IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v185y2021icp1-16.html
   My bibliography  Save this article

FPGA based effective agriculture productivity prediction system using fuzzy support vector machine

Author

Listed:
  • Prabakaran, G.
  • Vaithiyanathan, D.
  • Ganesan, Madhavi

Abstract

This work investigates the functions of hardware-implemented intelligent decision support system using support vector machines. The system aims to forecast future productivity based on the data prepared by field experts followed by productivity influence factors. This feature is perceived by the combination of fuzzy logic and support vector machine. The proposed approach has been thoroughly tested at a ground level, and the designed structural test results have made major improvements compared to the lack of proper approach. This system proposed to compensate for performance decrease, achieved higher productivity with a prediction accuracy of 95%. Furthermore, the proposed intelligent embedded decision support system provided the deficit level of needed input scale to increase productivity and avoid excess consumption of fertilizer in agriculture. A 30-year climate parameter has been taken into account to establish such a system to control the consumption of fertilizers.

Suggested Citation

  • Prabakaran, G. & Vaithiyanathan, D. & Ganesan, Madhavi, 2021. "FPGA based effective agriculture productivity prediction system using fuzzy support vector machine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 1-16.
    • Handle: RePEc:eee:matcom:v:185:y:2021:i:c:p:1-16
    DOI: 10.1016/j.matcom.2020.12.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475420304663
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2020.12.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Anar, Mohammad J. & Lin, Zhulu & Hoogenboom, Gerrit & Shelia, Vakhtang & Batchelor, William D. & Teboh, Jasper M. & Ostlie, Michael & Schatz, Blaine G. & Khan, Mohamed, 2019. "Modeling growth, development and yield of Sugarbeet using DSSAT," Agricultural Systems, Elsevier, vol. 169(C), pages 58-70.
    2. Kiiza, Barnabas & Pederson, Glenn, 2012. "ICT-based market information and adoption of agricultural seed technologies: Insights from Uganda," Telecommunications Policy, Elsevier, vol. 36(4), pages 253-259.
    3. Nakano, Satoshi & Washizu, Ayu, 2018. "Induced effects of smart food/agri-systems in Japan: Towards a structural analysis of information technology," Telecommunications Policy, Elsevier, vol. 42(10), pages 824-835.
    4. Chen, Xiaoping & Qi, Zhiming & Gui, Dongwei & Sima, Matthew W. & Zeng, Fanjiang & Li, Lanhai & Li, Xiangyi & Gu, Zhe, 2020. "Evaluation of a new irrigation decision support system in improving cotton yield and water productivity in an arid climate," Agricultural Water Management, Elsevier, vol. 234(C).
    5. McCown, R. L., 2002. "Changing systems for supporting farmers' decisions: problems, paradigms, and prospects," Agricultural Systems, Elsevier, vol. 74(1), pages 179-220, October.
    6. Yongli Zhang & Sanggyun Na, 2018. "A Novel Agricultural Commodity Price Forecasting Model Based on Fuzzy Information Granulation and MEA-SVM Model," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-10, November.
    7. Helin Yin & Yeong Hyeon Gu & Chang-Jin Park & Jong-Han Park & Seong Joon Yoo, 2020. "Transfer Learning-Based Search Model for Hot Pepper Diseases and Pests," Agriculture, MDPI, vol. 10(10), pages 1-16, September.
    8. Mar-Ortiz, Julio & Castillo-García, Norberto & Gracia, María D., 2020. "A decision support system for a capacity management problem at a container terminal," International Journal of Production Economics, Elsevier, vol. 222(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ahmed, Moiz Uddin & Hussain, Iqbal, 2022. "Prediction of Wheat Production Using Machine Learning Algorithms in northern areas of Pakistan," Telecommunications Policy, Elsevier, vol. 46(6).
    2. Nur Adibah Mohidem & Nik Norasma Che’Ya & Abdul Shukor Juraimi & Wan Fazilah Fazlil Ilahi & Muhammad Huzaifah Mohd Roslim & Nursyazyla Sulaiman & Mohammadmehdi Saberioon & Nisfariza Mohd Noor, 2021. "How Can Unmanned Aerial Vehicles Be Used for Detecting Weeds in Agricultural Fields?," Agriculture, MDPI, vol. 11(10), pages 1-27, October.
    3. Ustaoglu, E. & Sisman, S. & Aydınoglu, A.C., 2021. "Determining agricultural suitable land in peri-urban geography using GIS and Multi Criteria Decision Analysis (MCDA) techniques," Ecological Modelling, Elsevier, vol. 455(C).
    4. Bitopi Biswas & Mohammad Tariful Alam Khan & Mohammad Billal Hossain Momen & Mohammad. Rashedur Rahman Tanvir & Abu Mohammad Shahidul Alam & M Robiul Islam Islam, 2024. "Advancements in fuzzy expert systems for site-specific nitrogen fertilisation: Incorporating RGB colour codes and irrigation schedules for precision maize production in Bangladesh," Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 70(3), pages 155-166.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mompremier, R. & Her, Y. & Hoogenboom, G. & Migliaccio, K. & Muñoz-Carpena, R. & Brym, Z. & Colbert, R.W. & Jeune, W., 2021. "Modeling the response of dry bean yield to irrigation water availability controlled by watershed hydrology," Agricultural Water Management, Elsevier, vol. 243(C).
