scholarly journals Benefits and Limitations of Decision Support Systems (DSS) with a Special Emphasis on Weeds

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 548 ◽  
Author(s):  
Panagiotis Kanatas ◽  
Ilias S. Travlos ◽  
Ioannis Gazoulis ◽  
Alexandros Tataridas ◽  
Anastasia Tsekoura ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Weed Management ◽  
Crop Production ◽  
Support Systems ◽  
Management Strategies ◽  
Farming Systems ◽  
Climatic Conditions ◽  
Management Options ◽  
The Right

Decision support systems (DSS) have the potential to support farmers to make the right decisions in weed management. DSSs can select the appropriate herbicides for a given field and suggest the minimum dose rates for an herbicide application that can result in optimum weed control. Given that the adoption of DSSs may lead to decreased herbicide inputs in crop production, their potential for creating eco-friendly and profitable weed management strategies is obvious and desirable for the re-designing of farming systems on a more sustainable basis. Nevertheless, it is difficult to stimulate farmers to use DSSs as it has been noticed that farmers have different expectations of decision-making tools depending on their farming styles and usual practices. The function of DSSs requires accurate assessments of weeds within a field as input data; however, capturing the data can be problematic. The development of future DSSs should target to enhance weed management tactics which are less reliant on herbicides. DSSs should also provide information regarding weed seedbank dynamics in the soil in order to suggest management options not only within a single period but also in a rotational view. More aspects ought to be taken into account and further research is needed in order to optimize the practical use of DSSs for supporting farmers regarding weed management issues in various crops and under various soil and climatic conditions.

Decision Support Systems in Crop Protection

1994 ◽  
Vol 23 (4) ◽  
pp. 281-285 ◽  
Author(s):  
Jonathan D. Knight ◽  
John D. Mumford
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Crop Protection ◽  
Expert Advice ◽  
Management Decision ◽  
Sufficient Information ◽  
Record Keeping ◽  
Pests And Diseases ◽  
The Right

All farmers and growers have at some time faced the decision of whether to control a pest in their crop. In order to make the correct decision the farmer needs access to, and an understanding of, sufficient information relevant to such pest problems. Decision support systems are able to help farmers make these difficult decisions by providing information in an easily understandable and quickly accessed form. The increasing use of computers by farmers for record-keeping and business management is putting the hardware necessary for the implementation of these systems onto more and more farms. The scarcity of expert advice, increasingly complex decisions and reduced economic margins all increase the importance of making the right pest management decision at the right time. It is against this background that decision support systems have an important role to play in the fight against losses caused by pests and diseases.

scholarly journals Contribution of decision support systems to water management improvement in basins with high evaporation in Mediterranean climates

2019 ◽  
Vol 50 (4) ◽  
pp. 1020-1036 ◽  
Author(s):  
Verónica Ruiz-Ortiz ◽  
Santiago García-López ◽  
Abel Solera ◽  
Javier Paredes
Keyword(s):  
Water Management ◽  
Decision Support ◽  
Surface Water ◽  
Decision Support Systems ◽  
Support Systems ◽  
Management Strategies ◽  
Decision Makers ◽  
Basin Management ◽  
Surface Water And Groundwater

Abstract The entry into force of Directive 2000/60/EC of the European Parliament and the Council of 23 October 2000 established a new model for the management and protection of surface water and groundwater in Europe. In this sense, a thorough knowledge of the basins is an essential step in achieving this European objective. The utility of integrative decision support systems (DSS) for decision-making in complex systems and multiple objectives allows decision-makers to identify characteristics and improve water management in a basin. In this research, hydrological and water management resource models have been combined, with the assistance of the DSS AQUATOOL, with the aim of deepening the consideration of losses by evaporation of reservoirs for a better design of the basin management rules. The case study treated is an Andalusian basin of the Atlantic zone (Spain). At the same time, different management strategies are analysed based on the optimization of the available resources by means of the conjunctive use of surface water and groundwater.

Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate

2009 ◽  
Vol 60 (11) ◽  
pp. 1057 ◽  
Author(s):  
Z. Hochman ◽  
H. van Rees ◽  
P. S. Carberry ◽  
J. R. Hunt ◽  
R. L. McCown ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Crop Production ◽  
Management Practices ◽  
Support Systems ◽  
Cost Effective ◽  
Problem Definition ◽  
New Paradigm ◽  
Large Measure ◽  
Internet Service

