کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
481578 1446151 2009 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Logistic evolutionary product-unit neural networks: Innovation capacity of poor Guatemalan households
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
Logistic evolutionary product-unit neural networks: Innovation capacity of poor Guatemalan households
چکیده انگلیسی

A new logistic regression algorithm based on evolutionary product-unit (PU) neural networks is used in this paper to determine the assets that influence the decision of poor households with respect to the cultivation of non-traditional crops (NTC) in the Guatemalan Highlands. In order to evaluate high-order covariate interactions, PUs were considered to be independent variables in product-unit neural networks (PUNN) analysing two different models either including the initial covariates (logistic regression by the product-unit and initial covariate model) or not (logistic regression by the product-unit model). Our results were compared with those obtained using a standard logistic regression model and allow us to interpret the most relevant household assets and their complex interactions when adopting NTC, in order to aid in the design of rural policies.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 195, Issue 2, 1 June 2009, Pages 543–551
نویسندگان
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