scholarly journals Predictive Models for Agricultural Management

2021 ◽  
Vol 12 (7) ◽  
pp. 220-225
Author(s):  
Natalia N. Bakhtadze ◽  
◽  
Evgeny M. Maximov ◽  
Natalia E. Maximova ◽  
Lamara N. Kozlovskaya
Keyword(s):  
Decision Support ◽  
Grain Yield ◽  
Decision Support Systems ◽  
Knowledge Base ◽  
Predictive Models ◽  
Agricultural Production ◽  
Support Systems ◽  
Ecological Effect ◽  
The Cost

This paper is devoted to the development of predictive models for decision support systems applied in precision farming. Application of predictive models makes it possible to use resources effectively, which reduces the cost of production and increases the efficiency of agricultural production. In addition, the forecast makes it possible to reach a long-term agronomic and ecological effect due to more careful tillage and reduced use of fertilizers. The algorithms using knowledge base for creating models of grain yield are described and the results of applying these models are presented.

Overview of Decision Support Systems Applied to Construction

2016 ◽  
pp. 77-94
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Markov Decision Processes ◽  
Support Systems ◽  
Decision Processes ◽  
Rule Based ◽  
Markov Decision ◽  
Knowledge Intensive ◽  
The Cost ◽  
Rule Based Systems

The domain of construction is a very knowledge-intensive domain with so many factors involved. This implies undertaking any action requires an understanding of the different factors and how best to combine them to achieve a favourable and optimal outcome. Thus decision-making has been extensively used in the domain of construction. The aim of this chapter is to undertake a review of various decision support systems and to provide insights into their applications in the domain of construction. Specifically, the principle of cost index, sub-work chaining diagram method, linear regression and cost over-runs in time-overrun context (CCOTOV) model and Markov decision processes (MDP), ontology and rule-based systems have been reviewed. Based on the review the Markov decision processes (MDP), ontology and rule-based systems were chosen as the more suitable for the cost control case considered in this study.

scholarly journals Cost and economic benefit of clinical decision support systems for cardiovascular disease prevention: a community guide systematic review

2017 ◽  
Vol 24 (3) ◽  
pp. 669-676 ◽  
Author(s):  
Verughese Jacob ◽  
Anilkrishna B Thota ◽  
Sajal K Chattopadhyay ◽  
Gibril J Njie ◽  
Krista K Proia ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Costs And Benefits ◽  
The Cost

Objective: This review evaluates costs and benefits associated with acquiring, implementing, and operating clinical decision support systems (CDSSs) to prevent cardiovascular disease (CVD). Materials and Methods: Methods developed for the Community Guide were used to review CDSS literature covering the period from January 1976 to October 2015. Twenty-one studies were identified for inclusion. Results: It was difficult to draw a meaningful estimate for the cost of acquiring and operating CDSSs to prevent CVD from the available studies (n = 12) due to considerable heterogeneity. Several studies (n = 11) indicated that health care costs were averted by using CDSSs but many were partial assessments that did not consider all components of health care. Four cost-benefit studies reached conflicting conclusions about the net benefit of CDSSs based on incomplete assessments of costs and benefits. Three cost-utility studies indicated inconsistent conclusions regarding cost-effectiveness based on a conservative $50,000 threshold. Discussion: Intervention costs were not negligible, but specific estimates were not derived because of the heterogeneity of implementation and reporting metrics. Expected economic benefits from averted health care cost could not be determined with confidence because many studies did not fully account for all components of health care. Conclusion: We were unable to conclude whether CDSSs for CVD prevention is either cost-beneficial or cost-effective. Several evidence gaps are identified, most prominently a lack of information about major drivers of cost and benefit, a lack of standard metrics for the cost of CDSSs, and not allowing for useful life of a CDSS that generally extends beyond one accounting period.