In Australia, a land subject to high annual variation in grain yields, farmers find it challenging to adjust crop production inputs to yield prospects. Scientists have responded to this problem by developing Decision Support Systems, yet the scientists’ enthusiasm for developing these tools has not been reciprocated by farm managers or their advisers, who mostly continue to avoid their use. Preceding papers in this series described the FARMSCAPE intervention: a new paradigm for decision support that had significant effects on farmers and their advisers. These effects were achieved in large measure because of the intensive effort which scientists invested in engaging with their clients. However, such intensive effort is time consuming and economically unsustainable and there remained a need for a more cost-effective tool. In this paper, we report on the evolution, structure, and performance of Yield Prophet®: an internet service designed to move on from the FARMSCAPE model to a less intensive, yet high quality, service to reduce farmer uncertainty about yield prospects and the potential effects of alternative management practices on crop production and income. Compared with conventional Decision Support Systems, Yield Prophet offers flexibility in problem definition and allows farmers to more realistically specify the problems in their fields. Yield Prophet also uniquely provides a means for virtual monitoring of the progress of a crop throughout the season. This is particularly important for in-season decision support and for frequent reviewing, in real time, of the consequences of past decisions and past events on likely future outcomes. The Yield Prophet approach to decision support is consistent with two important, but often ignored, lessons from decision science: that managers make their decisions by satisficing rather than optimising and that managers’ fluid approach to decision making requires ongoing monitoring of the consequences of past decisions.

scholarly journals A framework for ecological decision support systems: Building the right systems and building the systems right

2001 ◽  
Author(s):  
Frank D'Erchia ◽  
Carl E. Korschgen ◽  
M. Nyquist ◽  
Ralph Root ◽  
Richard S. Sojda ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
The Right

scholarly journals Seleksi Penyerang Utama Menggunakan K-Means Clustering Dan Sistem Pendukung Keputusan Metode Topsis

2017 ◽  
Vol 2 (1) ◽  
pp. 37-48
Author(s):  
Renenata Ardilesmana Siregar
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Selection Process ◽  
Ideal Solution ◽  
Major Player ◽  
The Right ◽  
Selection Of ◽  
The Ideal

Untuk  menentukan penyerang ideal dalam sepak bola agar sesuai karakter dan kriteria yang diharapkan,  diperlukan  pelatih  yang  mempunyai naluri  tajam  dan  juga  sistem  yang  bisa membantu pelatih dalam memberikan pilihan. Biasanya dalam proses penentuan pemain masih dilakukan  secara  manual dengan melihat dari karakter dan kriteria dari pemain tersebut. Tetapi terkadang hanya dengan melihat dari karakter dan kriteria dari pemain tersebut saja masih kurang cukup sehingga jauh dari apa yang diharapkan. Untuk  mempermudah dalam pemilihan penyerang ideal, maka diperlukan suatu sistem yang dapat membantu pelatih untuk  memilih penyerang yang dibutuhkan sesuai dengan kebutuhan tim yaitu dengan menggunakan teknik K-Means Clustering dalam metode data mining sebagai proses dalam menyeleksi pemain untuk bergabung  dalam  suatu  tim  dan  juga  didukung  dengan  metode  Sistem  Pendukung Keputusan (Decision Support Systems) The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) sebagai proses dalam menentukan penyerang yang akan bermain sebagai pemain utama dalam tim yang menggunakan beberapa kriteria untuk  memilih pemain yang tepat. Dengan hasil penelitian ini, diharapkan dapat membantu pelatih dalam proses seleksi pemain dan dapat mengubah cara penilaian terhadap sifat subjektif agar lebih obyektif dalam pengambilan keputusan. Kata Kunci :Data Mining, K-Means Clustering, Sistem Pendukung Keputusan To  determine  the  ideal  attacker  in football to match the expected character and criteria, a  coach who has a sharp instinct and a system that can assist the coach in providing choices. Usually  in  the  process  of  determining  the  player  is  still  done  manually  by  look ing  at  the characters  and  criteria  of  the  player.  But  sometimes just by look ing at the characters and criteria of the player is still not enough so far from what is expected. To facilitate the selection of ideal attackers, a system that can help the trainer to select the attacker needed according to the needs of the team is by using K-Means Clustering technique in the method of data mining as a process in selecting players to join a team and also supported by Decision Support Systems method The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is the process of determining which attack er will play as a major player in the team using multiple criteria to select the right player. With the results of this study, it is expected to assist trainers in the selection process of players and can change the way the assessment of the subjective nature to be more objective in decision making. Keywords: Data Mining, K-Means Clustering, Decision Support System.  

scholarly journals PEMILIHAN BIBIT LELE UNGGUL DENGAN MENGGUNAKAN METODE WEIGHTED PRODUCT

2019 ◽  
Vol 2 (1) ◽  
pp. 15-23
Author(s):  
Dasril Aldo
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Selection Mechanism ◽  
The Right

One method of computing that is quite developed today is the method of decision support systems. A decision support system is required in order to have the ability to process a fast, targeted, and accountable in generating a decision. In the breeding and cultivation of catfish there are types of catfish seedlings are superior and not superior seeds, where the fish seeds should be selected and separated between superior and not superior. In the process of selecting superior catfish seedlings, the right selection mechanism is needed in order to produce the appropriate decisions as expected. The result of this research is the development of decision support system that can help the cultivation of catfish produce decision about the type of superior fish seedlings quickly and precisely.

