scholarly journals Possibilities of Farm Management Decision Support

2003 ◽  
pp. 287-292
Author(s):  
Róbert Szilágyi
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Decision Support ◽  
Farm Management ◽  
Management Decision ◽  
Decision Making Process ◽  
The West ◽  
Decision Supporting ◽  
Decision Supporting System ◽  
Management Decision Support

Computer science has a major role in the decision-making process of farmers. In this process IT can be applied to virtually all phase: from infromation gathering to information processing. I am examining the position of informatics in the decision-making process. IT can be used in every single phases of the decision-making process. In my essay the useage of Internet and the possibilities it can provide play a significant role.After a brief description of the IT position of Hungarian agriculture I am introducing some programs, which can be used in the management’s decision-supporting system. Besides the Hungarian experiences the West European surveys also comfirm the application of Information Technology.

scholarly journals Vezetői döntéshozatal és versenyképesség (The managerial decision making and the competitiveness)

2007 ◽  
pp. 18-28
Author(s):  
Zita Zoltayné Paprika ◽  
Ágnes Wimmer ◽  
Richárd Szántó
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Performance Appraisal ◽  
Business Performance ◽  
Management Decision ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
The World ◽  
Decision Supporting ◽  
Management Decision Support

A tanulmány a vezetői döntéshozatal három lényeges aspektusát tárja fel. A Versenyben a világgal c. kutatási program eredményei alapján arra lehet következtetni, hogy a menedzserek döntéshozatali képességei és megközelítései, a vállalati teljesítménymérés és menedzsment döntéseket támogató szerepe, valamint a vállalatok érintettekhez fűződő viszonya meghatározó lehet a hatékony vezetői döntéshozatal során. A vállalati döntéshozatal jellemzőinek bemutatása után megvizsgáljuk azt is, hogy a különböző teljesítményű cégek döntéseit mennyire támogatja a menedzserek felkészültsége, a teljesítménymérési gyakorlat és az érintettek elvárásai. A szerzők úgy találták, hogy a fenti tényezők mindegyike hozzájárul a hazai cégek versenyképességéhez, általánosságban ugyanis elmondható, hogy a döntéseket támogató vállalati környezet jobb üzleti teljesítményhez és gyorsabb reagálóképességhez vezethet. Az eredmények összegzése mellett ajánlásokkal is éltek a vállalatok számára, amelyek alkalmazásával hatékonyabb döntéseket hozhatnak. _______ This study presents three main aspects of the managerial decision making. Based on the results of the research program In competition with the World it points to the fact that decision making abilities and approaches of the managers, the corporate performance appraisal and the management decision support role, and the corporate relations to the stakeholders will be determinant in the process of the efficient managerial decision making. After presentation of characteristics of the corporate decision making the authors examine that how the decisions of enterprises with different performances are supported by the preparedness of the managers, the performance appraisal practice and the stakeholders expectations. The authors have thought that every factor contributes to the competitiveness of the domestic enterprises, and generally the decision supporting corporate environment can lead to better business performance and faster responsive abilities. Besides the results summary the authors give useful recommendations to the corporations with which they can make more efficient decisions.

A Study of Intelligent Decision Supporting System Based on Multi-Agent Exercise Prescription of Psychological Disorder

2014 ◽  
Vol 926-930 ◽  
pp. 1140-1143
Author(s):  
Hui Gao ◽  
Hong Jiang Wu ◽  
Hai Yan Zhao
Keyword(s):  
Decision Making ◽  
Exercise Prescription ◽  
Psychological Disorder ◽  
Decision Making Process ◽  
Supporting System ◽  
Intelligent Decision ◽  
Decision Supporting ◽  
Decision Supporting System ◽  
Multi Agent ◽  
Technical Features

This paper combines the technical features of multi-agent to form the intelligent decision supporting system for exercise prescription of psychological disorder based on multi-agent. And studies for the system decision-making process and system implementation are also presented. Meanwhile, it shows the insufficiency of the intelligent decision supporting system to lay a foundation for the realization of computerization in exercise prescription of psychological disorder.

The forest management decision support system project

1991 ◽  
Vol 67 (6) ◽  
pp. 622-628 ◽  
Author(s):  
Dan Bulger ◽  
Harold Hunt
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Forest Management ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Decision Makers ◽  
Management Decision ◽  
Management Decision Support

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.

