the authors, focus on decisions and decision makers, and on information. Technology is treated as a tool and data as the raw material. In many traditional systems the focus is on the technology, and the data is the "information", while decision makers are, to some extent, externalized.The purpose of the Forest Management Decision Support System (FMDSS) project is to develop a set of software tools for creating forest management decision support systems. This set of tools will be used to implement a prototype forest management decision support system for the Plonski forest, near Kirkland Lake, Ontario.There are three critical ingredients in building the FMDSS, these are: (1) knowledge of the decision making process, (2) knowledge of the forest, and (3) the functionality of underlying support technology. The growing maturity of the underlying technology provides a tremendous opportunity to develop decision support tools. However, a significant obstacle to building FMDSS has been the diffuse nature of knowledge about forest management decision making processes, and about the forest ecosystem itself. Often this knowledge is spread widely among foresters, technicians, policy makers, and scientists, or is in a form that is not easily amenable to the decision support process. This has created a heavy burden on the project team to gather and collate the knowledge so that it could be incorporated into the function and design of the system. It will be difficult to gauge the success of this exercise until users obtain the software and begin to experiment with its use.

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Barr, Thomas R. "Critical Decision Making: The Decision to Deploy a Clinical Management System, Part 2." Journal of Oncology Practice 1, no. 3 (September 2005): 118–23. http://dx.doi.org/10.1200/jop.2005.1.3.118.

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Barr, T. R. "Critical Decision Making: The Decision to Deploy a Clinical Management System, Part 2." Journal of Oncology Practice 1, no. 3 (September 1, 2005): 118–23. http://dx.doi.org/10.1200/jop.1.3.118.

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Noonan-Wright, Erin K., Tonja S. Opperman, Mark A. Finney, G. Thomas Zimmerman, Robert C. Seli, Lisa M. Elenz, David E. Calkin, and John R. Fiedler. "Developing the US Wildland Fire Decision Support System." Journal of Combustion 2011 (2011): 1–14. http://dx.doi.org/10.1155/2011/168473.

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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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KAGAYA, Seiichi, and Etsuo YAMAMURA. "Support system of decision-making for management of river environment." ENVIRONMENTAL SYSTEMS RESEARCH 19 (1991): 124–29. http://dx.doi.org/10.2208/proer1988.19.124.

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D’Angelo, Letizia, Noel Finnerty, Federico Seri, Alessandro Piccinini, Ronan Coffey, Carlos Tighe, PJ Mealy, Marc Mellotte, and Marcus Keane. "A Global Energy Management System to Support Sustainable Decision Making." Proceedings 20, no. 1 (August 6, 2019): 22. http://dx.doi.org/10.3390/proceedings2019020022.

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Global energy consumption has risen enormously over the past century due to population growth and increasing energy use per person. Industrial production consumes a significant portion of global energy resources. Thus, industrial sector’s investment in energy efficiency is critical to a sustainable future. For most global enterprises the consumption of energy and natural resources represents a major overhead and developing sustainable energy policies can represent a significant competitive advantage due to the growing price of energy and volatility of supply. This symbiotic relationship can lead to the mutual benefits of increasing industrial efficiency whilst allowing the transition to a sustainable renewables-based energy future and needs to be significantly harnessed. This paper describes a decision support framework to help industrial organisations make positive investment decisions on energy performance improvement projects.

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Marengoni, M., A. Hanson, S. Zilberstein, and E. Riseman. "Decision making and uncertainty management in a 3D reconstruction system." IEEE Transactions on Pattern Analysis and Machine Intelligence 25, no. 7 (July 2003): 852–58. http://dx.doi.org/10.1109/tpami.2003.1206514.

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Terrada, Loubna, Mohamed El Khaïli, and Hassan Ouajji. "Multi-Agents System Implementation for Supply Chain Management Making-Decision." Procedia Computer Science 177 (2020): 624–30. http://dx.doi.org/10.1016/j.procs.2020.10.089.

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Amador-Jiménez, Luis Esteban, and Amir Pooyan Afghari. "Non-monetised multi-objective decision making system for road management." International Journal of Pavement Engineering 14, no. 7 (October 2013): 686–96. http://dx.doi.org/10.1080/10298436.2012.727995.

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Cho, Young-Seok, Jong-In Im, and Kyung-Ho Lee. "A Study on Decision Making Process of System Access Management." Journal of the Korea Institute of Information Security and Cryptology 25, no. 1 (February 28, 2015): 225–35. http://dx.doi.org/10.13089/jkiisc.2015.25.1.225.

