Implementation of a decision support system using an interactive large-scale high-resolution display

2017 ◽  
Vol 22 (3) ◽  
pp. 385-390 ◽  
Author(s):  
Tomoyuki Ishida ◽  
Yusuke Hirohara ◽  
Nobuyuki Kukimoto ◽  
Yoshitaka Shibata
Keyword(s):  
Decision Support ◽  
High Resolution ◽  
Decision Support System ◽  
Support System ◽  
Large Scale

scholarly journals A Decision Support System for Public Funding of Experimental Development in Energy Research

Energies ◽  
2018 ◽  
Vol 11 (6) ◽  
pp. 1357 ◽  
Author(s):  
Simon Hirzel ◽  
Tim Hettesheimer ◽  
Peter Viebahn ◽  
Manfred Fischedick
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Public Funding ◽  
Evaluation Process ◽  
Decision Makers ◽  
Market Failures ◽  
Energy Research ◽  
Experimental Development

New energy technologies may fail to make the transition to the market once research funding has ended due to a lack of private engagement to conclude their development. Extending public funding to cover such experimental developments could be one way to improve this transition. However, identifying promising research and development (R&D) proposals for this purpose is a difficult task for the following reasons: Close-to-market implementations regularly require substantial resources while public budgets are limited; the allocation of public funds needs to be fair, open, and documented; the evaluation is complex and subject to public sector regulations for public engagement in R&D funding. This calls for a rigorous evaluation process. This paper proposes an operational three-staged decision support system (DSS) to assist decision-makers in public funding institutions in the ex-ante evaluation of R&D proposals for large-scale close-to-market projects in energy research. The system was developed based on a review of literature and related approaches from practice combined with a series of workshops with practitioners from German public funding institutions. The results confirm that the decision-making process is a complex one that is not limited to simply scoring R&D proposals. Decision-makers also have to deal with various additional issues such as determining the state of technological development, verifying market failures or considering existing funding portfolios. The DSS that is suggested in this paper is unique in the sense that it goes beyond mere multi-criteria aggregation procedures and addresses these issues as well to help guide decision-makers in public institutions through the evaluation process.

Decision support system for corrective maintenance in large-scale photovoltaic systems

2021 ◽  
Author(s):  
Andreas Livera ◽  
Marios Theristis ◽  
Alexios Charalambous ◽  
Joshua S. Stein ◽  
George E. Georghiou
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Photovoltaic Systems ◽  
Corrective Maintenance

Decision Support System for Wind Farm Installation Using Bipolar Analysis

2015 ◽  
pp. 1-21 ◽  
Author(s):  
Yasmina Bouzarour-Amokrane ◽  
Ayeley P. Tchangani ◽  
François Pérès
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Wind Energy ◽  
Support System ◽  
Large Scale ◽  
Wind Farm ◽  
Negative Impact ◽  
Life Quality ◽  
Energy Projects ◽  
And Performance

The necessity to control and reduce the negative impact of human activities on environment and life quality along with technology progress in renewable energy in general and wind energy in particular render it possible today to consider wind energy projects on a large scale. Developing wind energy on a large scale however raises other problems such as choosing an adequate site to settle a wind farm where many other issues such technical feasibility and performance levels, visual pollution, economic and social concerns, etc. must be addressed. Such decisions usually involve many parameters and necessitate the collaboration of many stakeholders. In this context, this chapter proposes an approach based on the concept of bipolar analysis through Benefit Opportunity Cost and Risk (BOCR) analysis, which permits one to address correctly a Group Decision-Making Problem (GDMP) to build a decision support system in order to assist the wind farm installation process.

Pragmatism in Decision Support System Research

2021 ◽  
pp. 1471-1493
Author(s):  
Mohammad Tafiqur Rahman
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Humanitarian Logistics ◽  
Knowledge Based ◽  
Relief Distribution ◽  
Distribution Process ◽  
Complex Knowledge

Decision making on relief distribution is a complex multidisciplinary task in humanitarian logistics. It incorporates decision makers from different but related problem areas. The failure to perform assigned decision-making tasks in any area makes the entire system unstable and delays the relief distribution process. An organized, well-planned, and practical decision support system (DSS) can assist practitioners in making rapid decisions on delivering relief items. Hence, DSS researchers in humanitarian logistics require rigorous thinking, close and critical analysis, and the identification of challenges to conduct research or validate the generated knowledge properly. To perform such complex knowledge-based tasks, the philosophical understanding of DSS in the humanitarian context is necessary. After analyzing the commonly used philosophical paradigms, this research identifies the pragmatic approach as the adequate support for solving decision-making problems in relief distribution during large-scale disasters.

