By Ger Devlin
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R. (1974). Simulation: methodology and application in agricultural economics. Review of Marketing and Agricultural Economics, Vol. 42, No. 1, (March 1974) pp. ; Khalghani, J. & Partovi, M. (2005). A decision support system for post-emergence weed management in winter wheat, Proccedings of the 5th conference of the European Federation for Information Technology in Agriculture, 3rd World Congress on Computer in Agriculture and Natural Resources, pp. 63-66, Vila Real, Portugal, 25-28 July 2005 BCPC (2000).
4. Membership function used to convert a suitability criterion (in this example, the distance to the nearest high voltage power line is given in meters) into a suitability index. 3 Criteria aggregation • Constraint Criteria Composite constraint maps are produced in two stages. The first stage involves aggregating criteria by level of constraint, while the second stage involves applying the highest level of constraint to each pixel of the general map. The database also contains intermediate maps which show - for each pixel - the number of criteria per level of constraint, or the clustered pixel area for a given level of constraint.
The results from this learning process are called neurons. Neurons arrange themselves in a level form and have connection lines to transfer or process data from input, hidden and output layers. Each connection line presents weights between each layer connection. Moreover, neurons adjust their weights via an activation function, which is the processing function to create the results, to calculate the desirable results (Fausett, 1994; Sangpong & Chaveesuk, 2007). The activation function deployed in this study is the sigmoid function, which is a nonlinear function.