scholarly journals A Comparative Study of Demand Forecasting Using Winters Model and Neural Network for Automobile Sales during Lockdown in India – A Case Study

2021 ◽  
Vol 7 (8) ◽  
Author(s):  
Mir Mohammed Junaid Basha ◽  
Kavya C. ◽  
Prathiksha B. B. ◽  
Vikram N. Bahadurdesai
Keyword(s):  
Neural Network ◽  
Comparative Study ◽  
Demand Forecasting ◽  
Automobile Sales

Research on BP Neural Network Model for Water Demand Forecasting and its Application

2012 ◽  
Vol 170-173 ◽  
pp. 2352-2355 ◽  
Author(s):  
Yue Feng Sun ◽  
Hao Tian Chang ◽  
Zheng Jian Miao
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Water Demand ◽  
Demand Forecasting ◽  
Water Demand Forecasting ◽  
Trial And Error Method ◽  
Bp Neural Network Model ◽  
Resources Planning ◽  
Error Method

It is difficult to determine a proper neurons number of the mid-layer when using the BP neural network for water demand forecasting. Aiming at the problem, the BP neural network is presented in this paper for water demand forecasting. A suitable neurons number in the mid-layer is calculated based on the empirical formula method and trial and error method. A certain basin in China is taken as a case study. The results indicate that the mean relative error is 2.42%. The water consumption is 42.8 billion m3 in 2015 and 43.6 billion m3 in 2030 in the study area. The results are useful for water resources planning and management.

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