An Integrated Decision Support System for Intercropping

2010 ◽  
Vol 2 (3) ◽  
pp. 51-66 ◽  
Author(s):  
A. S. Sodiya ◽  
A. T. Akinwale ◽  
K. A. Okeleye ◽  
J. A. Emmanuel
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Crop Production ◽  
Large Scale ◽  
Weather Condition ◽  
Agricultural Practice ◽  
Pests And Diseases ◽  
General Decline ◽  
Fertility Protection

Intercropping, which is the agricultural practice of growing two or more crops in the same land area, is not currently yielding adequate results in Africa. Despite the advantages of intercropping like improved soil fertility, protection against pests and diseases and eventual increase in farm yield, this farming practice is faced with challenges—inadequate planning, bad crop management and lack of required intercropping expertise. Consequently, this has resulted in inadequate reward for farmers and a general decline in crop production. In this regard, the authors present an Intelligent and Integrated Intercropping Decision Support System for Intercropping (IDSS-I) for improved crop production. The design adopts a forecasting component that provides farmers with the estimated yield and income depending on the size of land, soil type and weather condition. Although the implementation was carried out using JAVA and SQL, usability testing revealed 85% acceptance of the tool among the contacted 10 large scale farmers. It was also confirmed that the system provided 95% diagnosis information for 90% common Africa crop diseases.

scholarly journals Transforming Unmanned Aerial Vehicle (UAV) and Multispectral Sensor into a Practical Decision Support System for Precision Nitrogen Management in Corn

2020 ◽  
Vol 12 (10) ◽  
pp. 1597
Author(s):  
Laura J. Thompson ◽  
Laila A. Puntel
Keyword(s):  
Decision Support ◽  
High Resolution ◽  
Decision Support System ◽  
Support System ◽  
Critical Issue ◽  
N Fertilization ◽  
Sensor Data ◽  
N Application ◽  
High Resolution Imagery ◽  
N Management

Determining the optimal nitrogen (N) rate in corn remains a critical issue, mainly due to unaccounted spatial (e.g., soil properties) and temporal (e.g., weather) variability. Unmanned aerial vehicles (UAVs) equipped with multispectral sensors may provide opportunities to improve N management by the timely informing of spatially variable, in-season N applications. Here, we developed a practical decision support system (DSS) to translate spatial field characteristics and normalized difference red edge (NDRE) values into an in-season N application recommendation. On-farm strip-trials were established at three sites over two years to compare farmer’s traditional N management to a split-application N management guided by our UAV sensor-based DSS. The proposed systems increased nitrogen use efficiency 18.3 ± 6.1 kg grain kg N−1 by reducing N rates by 31 ± 6.3 kg N ha−1 with no yield differences compared to the farmers’ traditional management. We identify five avenues for further improvement of the proposed DSS: definition of the initial base N rate, estimation of inputs for sensor algorithms, management zone delineation, high-resolution image normalization approach, and the threshold for triggering N application. Two virtual reference (VR) methods were compared with the high N (HN) reference strip method for normalizing high-resolution sensor data. The VR methods resulted in significantly lower sufficiency index values than those generated by the HN reference, resulting in N fertilization recommendations that were 31.4 ± 10.3 kg ha−1 higher than the HN reference N fertilization recommendation. The use of small HN reference blocks in contrasting management zones may be more appropriate to translate field-scale, high-resolution imagery into in-season N recommendations. In view of a growing interest in using UAVs in commercial fields and the need to improve crop NUE, further work is needed to refine approaches for translating imagery into in-season N recommendations.

A GIS Based Decision Support System for the Cultivation and Management of Eucalypt

2011 ◽  
Vol 403-408 ◽  
pp. 2607-2611
Author(s):  
Xin Wen Yu ◽  
Yan Chen Yang ◽  
Xu Zhang ◽  
Xuan Li ◽  
Ying Wu Li
Keyword(s):  
Decision Support ◽  
Economic Evaluation ◽  
Decision Support System ◽  
Support System ◽  
Large Scale ◽  
Small Scale ◽  
Variety Selection

A GIS based decision support system for eucalypt cultivation and management was developed. The system can help farmers make decision in planting suitability, eucalypt variety selection, planting scheme making etc. The system can also make an economic evaluation for the selected variety so that users can make decision to plant or not. The system supports two groups of users which are eucalypt farmers who cultivate eucalypt in a small scale and forest farms who cultivate eucalypt in a relatively large scale.

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