Review of classification studies for machine learning in the development of intelligent management decision support systems

2020 ◽  
Vol 89 ◽  
pp. 20-29
Author(s):  
Sh. K. Kadiev ◽  
◽  
R. Sh. Khabibulin ◽  
P. P. Godlevskiy ◽  
V. L. Semikov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Support ◽  
Mathematical Models ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Decision ◽  
Classification Methods ◽  
Advantages And Disadvantages ◽  
Intelligent Management ◽  
Management Decision Support

Introduction. An overview of research in the field of classification as a method of machine learning is given. Articles containing mathematical models and algorithms for classification were selected. The use of classification in intelligent management decision support systems in various subject areas is also relevant. Goal and objectives. The purpose of the study is to analyze papers on the classification as a machine learning method. To achieve the objective, it is necessary to solve the following tasks: 1) to identify the most used classification methods in machine learning; 2) to highlight the advantages and disadvantages of each of the selected methods; 3) to analyze the possibility of using classification methods in intelligent systems to support management decisions to solve issues of forecasting, prevention and elimination of emergencies. Methods. To obtain the results, general scientific and special methods of scientific knowledge were used - analysis, synthesis, generalization, as well as the classification method. Results and discussion thereof. According to the results of the analysis, studies with a mathematical formulation and the availability of software developments were identified. The issues of classification in the implementation of machine learning in the development of intelligent decision support systems are considered. Conclusion. The analysis revealed that enough algorithms were used to perform the classification while sorting the acquired knowledge within the subject area. The implementation of an accurate classification is one of the fundamental problems in the development of management decision support systems, including for fire and emergency prevention and response. Timely and effective decision by officials of operational shifts for the disaster management is also relevant. Key words: decision support, analysis, classification, machine learning, algorithm, mathematical models.

Models of decision support in socio-cyber-physical systems

2019 ◽  
pp. 55-70 ◽  
Author(s):  
A. V. Smirnov ◽  
T. V. Levashova
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Situation Awareness ◽  
Cyber Physical Systems ◽  
Emergent Behavior ◽  
Emergent Properties ◽  
Decision Making Process ◽  
Physical Systems ◽  
Decision Support Models ◽  
Common Goals

Introduction: Socio-cyber-physical systems are complex non-linear systems. Such systems display emergent properties. Involvement of humans, as a part of these systems, in the decision-making process contributes to overcoming the consequences of the emergent system behavior, since people can use their experience and intuition, not just the programmed rules and procedures.Purpose: Development of models for decision support in socio-cyber-physical systems.Results: A scheme of decision making in socio-cyber-physical systems, a conceptual framework of decision support in these systems, and stepwise decision support models have been developed. The decision-making scheme is that cybernetic components make their decisions first, and if they cannot do this, they ask humans for help. The stepwise models support the decisions made by components of socio-cyber-physical systems at the conventional stages of the decision-making process: situation awareness, problem identification, development of alternatives, choice of a preferred alternative, and decision implementation. The application of the developed models is illustrated through a scenario for planning the execution of a common task for robots.Practical relevance: The developed models enable you to design plans on solving tasks common for system components or on achievement of common goals, and to implement these plans. The models contribute to overcoming the consequences of the emergent behavior of socio-cyber-physical systems, and to the research on machine learning and mobile robot control.

Sistem Pendukung Keputusan Untuk Penerimaan Calon Karyawan Outsourcing Dengan Metode Simple Additive Weighting (SAW)

2018 ◽  
Vol 4 (1) ◽  
pp. 29-39 ◽  
Author(s):  
Otto Fajarianto ◽  
Ardiyanto S. Widodo ◽  
Muhammad Iqbal Hanafri ◽  
Arianto ◽  
Arif Muchlisin Fauzi
Keyword(s):  
Decision Making ◽  
Supporting System ◽  
Performance Result ◽  
Decision Supporting ◽  
Decision Supporting System ◽  
Application Data ◽  
Simple Additive Weighting

Decision making on hiring outsourcing employment candidate which still manually has impact on stucking application data, obstacle on placement process and unreal in scoring criteria. In deciding decision needs specific criteria for scoring performance result. This criterion can be standardized in deciding advisable candidate. The purpose of this study is building a decision supporting system, help the company in giving score and choosing new employment. SAW method uses for calculating criteria value base on the highest degree and calculating is taken from normalisation process. The data will be inputted in decision supporting system, and then it will be calculated base on specific criteria. The score from each criterion will be calculated to get the highest score. The result will give recommendation for company in deciding advisable candidate.

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