Prognostication of environmental indices in potato production using artificial neural networks

The artificial neural network for solar radiation prediction and designing solar systems: a systematic literature review

“…ANN has successfully been employed for the solar radiation prediction and solar systems design that is essential for clean environment. Recently ANN is also used for predicting the environmental impacts by assessing the green house crops (Khoshnevisan et al, 2014;Khoshnevisan, Rafiee, Omid, Mousazadeh, & Sefeedpari, 2013). ANNs utilize neurons and simple processing units, combine data, and store relationships between independent and dependent variables.…”

“…There are mainly two sorts of solar energy systems employed, namely thermal and electrical. Thermal solar systems are often applied for space heating, space cooling, heat generation processes and water heating (Khoshnevisan et al, 2013). Solar power is converted into electricity in two ways:…”

“…However, if the MAPE value is between 50% and 20%, a reasonable prediction has been obtained. If MAPE is between 20% and 10%, it means that a good prediction has been achieved, while the best prediction is only achieved when MAPE is less than 10% (Khoshnevisan et al, 2013). The values obtained from these accuracy formulas are noted for monthly/daily, hourly solar radiation prediction and depicted in table 6, 7 and 8.…”

Prediction of global horizontal solar irradiance in Zimbabwe using artificial neural networks

“…The results in Table 11 show a MAPE of 5.9% and 7.6% for GHI prediction for the day before and the day after, respectively. According to Khoshnevisan et al (2013), a MAPE value of less than 10% indicates that the best prediction has been achieved. Therefore, these results demonstrate that the ANN-based model developed in this study can estimate the GHI value for the given data sets.…”

Classification of the Energy and Exergy of Microwave Dryers in Drying Kiwi Using Artificial Neural Networks

“…Instead, the network is trained with experimental data to find the relationship; so they are becoming very popular estimating tools and are known to be efficient and less time-consuming in modeling of complex systems compared to other mathematical models such as regression(B. Khoshnevisan, Sh. Rafiee, M. Omid 2013) The concept of Artificial Neural Networks (ANN) was developed about fifty years ago, but it has been used for practical applications for approximately the last twenty years.…”