A PATTERN FOR THE SUCCESS OF AGRICULTURAL INVESTMENT PROJECTS

摘要: Introduction Agriculture still constitutes the backbone of rural economy and is an engine household income growth in developing countries. According to evidence, agriculture sector has important role also Islamic Republic Iran. Thus, order promote economy, development programs policies have been focused on agricultural investments. Although focus was agriculture, investment not completely successful faced with challenges recent years. In particular, Zanjan Province, most investments from Small Medium Agricultural Enterprises (SMAEs) over period 2005-2010. The facts indicate that SMAEs successful, so, alongside favored projects, there are some unsuccessful projects. Therefore, two groups projects (successful, failed). Failure resulted losses resources it high costs for firm, society finally country’s prevent best resource allocation, Success/failure should be recognized separated beforehand. This study aims introduce a pattern recognizing predicting failure enterprise by classifying failed non-failed based predictors’ variables. binary classification problem this research. Neural Network (NN) widely used investigate problems, NN presents several advantages compared traditional methods such as logic discriminate analysis. Among models, Multi-layer Perceptron (MLP) common neural network problems like failure/success project prediction. addition, review literature, Investment Climate (IC), properties, individual characteristic investor effective factors growth, therefore they can predictors each project’s failure/success.