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45

Forgionne, Guisseppi A., and Rajiv Kohli. "HMSS: a management support system for concurrent hospital decision making." Decision Support Systems 16, no. 3 (March 1996): 209–29. http://dx.doi.org/10.1016/0167-9236(95)00011-9.

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Kurennykh, A., V. Sudakov, and A. Batkovsky. "Optimal Management Decision-making in Choice of the Best ERP System." Bulletin of Science and Practice 6, no. 3 (March 15, 2020): 23–31. http://dx.doi.org/10.33619/2414-2948/52/02.

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In this paper, the authors propose an effective and understandable method for substantiating and choosing the optimal corporate information system for an enterprise. The authors offer a number of essential criteria that ensure the completeness and sufficiency of information for making the optimal (rational) decision on the suitability of the corporate information system for the enterprise. Such criteria include the scale of the information system, its cost, functional characteristics, the ability to integrate with related systems, setup and development time, and ease of support at all stages of the life cycle. The estimation method is based on the use of the mathematical apparatus of decision theory. The mathematical approach to the assessment of information system options allows us to ensure the accuracy of estimates when it is possible to process both qualitative and quantitative judgments of experts, users and the management team. In the software implementation of these methods, the authors focused on the use of web services that are convenient to use, easy to integrate and do not impose restrictions on the applied and system software used by the expert in evaluating information systems. An important place in the software implementation is occupied by checking the quality and correctness of the source data – an error in the initial judgments of the evaluating person can lead to incorrect decisions, it is this fact that allows one to make optimal or close to optimal decisions.

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KUPPURAJU, N., S. GANESAN, F. MISTREE, and J. S. SOBIESKI. "HIERARCHICAL DECISION MAKING IN SYSTEM DESIGN." Engineering Optimization 8, no. 3 (January 1985): 223–52. http://dx.doi.org/10.1080/03052158508902491.

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Ayyub, Bilal M., Peter G. Prassinos, and John Etherton. "Risk-informed Decision Making." Mechanical Engineering 132, no. 01 (January 1, 2010): 28–33. http://dx.doi.org/10.1115/1.2010-jan-2.

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This article presents an overview of the need for inclusion of an effective risk analysis program in a product’s lifecycle. Risk-based technologies (RBT) are tools and processes used to assess and manage the risks of a component—or even of an entire system. One RBT method is risk assessment, which consists of hazard identification, scenario-probability assessment, and consequence assessment. Another method is risk control, which uses failure prevention and consequence mitigation, as well as risk communication. Risk can be quantified by estimating probabilities and consequences in a qualitative manner using expert opinion and communicated using matrices for preliminary screening. There are four primary ways available to deal with risk within the context of a risk management strategy: risk reduction or elimination, risk transfer, risk avoidance, and risk absorbance or pooling. The use of tools such as risk analysis helps enable decision makers to be as informed on the risks involved with each choice as they are with other important parameters of the system such as strategic importance, schedule criticality, cost, and customer satisfaction.

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Huang, Zhecheng. "Intelligent Decision-Making Model of Enterprise Management Based on Random Forest Algorithm." Mobile Information Systems 2022 (May 9, 2022): 1–11. http://dx.doi.org/10.1155/2022/6184106.

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With the sustained and rapid development of China’s economy, the business environment of enterprises is becoming more and more complicated. Coupled with the increasing international competitive pressure of enterprises, the management of enterprises needs more attention. The emergence of DSS provides an opportunity for enterprise management intelligent decision-making. Based on the in-depth study of RF algorithm, this paper proposes a new intelligent decision-making model for enterprise management, aiming at the shortcomings of traditional decision-making systems. In this paper, the decision-making process of the system for decision support is given. Through the quantification and evaluation of various data by subsystems, the best decision-making scheme with strong operability is provided for enterprises. And this model can effectively solve the problem of heterogeneity, duplication and clutter of data in traditional database, and avoid the loss of historical data. Through simulation, the accuracy of this system can reach 96%, which is about 17% higher than other systems. It has certain practicability and feasibility. It is hoped that the research in this paper will play an important role and service support for enterprise intelligent decision-making and further promote the development of intelligent enterprise management decision-making system in China.

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Podskrebko, O. S. "Developing the Structure of Decision-Making Support System for Management of the Production Logistics of an Industrial Enterprise." Business Inform 4, no. 495 (2019): 139–46. http://dx.doi.org/10.32983/2222-4459-2019-4-139-146.

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