A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India
This study introduces a novel graph-based innovative trend analysis (GBITA) technique for detecting trends in time series data, thus fundamentally challenging conventional assumptions in trend assessment. Unlike traditional methods, which often rely on the assumption of a serial correlation, the pro...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | AgriEngineering |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2624-7402/7/2/36 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849722557878501376 |
|---|---|
| author | Chalissery Mincy Thomas Archana Nair |
| author_facet | Chalissery Mincy Thomas Archana Nair |
| author_sort | Chalissery Mincy Thomas |
| collection | DOAJ |
| description | This study introduces a novel graph-based innovative trend analysis (GBITA) technique for detecting trends in time series data, thus fundamentally challenging conventional assumptions in trend assessment. Unlike traditional methods, which often rely on the assumption of a serial correlation, the proposed methodology only requires that the data values conform to a non-negative distribution. The effectiveness of GBITA was validated through 200 Monte Carlo simulations, and it was subsequently applied to analyze the productivity and cultivated area of paddy and coconut crops across Kerala and its 14 districts. The results indicate an upward trend in the productivity of both crops; however, the area under paddy cultivation is decreasing, while the coconut cultivation area is increasing. Notably, the southern districts of Kerala exhibited a declining trend in both the productivity and cultivated area for these crops. This innovative approach holds promise for broader applications across various crop varieties and regions, with potential implications for fields such as statistics, economics, and computer science. |
| format | Article |
| id | doaj-art-cbd6e086bff7487e9a3b3bb9cd7d40da |
| institution | DOAJ |
| issn | 2624-7402 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | AgriEngineering |
| spelling | doaj-art-cbd6e086bff7487e9a3b3bb9cd7d40da2025-08-20T03:11:18ZengMDPI AGAgriEngineering2624-74022025-02-01723610.3390/agriengineering7020036A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, IndiaChalissery Mincy Thomas0Archana Nair1Department of Mathematics, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Kochi Campus, Kochi 682024, IndiaDepartment of Mathematics, Amrita School of Physical Sciences, Amrita Vishwa Vidyapeetham, Kochi Campus, Kochi 682024, IndiaThis study introduces a novel graph-based innovative trend analysis (GBITA) technique for detecting trends in time series data, thus fundamentally challenging conventional assumptions in trend assessment. Unlike traditional methods, which often rely on the assumption of a serial correlation, the proposed methodology only requires that the data values conform to a non-negative distribution. The effectiveness of GBITA was validated through 200 Monte Carlo simulations, and it was subsequently applied to analyze the productivity and cultivated area of paddy and coconut crops across Kerala and its 14 districts. The results indicate an upward trend in the productivity of both crops; however, the area under paddy cultivation is decreasing, while the coconut cultivation area is increasing. Notably, the southern districts of Kerala exhibited a declining trend in both the productivity and cultivated area for these crops. This innovative approach holds promise for broader applications across various crop varieties and regions, with potential implications for fields such as statistics, economics, and computer science.https://www.mdpi.com/2624-7402/7/2/36graph-based techniqueMonte Carlo simulationsserial correlationtime seriestrend |
| spellingShingle | Chalissery Mincy Thomas Archana Nair A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India AgriEngineering graph-based technique Monte Carlo simulations serial correlation time series trend |
| title | A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India |
| title_full | A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India |
| title_fullStr | A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India |
| title_full_unstemmed | A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India |
| title_short | A Novel Graph-Based Innovative Trend Analysis Technique for Studying the Crop Trends in Kerala, India |
| title_sort | novel graph based innovative trend analysis technique for studying the crop trends in kerala india |
| topic | graph-based technique Monte Carlo simulations serial correlation time series trend |
| url | https://www.mdpi.com/2624-7402/7/2/36 |
| work_keys_str_mv | AT chalisserymincythomas anovelgraphbasedinnovativetrendanalysistechniqueforstudyingthecroptrendsinkeralaindia AT archananair anovelgraphbasedinnovativetrendanalysistechniqueforstudyingthecroptrendsinkeralaindia AT chalisserymincythomas novelgraphbasedinnovativetrendanalysistechniqueforstudyingthecroptrendsinkeralaindia AT archananair novelgraphbasedinnovativetrendanalysistechniqueforstudyingthecroptrendsinkeralaindia |