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Prediction Of Lamp Price Using Adaptive Neuro Fuzzy Inference System
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ridwan, Mohammad |
| Copyright Year | 2018 |
| Abstract | Precise Lamp predictions lead to the optimal allocation of resources, efficiency improvements, and increased company revenue. to forecast the price of building lights is a type of non-linear prediction. In this study, periodic data with time range of data from Jan-2009 to Dec-2015 used as prediction process parameter using ANFIS. The research method was started by mapping data into 4 input parameters and 1 output result, followed by training and testing 3 times with data classification period 1-19, 2-20, and 321. The result of the research Prediction of price using ANFIS model based on 63 data with 3 variant of light and input parameter that include number of membership function = 2, membership function type Trapezium, error goal 0, and epoch Maximum 100 able to give value of RMSE=0.05, MAPE=5.62, and produces predictive price according to actual data with percentage difference of 1,65x10-3. |
| File Format | PDF HTM / HTML |
| DOI | 10.4108/eai.24-10-2018.2280522 |
| Alternate Webpage(s) | http://eudl.eu/pdf/10.4108/eai.24-10-2018.2280522 |
| Alternate Webpage(s) | https://doi.org/10.4108/eai.24-10-2018.2280522 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