Using the Rhizomer Platform for Semantic Decision Support Systems Development

2010 ◽  
Vol 2 (1) ◽  
pp. 60-80 ◽  
Author(s):  
Roberto García
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
User Interaction ◽  
Data Publishing ◽  
Semantic Web Technologies ◽  
Financial Reports ◽  
Semantic Data ◽  
Semantic Decision ◽  
The Cost

Decision support systems get more useful as they manage to make decisions more informed. However, the cost of information and of combining and making it available in the appropriate context make this a tricky trade-off. Fortunately, Semantic Web technologies make it possible to easily publish and reuse data. But this is not simple data, it is semantic data, which makes it easier to query, browse and combine it. Apart from semantic data, it is also important a user interface that carries all this potential to the user. Rhizomer is a framework for semantic data publishing and user interaction that facilitates building semantic dashboards. It is possible, for instance, to build a simple dashboard on top of semantic data generated from financial reports and incorporate web services that provide specialised ways to interact with semantic data, like showing geo-located resources in a map or events in a timeline.

Geospatial Decision Support Systems

2020 ◽  
pp. 163-177
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Development Planning ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Interactive Decision Support

The chapter is on the geospatial decision support systems. Challenges arise when simple GIS is used to support complex problems encountered at higher level, strategic decision-making, and long-term development planning. In this case, SDI can be more valuable. The chapter presents the perspective of information systems for decision support taking into account the following: the levels of decisions and the process of decision making. Trends on the tools and framework for interactive decision support systems are discussed focusing on geospatial decision support systems based on GIS and SDI.

Dynamic reasoning to solve complex problems in activated sludge processes: a step further in decision support systems

2006 ◽  
Vol 53 (1) ◽  
pp. 191-198 ◽  
Author(s):  
M. Martínez ◽  
I. Rodríguez-Roda ◽  
M. Poch ◽  
U. Cortés ◽  
J. Comas
Keyword(s):  
Decision Support ◽  
Activated Sludge ◽  
Decision Support Systems ◽  
Support Systems ◽  
Biological Origin ◽  
Dynamic Reasoning ◽  
Solids Separation ◽  
Activated Sludge Processes ◽  
Separation Problems

Decision support systems (DSS) have generated high expectations as a tool to support activated sludge operation because of their ability to represent heuristic reasoning and to handle large amounts of qualitative, uncertain and low-accuracy data. Previous applications have been satisfactory to control simple problems, when static reasoning and literature-based solutions were enough. However to face complex operational problems with biological origin and slow dynamics (e.g. solids separation problems), it is necessary to use dynamic reasoning and apply long-term control strategies, monitoring the evolution of the process and adjusting the action plan according to the feed back of the process. This paper presents a dynamic reasoning DSS to face solids separation problems in the activated sludge system. The DSS is capable of identifying the complex problem affecting the process, determining if the current situation is new or a continuation from the previous one, assessing what is the specific cause of the situation, and recommending a long-term control strategy, which is daily adjusted according to the evolution of the process.

scholarly journals Using the Rhizomer Platform for Semantic Decision Support Systems Development

2012 ◽  
pp. 62-82
Author(s):  
Roberto García
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
User Interaction ◽  
Data Publishing ◽  
Semantic Web Technologies ◽  
Financial Reports ◽  
Semantic Data ◽  
Semantic Decision ◽  
The Cost

Decision support systems get more useful as they manage to make decisions more informed. However, the cost of information and of combining and making it available in the appropriate context make this a tricky trade-off. Fortunately, Semantic Web technologies make it possible to easily publish and reuse data. But this is not simple data, it is semantic data, which makes it easier to query, browse and combine it. Apart from semantic data, it is also important a user interface that carries all this potential to the user. Rhizomer is a framework for semantic data publishing and user interaction that facilitates building semantic dashboards. It is possible, for instance, to build a simple dashboard on top of semantic data generated from financial reports and incorporate web services that provide specialised ways to interact with semantic data, like showing geo-located resources in a map or events in a timeline.

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