کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4947463 | 1439578 | 2017 | 25 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Verification and predicting temperature and humidity in a solar greenhouse based on convex bidirectional extreme learning machine algorithm
ترجمه فارسی عنوان
بررسی و پیش بینی دما و رطوبت در یک گلخانه خورشیدی بر اساس الگوریتم ماشین محاسباتی افقی دو طرفه محدب
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کلمات کلیدی
گلخانه خورشیدی، ماشین بردار پشتیبانی، تابع پایه شعاعی، محدوده دو طرفه دستگاه یادگیری افراطی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Predictions regarding the solar greenhouse temperature and humidity are important because they play a critical role in greenhouse cultivation. On account of this, it is important to set up a predictive model of temperature and humidity that would precisely predict the temperature and humidity, reducing potential financial losses. This paper presents a novel temperature and humidity prediction model based on convex bidirectional extreme learning machine (CB-ELM). Simulation results show that the convergence rate of the bidirectional extreme learning machine (B-ELM) can further be improved while retaining the same simplicity, by simply recalculating the output weights of the existing nodes based on a convex optimization method when a new hidden node is randomly added. The performance of the CB-ELM model is compared with other modeling approaches by applying it to predict solar greenhouse temperature and humidity. The experiment results show that the CB-ELM model predictions are more accurate than those of the B-ELM, Back Propagation Neural Network (BPNN), Support Vector Machine (SVM), and Radial Basis Function (RBF). Therefore, it can be considered as a suitable and effective method for predicting the solar greenhouse temperature and humidity.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 249, 2 August 2017, Pages 72-85
Journal: Neurocomputing - Volume 249, 2 August 2017, Pages 72-85
نویسندگان
Weidong Zou, Fenxi Yao, Baihai Zhang, Chaoxing He, Zixiao Guan,