Prediction of Rainfall Using Intensified Lstm and Rule based Crop Recommendation Over Drought Period
| dc.contributor.guide | Pushpalatha M | |
| dc.coverage.spatial | ||
| dc.creator.researcher | Poornima S | |
| dc.date.accessioned | 2021-09-03T05:04:46Z | |
| dc.date.available | 2021-09-03T05:04:46Z | |
| dc.date.awarded | ||
| dc.date.completed | 2021 | |
| dc.date.registered | ||
| dc.description.abstract | Weather forecasting is an essential part of several applications such as marine, air traffic, newlinemilitary, etc., to take preventive measures on the unusual situation due to nature. newlineAgriculture is an important application that relies majorly on several climatic factors like newlinerainfall, temperature, humidity, etc., for successful growth of crops. It is one of the main newlinesectors that decides the socio-economic status of a country as well. Hence it is imperative newlineto analyse the climatic data efficiently in order to reduce the risk of crop failures. Data newlineanalysis will assist in forecasting various weather parameters from which appropriate newlinedecisions can be made for future actions newline | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | DVD | |
| dc.format.dimensions | ||
| dc.format.extent | ||
| dc.identifier.uri | http://hdl.handle.net/10603/338861 | |
| dc.language | English | |
| dc.publisher.institution | Department of Computer Science Engineering | |
| dc.publisher.place | Kattankulathur | |
| dc.publisher.university | SRM University | |
| dc.relation | ||
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Computer Science | |
| dc.subject.keyword | Computer Science Hardware and Architecture | |
| dc.subject.keyword | Engineering and Technology | |
| dc.title | Prediction of Rainfall Using Intensified Lstm and Rule based Crop Recommendation Over Drought Period | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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