Abstract:
Agriculture crop prices forecasting is a very
interesting and high challenging process as it is fully dependent
on upcoming production in entire country. Recently most
available application is designed for price analysis rather than
price forecasting. In India agriculture production, when it is
calculated per farmer, it is very instable is there compare to rest
of the world, when compared to individual farmer in various
countries with stable environment, and without providing
sufficient MSP it will not benefit farmers and agriculture
fraternity. If the farmers and agriculture fraternity get an access
to appropriate crop prices, then poverty can be reduced in India.
In advanced agriculture development, a large quantity of data is
generated from the agriculture commodity market. Agriculture
has a large amount of data, however regrettably, most of this
data is not extracted to find out unseen information in data—
crop price forecast is more beneficial to the farmers and
agriculture fraternity to take proper and timely decisions.
According to the output of process, Advanced data mining
techniques play a pivotal role in analysis to discover a hidden
pattern in data. Performance of data mining techniques is
compared with past crop prices, weather, current market prices,
stock availability and the upcoming production of the crop in
recent years. The data mining that is a regression analysis,
Tracking Patterns, Cluster Analysis, and visualization techniques
are used to create an inventive representation to predict the
agricultural crop prices.