    2. Maren Radeny & Elizaphan J. O. Rao & Maurice Juma Ogada & John W. Recha & Dawit Solomon, 2022. "Impacts of climate-smart crop varieties and livestock breeds on the food security of smallholder farmers in Kenya," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(6), pages 1511-1535, December.
    3. Gary Bentrup & Michael G. Dosskey, 2022. "Tree Advisor: A Novel Woody Plant Selection Tool to Support Multifunctional Objectives," Land, MDPI, vol. 11(3), pages 1-23, March.
    4. McCown, R. L., 2002. "Locating agricultural decision support systems in the troubled past and socio-technical complexity of `models for management'," Agricultural Systems, Elsevier, vol. 74(1), pages 11-25, October.
    5. Hua, Ye, 2015. "Influential factors of farmers' demands for agricultural science and technology in China," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 249-254.
    6. Qi Zhang & Yi Hu & Jianbin Jiao & Shouyang Wang, 2022. "Exploring the Trend of Commodity Prices: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(15), pages 1-22, August.
    7. Muhammad Ismail Kumbhar & Zareen Khan Rind & Faisal Khan Chang & Nadia Baloch & Summaya Baloch, 2019. "Effect of Climate Change on the Livelihood of Coastal Areas of Taluka Sonmaini, District Lasbela, Balochistan," International Journal of Environmental Sciences & Natural Resources, Juniper Publishers Inc., vol. 21(1), pages 21-29, August.
    8. Berrueta, Cecilia & Giménez, Gustavo & Dogliotti, Santiago, 2021. "Scaling up from crop to farm level: Co-innovation framework to improve vegetable farm systems sustainability," Agricultural Systems, Elsevier, vol. 189(C).
    9. Rossing, Walter A.H. & Albicette, Maria Marta & Aguerre, Veronica & Leoni, Carolina & Ruggia, Andrea & Dogliotti, Santiago, 2021. "Crafting actionable knowledge on ecological intensification: Lessons from co-innovation approaches in Uruguay and Europe," Agricultural Systems, Elsevier, vol. 190(C).
    10. Martin, G. & Duru, M. & Schellberg, J. & Ewert, F., 2012. "Simulations of plant productivity are affected by modelling approaches of farm management," Agricultural Systems, Elsevier, vol. 109(C), pages 25-34.
    11. Vayssières, Jonathan & Bocquier, François & Lecomte, Philippe, 2009. "GAMEDE: A global activity model for evaluating the sustainability of dairy enterprises. Part II - Interactive simulation of various management strategies with diverse stakeholders," Agricultural Systems, Elsevier, vol. 101(3), pages 139-151, July.
    12. Shen, Zhiyang & Wang, Songkai & Boussemart, Jean-Philippe & Hao, Yu, 2022. "Digital transition and green growth in Chinese agriculture," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    13. Sterk, B. & van Ittersum, M.K. & Leeuwis, C. & Rossing, W.A.H. & van Keulen, H. & van de Ven, G.W.J., 2006. "Finding niches for whole-farm design models - contradictio in terminis?," Agricultural Systems, Elsevier, vol. 87(2), pages 211-228, February.
    14. Guo, Jianxin & Jin, Songqing & Chen, Lei & Wang, Min & Zhang, Junfeng & Sun, Sufen, 2015. "The Effects of Distance Education on Agricultural Performance and Household Income: Evidence from Suburban Beijing," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205754, Agricultural and Applied Economics Association.
    15. Carberry, P. S. & Hochman, Z. & McCown, R. L. & Dalgliesh, N. P. & Foale, M. A. & Poulton, P. L. & Hargreaves, J. N. G. & Hargreaves, D. M. G. & Cawthray, S. & Hillcoat, N. & Robertson, M. J., 2002. "The FARMSCAPE approach to decision support: farmers', advisers', researchers' monitoring, simulation, communication and performance evaluation," Agricultural Systems, Elsevier, vol. 74(1), pages 141-177, October.
    16. M. G. P. P. Mahindarathne & Qingfei Min, 2019. "Factors that Influence Farmers’ Information Seeking Behaviour: A Study of Sri Lankan Vegetable Farmers," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 1-15, September.
    17. Roberto Louis Forestal & Shih-Ming Pi, 2021. "Using Artificial Neural networks and Optimal Scaling Model to Forecast Agriculture Commodity Price: An Ecological-economic Approach," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 11(3), pages 1-3.
    18. Ogada, Maurice Juma & Rao, Elizaphan J.O. & Radeny, Maren & Recha, John W. & Solomon, Dawit, 2020. "Climate-smart agriculture, household income and asset accumulation among smallholder farmers in the Nyando basin of Kenya," World Development Perspectives, Elsevier, vol. 18(C).
    19. Roy, Debjit & van Ommeren, Jan-Kees & de Koster, René & Gharehgozli, Amir, 2022. "Modeling landside container terminal queues: Exact analysis and approximations," Transportation Research Part B: Methodological, Elsevier, vol. 162(C), pages 73-102.
    20. Matthews, K.B. & Wright, I.A. & Buchan, K. & Davies, D.A. & Schwarz, G., 2006. "Assessing the options for upland livestock systems under CAP reform: Developing and applying a livestock systems model within whole-farm systems analysis," Agricultural Systems, Elsevier, vol. 90(1-3), pages 32-61, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:matcom:v:185:y:2021:i:c:p:1-16. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.