FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386004553> ?p ?o ?g. }

• W4386004553 endingPage "667" @default.
• W4386004553 startingPage "658" @default.
• W4386004553 abstract "Machine learning is an essential tool for crop yield prediction. Crop yield prediction is a challenging task in the agriculture and agronomic field. In crop yield, many factors can impact crop yields such as soil quality, temperature, humidity, quality of the seeds, rainfall, and many more. To give an accurate yield prediction with the right machine learning algorithms we need to process a huge amount with the selections of impactful features. In this study, we performed a systematic literature review to select machine learning methods and features that can analyze large amounts of data and give more accurate results. We discuss the lacking’s of existing research and generated a comparative analysis to give a clear aspect of the better solutions. From a critical evaluation and specific search criteria, we found – papers from AGORA that contain many more different databases such as MDPI, Tylor and Francis, IEEE, etc. From 660 we selected 50 papers from that number that were used more efficiently and gives accurate results with a thorough investigation with the help of our selection criteria and generic research questions that can filter and bring out the more relevant papers regarding these fields. From the selected papers we evaluate the methods, and geographical areas that have been selected for acquiring data analyzed the features, and have a thorough inspection of the selected factors that have the most impact on yield prediction. This study will help future researchers to give a clear understanding of existing research and guide them to generate a more effective model." @default.
• W4386004553 created "2023-08-20" @default.
• W4386004553 creator A5034895200 @default.
• W4386004553 creator A5035313430 @default.
• W4386004553 creator A5040206539 @default.
• W4386004553 creator A5048954062 @default.
• W4386004553 creator A5063007244 @default.
• W4386004553 creator A5069566973 @default.
• W4386004553 date "2023-01-01" @default.
• W4386004553 modified "2023-10-12" @default.
• W4386004553 title "A Systematic Review on Crop Yield Prediction Using Machine Learning" @default.
• W4386004553 cites W2778376722 @default.
• W4386004553 cites W2805142011 @default.
• W4386004553 cites W2885770726 @default.
• W4386004553 cites W2898543370 @default.
• W4386004553 cites W2966050092 @default.
• W4386004553 cites W3125505924 @default.
• W4386004553 cites W3130052012 @default.
• W4386004553 cites W3199475877 @default.
• W4386004553 cites W4200256171 @default.
• W4386004553 cites W4200257808 @default.
• W4386004553 cites W4206381465 @default.
• W4386004553 cites W4207038069 @default.
• W4386004553 cites W4213249651 @default.
• W4386004553 cites W4214495458 @default.
• W4386004553 cites W4214679098 @default.
• W4386004553 cites W4214713085 @default.
• W4386004553 cites W4214860529 @default.
• W4386004553 cites W4220677561 @default.
• W4386004553 cites W4220822157 @default.
• W4386004553 cites W4220888197 @default.
• W4386004553 cites W4221093715 @default.
• W4386004553 cites W4225556963 @default.
• W4386004553 cites W4226087885 @default.
• W4386004553 cites W4281729686 @default.
• W4386004553 cites W4282965679 @default.
• W4386004553 cites W4282973315 @default.
• W4386004553 cites W4283208661 @default.
• W4386004553 cites W4283210400 @default.
• W4386004553 cites W4283642492 @default.
• W4386004553 cites W4292547850 @default.
• W4386004553 cites W4292833879 @default.
• W4386004553 cites W4292994098 @default.
• W4386004553 cites W4293090578 @default.
• W4386004553 cites W4293207334 @default.
• W4386004553 cites W4293919590 @default.
• W4386004553 cites W4294168985 @default.
• W4386004553 cites W4296144079 @default.
• W4386004553 cites W4298139433 @default.
• W4386004553 cites W4298144136 @default.
• W4386004553 cites W4303981410 @default.
• W4386004553 cites W4307117592 @default.
• W4386004553 cites W4307548948 @default.
• W4386004553 cites W4307553313 @default.
• W4386004553 cites W4307944956 @default.
• W4386004553 cites W4308118188 @default.
• W4386004553 cites W4308393900 @default.
• W4386004553 cites W4309003307 @default.
• W4386004553 cites W4309185665 @default.
• W4386004553 cites W4309738963 @default.
• W4386004553 cites W4311720842 @default.
• W4386004553 doi "https://doi.org/10.1007/978-981-99-4725-6_77" @default.
• W4386004553 hasPublicationYear "2023" @default.
• W4386004553 type Work @default.
• W4386004553 citedByCount "0" @default.
• W4386004553 crossrefType "book-chapter" @default.
• W4386004553 hasAuthorship W4386004553A5034895200 @default.
• W4386004553 hasAuthorship W4386004553A5035313430 @default.
• W4386004553 hasAuthorship W4386004553A5040206539 @default.
• W4386004553 hasAuthorship W4386004553A5048954062 @default.
• W4386004553 hasAuthorship W4386004553A5063007244 @default.
• W4386004553 hasAuthorship W4386004553A5069566973 @default.
• W4386004553 hasConcept C111472728 @default.
• W4386004553 hasConcept C111919701 @default.
• W4386004553 hasConcept C118518473 @default.
• W4386004553 hasConcept C119857082 @default.
• W4386004553 hasConcept C127413603 @default.
• W4386004553 hasConcept C134121241 @default.
• W4386004553 hasConcept C138885662 @default.
• W4386004553 hasConcept C154945302 @default.
• W4386004553 hasConcept C166957645 @default.
• W4386004553 hasConcept C191897082 @default.
• W4386004553 hasConcept C192562407 @default.
• W4386004553 hasConcept C201995342 @default.
• W4386004553 hasConcept C202444582 @default.
• W4386004553 hasConcept C205649164 @default.
• W4386004553 hasConcept C2522767166 @default.
• W4386004553 hasConcept C2779530757 @default.
• W4386004553 hasConcept C2780451532 @default.
• W4386004553 hasConcept C33923547 @default.
• W4386004553 hasConcept C41008148 @default.
• W4386004553 hasConcept C81917197 @default.
• W4386004553 hasConcept C88463610 @default.
• W4386004553 hasConcept C9652623 @default.
• W4386004553 hasConcept C98045186 @default.
• W4386004553 hasConceptScore W4386004553C111472728 @default.
• W4386004553 hasConceptScore W4386004553C111919701 @default.
• W4386004553 hasConceptScore W4386004553C118518473 @default.

• next