An Overview of Efforts to Bring Clinical Knowledge to the Point of Care

2005 ◽  
pp. 285-296
Author(s):  
Dean F. Sittig
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Point Of Care ◽  
Clinical Decision Support Systems ◽  
Clinical Information ◽  
Clinical Decision ◽  
Clinical Knowledge ◽  
The Right

By bringing people the right information in the right format at the right time and place, state of the art clinical information systems with imbedded clinical knowledge can help people make the right clinical decisions. This chapter provides an overview of the efforts to develop systems capable of delivering such information at the point of care. The first section focuses on “library-type” applications that enable a clinician to look-up information in an electronic document. The second section describes a myriad of “real-time clinical decision support systems.” These systems generally deliver clinical guidance at the point of care within the clinical information system (CIS). The third section describes several “hybrid” systems, which combine aspects of real-time clinical decision support systems with library-type information. Finally, section four provides a brief look at various attempts to bring clinical knowledge, in the form of computable guidelines, to the point of care.be sufficiently expressive to explicitly capture the design rational (process and outcome intentions) of the guideline’s author, while leaving flexibility at application time to the attending physician and their own preferred methods.” (Shahar, 2001)

Crop growth models for decision support systems

1996 ◽  
Vol 76 (1) ◽  
pp. 9-19 ◽  
Author(s):  
Y. W. Jame ◽  
H. W. Cutforth
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Crop Production ◽  
Systems Approach ◽  
Support Systems ◽  
Growth Models ◽  
Crop Growth ◽  
Agricultural Management ◽  
Knowledge Based ◽  
Crop Growth Models

Studies on crop production are traditionally carried out by using conventional experience-based agronomic research, in which crop production functions were derived from statistical analysis without referring to the underlying biological or physical principles involved. The weaknesses and disadvantages of this approach and the need for greater in-depth analysis have long been recognized. Recently, application of the knowledge-based systems approach to agricultural management has been gaining popularity because of our expanding knowledge of processes that are involved in the growth of plants, coupled with the availability of inexpensive and powerful computers. The systems approach makes use of dynamic simulation models of crop growth and of cropping systems. In the most satisfactory crop growth models, current knowledge of plant growth and development from various disciplines, such as crop physiology, agrometeorology, soil science and agronomy, is integrated in a consistent, quantitative and process-oriented manner. After proper validation, the models are used to predict crop responses to different environments that are either the result of global change or induced by agricultural management and to test alternative crop management options.Computerized decision support systems for field-level crop management are now available. The decision support systems for agrotechnology transfer (DSSAT) allows users to combine the technical knowledge contained in crop growth models with economic considerations and environmental impact evaluations to facilitate economic analysis and risk assessment of farming enterprises. Thus, DSSAT is a valuable tool to aid the development of a viable and sustainable agricultural industry. The development and validation of crop models can improve our understanding of the underlying processes, pinpoint where our understanding is inadequate, and, hence, support strategic agricultural research. The knowledge-based systems approach offers great potential to expand our ability to make good agricultural management decisions, not only for the current climatic variability, but for the anticipated climatic changes of the future. Key words: Simulation, crop growth, development, management strategy

scholarly journals Decision Support Systems For Strategic Dispute Resolution

2011 ◽  
Vol 15 (4) ◽  
pp. 13
Author(s):  
Anurag Agarwal ◽  
Sridhar Ramamoorti ◽  
Vaidyanathan Jayaraman
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Dispute Resolution ◽  
Support Systems ◽  
Management Strategies ◽  
Relevant Information ◽  
Litigation Risk ◽  
Risk Management Strategies ◽  
Alliance Partners ◽  
Out Of Pocket Expenses

Disputes and lawsuits are quite common in business and are often a source of significant liabilities. We conjecture that measurement challenges and lack of adequate analysis tools have greatly inhibited the ability of the General Counsels offices in selecting the best mode for the resolution (i.e. litigation vs. out-of-court settlement) of business conflicts and disputes. Easily quantified direct costs (e.g., out-of-pocket expenses related to pursuing and defending against litigation) tend to be considered, whereas the more difficult-to-quantify indirect risks and costs (e.g., damaged relationships with customers and potential alliance partners, including reputational harm) which may be quite significant, tend to be ignored. We also hypothesize that the benefits of Alternative Dispute Resolution (ADR) strategies may have been muted because of the failure to assess the real magnitude of not-easily-quantified indirect risks and costs. We propose two Decision Support Systems (DSSs), one for a macro-level analysis and one for a micro-level (i.e. case by case analysis), to alleviate the measurement and analysis problem. In the proposed DSSs, the underlying decision engine makes use of operations research tools such as decision trees, logic modeling, Monte-Carlo Markov-Chain (MCMC) and fuzzy logic simulations. By providing the means to gather decision-relevant information, especially on difficult-to-measure soft costs, we have attempted to reduce the decision making risk for the General Counsels offices. In the process, we have also furnished some ways to reach more informed assessments to support litigation risk management strategies and decisions.

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