Assessment of Machine Learning Algorithms for Network Intrusion Detection 
Mayur Sonthalia1, Jayavignesh Thyagarajan2
1Mayur Sonthalia, Electronics and Computer Engineering, School of Electronics Engineering, Vellore Institute of Technology, Chennai, India.
2Jayavignesh Thyagarajan*, School of Electronics Engineering, Vellore Institute of Technology, Chennai, India.
Manuscript received on March 28, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 1667-1671 | Volume-9 Issue-4, April 2020. | Retrieval Number: D8689049420/2020©BEIESP | DOI: 10.35940/ijeat.D8689.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: : in the study of agricultural land, the priority is the use of remote monitoring techniques using unmanned aerial vehicles, technological portable devices. Obtaining materials by remote methods will expand the possibilities of introducing grazing livestock, increase the yield and thereby improve the efficiency of production indicators. The article considers the issues of assessing the nutritional value of pasture fodder, in particular, the amino acid composition in combination with the vegetation index in the conditions of pasture livestock raising in the Stavropol Territory. Productive qualities of replacement young animals directly depend on the quality of feed. Monitoring the amino acid composition of feeds allows you to optimize the technology of growing sheep, taking into account their productivity direction. The combination of remote methods for assessing the vegetation index and the in-depth composition of the nutritional value of feeds makes it possible to optimize the production schedule for the use of pasture plots by various sex and age groups of animals and increase the average daily gain in live weight of young fattening groups by 8-10%. It has been shown that the introduction of top-dressing with roughage in especially dry periods contributes to preserve of animal growth energy when changing grazing areas. Remote assessment of pasture vegetation was carried out using a special camera to calculate the NDVI (Normalized Difference Vegetation Index), which was installed on an unmanned aerial vehicle. At the same time, the dynamics of the NDVI using a portable manual nitrogen sensor was studied in the same pasture plots. The obtained results of monitoring of the vegetative index on pasture plots were compared with the results of chemical analysis of plant feed. Information on the availability of gross amount of plant biomass in the fields was used for priority selection of a specific site for grazing animals and optimizing the use of agricultural territories. It was proven that the parameters of the NDVI for the pasture keeping of young sheep should not be lower than 0.4. The development and implementation of innovative methods of aerospace monitoring makes it possible to increase the efficiency of land use and increase the efficiency of grazing.
Keywords: amino acid composition of feed, nutritional value, pasture feed, sheep, vegetation index