A given model of yield forecasting using an artificial neural network connects the wheat crop with amount productive moisture in soil, soil fertility, weather, and factors presence pests, diseases, weeds. The difficulty creating a forecast system is correct choice predictors that have greatest impact on yield. To build model, 100 cm layer content nitrogen, phosphorus, humus, acidity were used a...

Crop yield forecasting at national level relies on predictors aggregated from smaller spatial units to larger ones according harvested crop areas. Such areas come land cover maps or reported statistics, both of which can have errors and uncertainties. Sub-national regional minimizes the propagation these some extent. In addition, forecasts provide added value insights stakeholders differences w...

The class of Functional Signal plus Noise (FSN) models is introduced that provides a new, general method for modelling and forecasting time series of economic functions. The underlying, continuous economic function (or ‘signal’) is a natural cubic spline whose dynamic evolution is driven by a cointegrated vector autoregression for the ordinates (or ‘y-values’) at the knots of the spline. The na...

The availability and efficient use of the feed resources in India are the primary drivers to maximize productivity of Indian livestock. Feed security is vital to the livestock management, extent of use, conservation and productivity enhancement. Assessment and forecasting of livestock feed resources are most important for effective planning and policy making. In the present study, 40 years of d...

Data Mining is the process of extracting useful information from large datasets. Data mining techniques till now used in business and corporate sectors may be used in agriculture for data characterization, discrimination and predictive and forecasting purposes. Data mining in agriculture is a novel research field. Recently Knowledge Management in agriculture facilitating extraction, storage, re...

A method for probabilistic forecast of agricultural yield depending on meteorological variability, i.e. forecast of agrometeorological resources, is discussed. Forecast is based on the category of meteorologically possible yield (MPY)–the maximum possible yield for a given variety in the existing meteorological conditions. The forecasting process is realized by a potato production process model...