کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
85183 158928 2009 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Support vector machines regression and modeling of greenhouse environment
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
پیش نمایش صفحه اول مقاله
Support vector machines regression and modeling of greenhouse environment
چکیده انگلیسی

The greenhouse environment is an uncertain nonlinear system which classical modeling methods cannot solve. Support vector machines regression (SVMR) is well supported by mathematical theory and has a simple structure, good generalization ability, and nonlinear modeling properties. Therefore, SVMR offers a very competent method for modeling the greenhouse environment. However, to deal with uncertainty, the model must be rectified online, and Online Sparse Least-Squares Support Vector Machines Regression (OS_LSSVMR) was developed to solve this problem. OS_LSSVMR reduced the number of training samples through use of a sample dictionary, and consequently LSSVMR has sparse solutions; the training samples were added sequentially, so that OS_LSSVMR has online learning capability. A simplified greenhouse model, in which only greenhouse internal and external air temperatures were considered, was presented, after analyzing the factors in the greenhouse environment. Then the OS_LSSVMR greenhouse model was constructed using real-world data. The resulting model shows a promising performance in the greenhouse environment, with potential improvements if a more complete data setup is used.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers and Electronics in Agriculture - Volume 66, Issue 1, April 2009, Pages 46–52
نویسندگان
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