scholarly journals DECISION SUPPORT SYSTEM FOR IRRIGATED CROPS GROWERS

2018 ◽  
pp. 38-45
Author(s):  
Alexander Sadovski ◽  
Christov Ilia
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Crop Yields ◽  
Irrigation Management ◽  
Field Trials ◽  
Scientific Management ◽  
Agricultural Field ◽  
Irrigated Crops ◽  
The Individual

Abstract: Against the background of climate change, which reduces water availability in many areas of the world, every year the global Agriculture, the world's largest user of the planet's water resources, spends a huge amount of water without achieving ptimal crop yields. Finding a universally applicable way to ensure the efficient use of irrigation water in agriculture is a real business need and its successful transformation into a fully functional automated decision support system is a technology that can lead to creation of a product, which will be a novelty for irrigation management. The article describes a comprehensive technology that allows scientific management of the state of irrigated crops for virtually any agricultural field that has been tested in long-term field trials and brought to the TRL6 software prototype. The structure of the Decision Support System is presented and links between the individual partial mathematical models and their technological relationship with the databases used are shown.

scholarly journals Weighted Deep Neural Network Based Clinical Decision Support System for the Determination of Fetal Health

2019 ◽  
Vol 8 (4) ◽  
pp. 8564-8569
Keyword(s):  
Neural Network ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Deep Neural Network ◽  
Predictive Analytics ◽  
Clinical Decision ◽  
Svm Classifier ◽  
Healthcare Data ◽  
The Individual

Healthcare industry is undergoing changes at a tremendous rate due to healthcare innovations. Predictive analytics is increasingly being used to diagnose the patient’s ailments and provide actionable insights into already existing healthcare data. The paper looks at a decision support system for determining the health status of the foetus from cardiotographic data using deep learning neural networks. The foetal health records are classified as normal, suspect and pathological. As the multiclass cardiotographic datset of the foetus shows a high degree of imbalance a weighted deep neural network is applied. To overcome the accuracy paradox due to the multiclass imbalance, relevant metrics such as the sensitivity, specificity, F1 Score and Gmean are used to measure the performance of the classifier rather than accuracy. The metrics are applied to the individual classes to ensure that the positive cases are identified correctly. The weighted DNN based classifier is able to classify the positive instances with Gmean score of 91% which is better than than the SVM classifier.

The Warning Decision Support System–Integrated Information

2007 ◽  
Vol 22 (3) ◽  
pp. 596-612 ◽  
Author(s):  
Valliappa Lakshmanan ◽  
Travis Smith ◽  
Gregory Stumpf ◽  
Kurt Hondl
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Severe Weather ◽  
Weather Data ◽  
Spatial Coverage ◽  
Analysis System ◽  
Automated Algorithms ◽  
The Individual ◽  
Integrated Information

Abstract The Warning Decision Support System–Integrated Information (WDSS-II) is the second generation of a system of tools for the analysis, diagnosis, and visualization of remotely sensed weather data. WDSS-II provides a number of automated algorithms that operate on data from multiple radars to provide information with a greater temporal resolution and better spatial coverage than their currently operational counterparts. The individual automated algorithms that have been developed using the WDSS-II infrastructure together yield a forecasting and analysis system providing real-time products useful in severe weather nowcasting. The purposes of the individual algorithms and their relationships to each other are described, as is the method of dissemination of the created products.

scholarly journals Suitability of the Decentralised Wastewater Treatment Effluent for Agricultural Use: Decision Support System Approach

Water ◽  
2021 ◽  
Vol 13 (18) ◽  
pp. 2454
Author(s):  
William Musazura ◽  
Alfred O. Odindo
Keyword(s):  
Wastewater Treatment ◽  
Decision Support ◽  
Decision Support System ◽  
South African ◽  
Support System ◽  
Low Income ◽  
Nutrient Loading ◽  
Crop Yields ◽  
Treated Wastewater ◽  
Agricultural Use

The decentralised wastewater treatment system (DEWATS) is an onsite sanitation technology that can be used in areas away from municipal sewerage networks. The discharge of effluent emanating from DEWATS into water bodies may cause pollution. Agricultural use of the effluent may improve crop yields and quality thereby contributing to food security in low-income communities. There are drawbacks to the agricultural use of treated wastewater. Therefore, the study assessed the crop, environmental and health risks when irrigating with anaerobic filter (AF) effluent using the Decision Support System (DSS) of the South African Water Quality Guideline model, in four South African agroecological regions, three soil types, two irrigation systems and three different crops. The model was parameterised using AF effluent characterisation data and simulated for 45 years. The model predicted that there are no negative impacts for using AF effluent on soil quality parameters (root zone salinity, soil permeability and oxidisable carbon loading), leaf scorching and irrigation equipment. The problems were reported for nutrient loading (N and P) in maize and microbial contamination in cabbage and lettuce. It was recommended that the effluent should be diluted when used for maize production and advanced treatment should be explored to allow unrestricted agricultural use.

scholarly journals A Decision Support System For Integration Of Vendor Selection Task

2011 ◽  
Vol 10 (1) ◽  
pp. 132 ◽  
Author(s):  
Raydel Tullous ◽  
Richard Lee Utecht
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Analytic Hierarchy Process ◽  
Support System ◽  
Selection Task ◽  
Vendor Selection ◽  
Analytic Hierarchy ◽  
Purchasing Decision ◽  
The Individual ◽  
Hierarchy Process

<span>The purpose of this paper is to illustrate the usefulness of a particular decision support system, the Analytic Hierarchy Process (AHP), for developing and implementing integrated procurement systems. The purchasing decision support system (PDSS) proposed in this paper provides each participant involved in the purchasing process with a procedure to communicate their preferences and the reasons for those preferences. All of the participants preferences may be aggregated to determine an overall preference, or in some cases, the results may simply be used to gain a better understanding of the values the individual place on various attributes.</span>

scholarly journals Planning and Managing the Integrated Water System: A Spatial Decision Support System to Analyze the Infrastructure Performances

2020 ◽  
Vol 12 (16) ◽  
pp. 6432
Author(s):  
Michele Grimaldi ◽  
Monica Sebillo ◽  
Giuliana Vitiello ◽  
Vincenzo Pellecchia
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Water System ◽  
Decision Makers ◽  
Spatial Decision Support System ◽  
Human Beings ◽  
Spatial Decision Support ◽  
System A ◽  
The Individual

The demand for water is constantly increasing, while there are factors related to climate change and pollution that make it less and less available. Addressing this problem means being able to face it with a global approach, which takes into account that human beings need water to survive, as well as all the systems on which they rely, namely sanitation, health, education, business, and industry. While human behavior is influenced by the growing awareness on this topic promoted by organizations specifically targeting this mission, the need to protect water resources in operational terms has led mainly to the need for smart urban infrastructure planning, consistent with the objective of promoting sustainable development. To this aim, the authorities in charge of monitoring the implementation of the investment plans by operators need to perform accurate evaluations of the technical quality of the services provided. The present paper introduces a framework to design a Multi-criteria Spatial Decision Support System, conceived to help decision-makers define and analyze the investment priorities of the individual service operators. By building a knowledge model of the network under investigation, decision-makers are aware of physical components of the whole system and are provided with an intervention priority index related to the network objects that could be affected by the planning action to be implemented.

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