HEPAR: An Intelligent System for Hepatitis Prognosis and Liver Transplantation Decision Support

2008 ◽  
pp. 163-180
Author(s):  
Constantinos Koutsojannis ◽  
Andrew Koupparis ◽  
Ioannis Hatzilygeroudis
Keyword(s):  
Liver Transplantation ◽  
Decision Support ◽  
Intelligent System

scholarly journals Deep learning-based decision support system for weeds detection in wheat fields

2022 ◽  
Vol 12 (1) ◽  
pp. 816
Author(s):  
Brahim Jabir ◽  
Noureddine Falih
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Decision Support ◽  
Large Scale ◽  
Intelligent System ◽  
Management Program ◽  
Wheat Crop ◽  
Smart System ◽  
Mechanical Methods ◽  
Hand Weeding

<span>In precision farming, identifying weeds is an essential first step in planning an integrated pest management program in cereals. By knowing the species present, we can learn about the types of herbicides to use to control them, especially in non-weeding crops where mechanical methods that are not effective (tillage, hand weeding, and hoeing and mowing). Therefore, using the deep learning based on convolutional neural network (CNN) will help to automatically identify weeds and then an intelligent system comes to achieve a localized spraying of the herbicides avoiding their large-scale use, preserving the environment. In this article we propose a smart system based on object detection models, implemented on a Raspberry, seek to identify the presence of relevant objects (weeds) in an area (wheat crop) in real time and classify those objects for decision support including spot spray with a chosen herbicide in accordance to the weed detected.</span>

An Intelligent Decision Support System for Sustainable Energy Local Planning

2017 ◽  
pp. 81-100
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Intelligent System ◽  
Sustainable Energy ◽  
Action Plan ◽  
Local Planning ◽  
Development Platform ◽  
Climate Action ◽  
Alternative Scenarios

The main scope of this chapter is to present the “Action3” Decision Support System that integrates the MPC+ approach (Map - Plan - Choose - Check), supporting local and regional authorities to the development, implementation and monitoring of the Sustainable Energy and Climate Action Plan (especially within the framework of the Covenant of Mayors). The proposed intelligent system integrates three main modules, namely the “BEI-Action” for the development of the baseline emission inventory, the “MDS-Action” for the creation and evaluation of the alternative Scenarios of Actions aiming at the identification of the most promising Scenario, as well as the “SEC-Action” for the application of the “Methodological Approach for Monitoring SEC (Sustainable Energy Communities) Targets”. The system was developed using the “Java” programming language and the “NetBeans IDE” software development platform. Particular emphasis was laid on the system's design, so as to be user-friendly, combining intuitive menus and navigation throughout the steps of the system.

Towards an Intelligent System for the Territorial Planning

2018 ◽  
pp. 158-178
Author(s):  
AMRI Benaouda ◽  
Francisco José García-Peñalvo
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Information System ◽  
Decision Support ◽  
Forest Management ◽  
Intelligent System ◽  
Geographical Information ◽  
Territorial Planning ◽  
Ecology And Environment ◽  
Aid Decision

This chapter concerns the conceptualization of an intelligent system for the territorial planning, taking as an example the agriculture case as a tool in decision making. It is started by giving a comparison between the geographical information system (GIS) and the intelligent system (IS), demonstrating the limits of the GIS and the appeal to the artificial intelligence. Also, the chapter gives an overview of the application of decision support systems (DSSs), modeling and simulation applied in forest management, agriculture, ecology, and environment. Finally, the chapter proposes the methodology and the intelligent system proposed, setting up some indicators which help to aid decision making.

Economic assessment of the effectiveness of implementing an intelligent system for educational organizations

2020 ◽  
pp. 221-225
Author(s):  
С.А. Кручинина
Keyword(s):  
Decision Support ◽  
Economic Efficiency ◽  
Return On Investment ◽  
Management System ◽  
Intelligent System ◽  
Investment Project ◽  
Economic Assessment ◽  
Payback Period ◽  
Educational Organizations

Статья посвящена вопросу экономической эффективности внедрения проблемно-ориентированной интеллектуальной системы управления и поддержки принятия решений для образовательных организаций. В частности приведены результаты расчетов, в основе которых лежит методология ROI – оценка возврата инвестиций, позволяющая, в том числе, определить сроки окупаемости инвестиционного проекта. The article is devoted to the economic efficiency of implementing a problem-oriented intellectual management system and decision support for educational organizations. In particular, the results of calculations based on the ROI methodology – an assessment of the return on investment, which allows, among other things, to determine the payback period of an investment project.

An intelligent fuzzy decision system for a flexible manufacturing system with multidecision points

2002 ◽  
Vol 216 (7) ◽  
pp. 1021-1031 ◽  
Author(s):  
F T S Chan ◽  
H K Chan ◽  
A Kazerooni
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Performance Measures ◽  
Support System ◽  
Flexible Manufacturing ◽  
Manufacturing System ◽  
Flexible Manufacturing System ◽  
Intelligent System ◽  
Fuzzy Decision ◽  
Fuzzy Decision Support System

This paper describes an intelligent fuzzy decision support system for real-time scheduling and dispatching of parts in a flexible manufacturing system (FMS), with alternative routing possibilities for all parts. A fuzzy logic approach is developed to improve the system performance by considering multiple performance measures and at multiple decision points. The characteristics of the system status, instead of parts, are fed back to assign priority to the parts waiting to be processed. A simulation model is developed and it is shown that the proposed intelligent fuzzy decision support system keeps all performance measures at a good level. The proposed intelligent system is a promising tool for dealing with scheduling FMSs, in contrast to traditional rules.

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