Parallel crop planning based on price forecast

2021 ◽  
Author(s):  
Menghan Fan ◽  
Mengzhen Kang ◽  
Xiujuan Wang ◽  
Jing Hua ◽  
Chaoxing He ◽  
...  
Keyword(s):  
Crop Planning ◽  
Price Forecast

scholarly journals The Effect of Renewable Energy Generation on the Electric Power Spot Price of the Japan Electric Power Exchange

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2215 ◽  
Author(s):  
Jun Maekawa ◽  
Bui Hai ◽  
Sarana Shinkuma ◽  
Koji Shimada
Keyword(s):  
Electric Power ◽  
Panel Data Analysis ◽  
Renewable Energies ◽  
Policy Implications ◽  
Spot Price ◽  
Price Forecast ◽  
Weather Information ◽  
Power Exchange ◽  
Renewable Energy Generation ◽  
The Relationship

This study aims to explore the relationship between renewable energies and the electric power spot price of the Japan Electric Power Exchange (JEPX). By using panel data analysis and proxy modeling, this work attempts to estimate how renewable energies (displayed through the proxies) and other factors influence the electric power spot price in Japan. Based on an analysis of the estimations, some policy implications have been proposed, such as to incorporate weather information into the price forecast, or to provide a guide to more effectively transact on the JEPX.

Boston Housing Price Forecast Based on HMM

2021 ◽  
Author(s):  
Ruhua Lu ◽  
Shuangwei Wang ◽  
Yalan Li
Keyword(s):  
Housing Price ◽  
Price Forecast

scholarly journals EQUIPMENT PRICE FORECAST BASED ON T-S FUZZY NEURAL NETWORK

2018 ◽  
Vol 48 (4) ◽  
pp. 305-309
Author(s):  
G. P. JIANG ◽  
L. XIE ◽  
S. X. SUN
Keyword(s):  
Neural Network ◽  
Wavelet Neural Network ◽  
Test Results ◽  
Factors Affecting ◽  
Price Forecast ◽  
Network Algorithm ◽  
Auction Price ◽  
Variable Weight ◽  
Fuzzy Neural ◽  
Neural Network Algorithm

As we all know, the factors affecting the price of equipment are more complicated, but these factors still have a great correlation. How can we accurately predict the price of equipment? Based on the study of the tight support and smoothness of wavelet function, this paper proposes a correlation variable weight wavelet neural network algorithm to predict the price of 162 devices. The test results show that if the weight is not reduced, the predicted price is 0, and the error is still large. However, by arranging the data from small to large, the variable weighted wavelet neural network algorithm is used to predict the result closer to the auction price, which overcomes the incompatibility of the algorithm iteration and provides a reference for accurately predicting the price of the device.

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