Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Indonesia is an agricultural country that relies on the agricultural sector to support the lives of its people. The agricultural sector is dependent on climatic and weather conditions which often cause failure and success in farming. At this time the agriculture department has never conducted an analysis of climatology data to manage agricultural data so that it is difficult to analyze accurate data. For spatial analysis, climatological data is needed in spatial form. This journal will discuss the process of analyzing climatological spatial data, food security data and crop data of an area combined with the overlay method. So we get a rule related to the relationship between client data and plant data. The output of this journal is spatial-based climatology data modeling for climate visualization and agricultural commodities suitable for planting in certain regions and more accurate agrometeorological data.
Charitas Fibriani. 2020. \u201cOptimization of Agrometeorological and Climatological Information to Reduce Risk Based on Spatial Data Agriculture\u201d. Global Journal of Science Frontier Research - D: Agriculture & Veterinary GJSFR-D Volume 20 (GJSFR Volume 20 Issue D2): .
Crossref Journal DOI 10.17406/GJSFR
Print ISSN 0975-5896
e-ISSN 2249-4626
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Neural Networks and Rules-based Systems used to Find Rational and
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Indonesia is an agricultural country that relies on the agricultural sector to support the lives of its people. The agricultural sector is dependent on climatic and weather conditions which often cause failure and success in farming. At this time the agriculture department has never conducted an analysis of climatology data to manage agricultural data so that it is difficult to analyze accurate data. For spatial analysis, climatological data is needed in spatial form. This journal will discuss the process of analyzing climatological spatial data, food security data and crop data of an area combined with the overlay method. So we get a rule related to the relationship between client data and plant data. The output of this journal is spatial-based climatology data modeling for climate visualization and agricultural commodities suitable for planting in certain regions and more accurate agrometeorological data.
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